MRI Texture Analysis Reflects Histopathology Parameters in Thyroid Cancer – A First Preliminary Study

OBJECT: Thyroid cancer represents the most frequent malignancy of the endocrine system with an increasing incidence worldwide. Novel imaging techniques are able to further characterize tumors and even predict histopathology features. Texture analysis is an emergent imaging technique to extract extensive data from an radiology images. The present study was therefore conducted to identify possible associations between texture analysis and histopathology parameters in thyroid cancer. METHODS: The radiological database was retrospectively reviewed for thyroid carcinoma. Overall, 13 patients (3 females, 23.1%) with a mean age of 61.6 years were identified. The MaZda program was used for texture analysis. The T1-precontrast and T2-weighted images were analyzed and overall 279 texture feature for each sequence was investigated. For every patient cell count, Ki67-index and p53 count were investigated. RESULTS: Several significant correlations between texture features and histopathology were identified. Regarding T1-weighted images, S(0;1)Sum Averg correlated the most with cell count (r = 0.82). An inverse correlations with S(5;0)AngScMom, S(5;0)DifVarnc S(5;0), DiffEntrp and GrNonZeros (r = ?0.69, ?0.66, ?0.69 and ?0.63, respectively) was also identified. For T2-weighted images, Variance with r = 0.63 was the highest coefficient, WavEnLL_S3 correlated inversely with cell count (r = ?0.57). WavEnLL_S2 derived from T1-weighted images was the highest coefficient r = ?0.80, S(0;5)SumVarnc was positively with r = 0.74. Regarding T2-weighted images WavEnHL_s-1 was inverse correlated with Ki67 index (r = ?0.77). S(1;0)Correlat was with r = 0.75 the best correlation with Ki67 index. For T1-weighed images S(5;0)SumofSqs was the best with r = 0.65 with p53 count. For T2-weighted images S(1;?1)SumEntrp was the inverse correlation with r = ?0.72, whereas S(0;4)AngScMom correlated positively with r = 0.63. CONCLUSIONS: MRI texture analysis derived from conventional sequences reflects histopathology features in thyroid cancer. This technique might be a novel noninvasive modality to further characterize thyroid cancer in clinical oncology.     

Histogram Analysis Parameters Apparent Diffusion Coefficient for Distinguishing High and Low-Grade Meningiomas: A Multicenter Study

Low grade meningiomas have better prognosis than high grade meningiomas. The aim of this study was to measure apparent diffusion coefficient (ADC) histogram analysis parameters in different meningiomas in a large multicenter sample and to analyze the possibility of several parameters for predicting tumor grade and proliferation potential. Overall, 148 meningiomas from 7 institutions were evaluated in this retrospective study. Grade 1 lesions were diagnosed in 101 (68.2%) cases, grade 2 in 41 (27.7%) patients, and grade 3 in 6 (4.1%) patients. All tumors were investigated by MRI (1.5 T scanner) by using diffusion weighted imaging (b values of 0 and 1000 s/mm²). For every lesion, the following parameters were calculated: mean ADC, maximum ADC, minimum ADC, median ADC, mode ADC, ADC percentiles P10, P25, P75, P90, kurtosis, skewness, and entropy. The comparison of ADC values was performed by Mann–Whitney-U test. Correlation between different ADC parameters and KI 67 was calculated by Spearman's rank correlation coefficient. Grade 2/3 meningiomas showed statistically significant lower ADC histogram analysis parameters in comparison to grade 1 tumors, especially ADC median. A threshold value of 0.82 for ADC median to predict tumor grade was estimated (sensitivity?=?82.2%, specificity?=?63.8%, accuracy?=?76.4%, positive and negative predictive values were 83% and 62.5%, respectively).All ADC parameters except maximum ADC showed weak significant correlations with KI 67, especially ADC P25 (P?=??.340, P?=?.0001).     

Association Between Background Parenchymal Enhancement and Pathologic Complete Remission Throughout the Neoadjuvant Chemotherapy in Breast Cancer Patients

PURPOSE: To retrospectively investigate the quantitative background parenchymal enhancement (BPE) of the contralateral normal breast in patients with unilateral invasive breast cancer throughout multiple monitoring points of neoadjuvant chemotherapy (NAC) and to further determine whether BPE is associated with tumor response, especially at the early stage of NAC. MATERIALS AND METHODS: A total of 90 patients with unilateral breast cancer who then received six or eight cycles of NAC before surgery were analyzed retrospectively. BPE was measured in dynamic contrast-enhanced MRI at baseline and after 2nd, 4th, and 6th NAC, respectively. Correlation between BPE and tumor size was analyzed, and the association between pathologic complete remission (pCR) and BPE was also analyzed. RESULTS: The BPE of contralateral normal breast showed a constant reduction throughout NAC therapy regardless of the menopausal status (P < .001 in all). Both the BPEs and the changes of BPE in each of the three monitoring points were significantly correlated with those in tumor size (P < .05 in all), and the reduction of BPE after 2nd NAC had the largest diagnostic value for pCR (AUC = 0.726, P < .001), particularly in hormonal receptor (HR)-negative patients (OR = 0.243, 95%CI = 0.083 to 0.706, P = .009). CONCLUSION: The BPE of contralateral normal breast had a constant decreased tendency similar to the change of tumor size in NAC. Reduction of BPE at the early stage of NAC was positively associated with pCR, especially in HR-negative status.     

Prognostic Value of Molecular Breast Cancer Subtypes based on Her2, ESR1, PGR and Ki67 mRNA-Expression in Muscle Invasive Bladder Cancer

INTRODUCTION: Gene expression analyses have identified similarities between bladder and breast cancer, where clinical risk stratification is based on Her2, ESR1, PGR and Ki67 expression. The aim of the study was to assess the respective marker gene expression in patients treated with radical cystectomy for muscle-invasive bladder cancer (MIBC) and to evaluate the applicability of breast cancer subtypes for MIBC risk stratification. MATERIALS & METHODS: 102 patients treated with radical cystectomy for MIBC were assessed. Using routine FFPE tissue and an IVD validated kit, mRNA expression was measured by single step RT-qPCR. Partition test were employed to define cut-off values for high or low marker gene expression. Association of expression with outcome was assessed using Kaplan-Meier analysis and multivariate cox regression analysis. Finally, we performed validation of our results in the MD-Anderson cohort (n = 57). RESULTS: Cancer specific survival (CSS) was impaired in patients with high gene expression of Her2 (P = 0.0009) and ESR1 (P = 0.04). In the multivariate regression model Her2 expression remained significant for the prediction of CSS (HR = 2.11, CI 1.11-4.21, P = 0.024). Furthermore, molecular stratification by breast cancer subgroups was significant (P = 0.023) for CSS prediction. Especially the differentiation between Her2-positive and Luminal A (HR = 4.41, CI 1.53-18.71, P = 0.004) and Luminal B (HR = 1.96, CI 0.99-4.08, P = 0.053) respectively was an independent prognostic parameter for CSS. External validation resulted in comparable risk stratification with differences in fractional subgroups distribution. CONCLUSION: Gene expression of Her2, ESR1, PGR, Ki67 and corresponding breast cancer subtypes allow a risk-stratification in MIBC, whereby Her2 overexpressing tumors reveal a particularly poor prognosis.     

Opioid-specific recognition sites of the mu- and the delta-type in rat striatum after lesions with kainic acid

The binding of 3H-dihydromorphine (3H-DHM) and of 3H-D-ala2, D-leu5-enkephalin (3H-DADL), which are regarded as relatively selective ligands for mu- or delta-type opioid receptors, respectively, was estimated in total particulate fraction of the striatum of rats in vitro, either in tissue of rats after striatal chemolesions with kainic acid or in control rats (not operated or saline injected into the striatum). Kainate lesions reduced the Bmax values of 3H-DHM by about 78 - 88% depending on the method of calculation, and of 3H-DADL by greater than 90%. Furthermore they lowered the Kd-values, suggesting an increase in affinity. The results are discussed with regard to recent hypotheses on the structure and function of opioid receptors.     

Expression and Functional Characterization of the BNIP3 Protein in Renal Cell Carcinomas

BNIP3 (Bcl-2/adenovirus E1B 19-kDa interacting protein 3) is a BH3-only protein that regulates apoptosis and autophagy. BNIP3 plays also an important role in hypoxia-induced cell response and is regulated by HIF1. Here, we studied a possible association of BNIP3 expression and the prognosis of patients with renal cell carcinomas (RCCs) and examined the functional relevance of BNIP3 in the regulation of cell survival and apoptosis of renal carcinoma cells. BNIP3 expression was determined by immunohistochemistry in RCC tumor tissue samples of 569 patients using a tissue microarray. Functional characterization of BNIP3 in renal carcinoma cells indicates prosurvival effects. In human RCC tumor samples, high cytoplasmic BNIP3 expression was associated with high-grade RCCs and regional lymph node metastasis. BNIP3 expression correlated negatively with disease-specific survival. Multivariate Cox regression analysis retained BNIP3 expression as an independent prognostic factor in patients without distant metastasis. Together, our studies imply that BNIP3 regulates cell survival in RCCs and its expression is an independent prognostic marker in patients with localized RCCs.     

Can Imaging Parameters Provide Information Regarding Histopathology in Head and Neck Squamous Cell Carcinoma? A Meta-Analysis

OBJECT: Our purpose was to provide data regarding relationships between different imaging and histopathological parameters in HNSCC. METHODS: MEDLINE library was screened for associations between different imaging parameters and histopathological features in HNSCC up to December 2017. Only papers containing correlation coefficients between different imaging parameters and histopathological findings were acquired for the analysis. RESULTS: Associations between ¹⁸F-FDG positron emission tomography (PET) and KI 67 were reported in 8 studies (236 patients). The pooled correlation coefficient was 0.20 (95% CI = [?0.04; 0.44]). Furthermore, in 4 studies (64 patients), associations between ¹⁸F-fluorothymidine PET and KI 67 were analyzed. The pooled correlation coefficient between SUV_max and KI 67 was 0.28 (95% CI = [?0.06; 0.94]). In 2 studies (23 patients), relationships between KI 67 and dynamic contrast-enhanced magnetic resonance imaging were reported. The pooled correlation coefficient between K_trans and KI 67 was ?0.68 (95% CI = [?0.91; ?0.44]). Two studies (31 patients) investigated correlation between apparent diffusion coefficient (ADC) and KI 67. The pooled correlation coefficient was ?0.61 (95% CI = [?0.84; ?0.38]). In 2 studies (117 patients), relationships between ¹⁸F-FDG PET and p53 were analyzed. The pooled correlation coefficient was 0.0 (95% CI = [?0.87; 0.88]). There were 3 studies (48 patients) that investigated associations between ADC and tumor cell count in HNSCC. The pooled correlation coefficient was ?0.53 (95% CI = [?0.74; ?0.32]). Associations between ¹⁸F-FDG PET and HIF-1α were investigated in 3 studies (72 patients). The pooled correlation coefficient was 0.44 (95% CI = [?0.20; 1.08]). CONCLUSIONS: ADC may predict cell count and proliferation activity, and SUV_max may predict expression of HIF-1α in HNSCC. SUV_max cannot be used as surrogate marker for expression of KI 67 and p53.     

US-guided Diffuse Optical Tomography: Clinicopathological Features Affect Total Hemoglobin Concentration in Breast Cancer

PURPOSE: To investigate breast cancers total hemoglobin concentration (THC) characteristics and its association with clinical pathologic findings. MATERIALS AND METHODS: The study was approved by the institutional review board and all patients provided written informed consent. 447 breast cancer patients, totally 455 lesions were included in our study. The size and THC of breast lesions were measured by conventional ultrasound (US) and US-guided Diffuse Optical Tomography (DOT) 1–2?days before surgery. Clinical and pathology information of patients was collected. RESULT: The average THC values of ER- or PR- lesions were significantly higher than the positive ones (P?=?.005 and P?=?.01,respectively); The average THC values of axillar LN+ or LVI+ were higher than the negative ones (P?=?.042 and P?=?.043, respectively). No significant THC difference was found in groups of infiltrating vs. non-infiltrating, HER2+ vs. HER2-, Ki67 high vs. Ki67 low, and different menstrual phases (P?=?.457, P?=?.917, P?=?.417, P?=?.213, respectively).The incidence ages and the lesion-nipple distances of T3 patients were lower than that of T1 and T2 (P?<?.001 and P?<?.001 respectively). The THC values and Ki67 indexes of T2 and T3 lesions were similar, but were higher than that of the T1 group (P?<?=0.001 and P?=?.006, respectively). CONCLUSION: Clinicopathological features of breast cancer, such as ER and PR status, axillary lymph node metastasis, lymphovascular invasion, correlate with THC values. Furthermore, the Ki67 indexes can be predicted using tumor size and THC, useful for pre-surgical evaluation of cancer biology and real-time, non-invasive monitoring of NAC efficacy.     

Predicting Treatment Response of Breast Cancer to Neoadjuvant Chemotherapy Using Ultrasound-Guided Diffuse Optical Tomography

PURPOSE: To prospectively investigate ultrasound-guided diffuse optical tomography (US-guided DOT) in predicting breast cancer response to neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: Eighty-eight breast cancer patients, with a total of 93 lesions, were included in our study. Pre– and post–last chemotherapy, size and total hemoglobin concentration (THC) of each lesion were measured by conventional US and US-guided DOT 1 day before biopsy (time point t0, THC THC0, SIZE S0) and 1 to 2 days before surgery (time point tL, THCL, SL). The relative changes in THC and SIZE of lesions after the first and last NAC cycles were considered as the variables ΔTHC and ΔSIZE. Receiver operating characteristic curve was performed to calculate ΔTHC and ΔSIZE cutoff values to evaluate pathologic response of 93 breast cancers to NAC, which were then prospectively used to predicate response of 61 breast cancers to NAC. RESULTS: The cutoff values of ΔTHC and ΔSIZE for evaluation of breast cancers NAC treatment response were 23.9% and 42.6%. At ΔTHC 23.9%, the predicted treatment response in 61 breast lesions for the time points t1 to t3 was calculated by area under the curve (AUC), which were AUC₁ 0.534 (P = .6668), AUC₂ 0.604 (P = .1893), and AUC₃ 0.674(P =. 0.027), respectively; for ΔSIZE 42.6%, at time points t1 to t3, AUC₁ 0.505 (P = .9121), AUC₂ 0.645 (P = .0115), and AUC₃ 0.719 (P = .0018). CONCLUSION: US-guided DOT ΔTHC 23.9% and US ΔSIZE 42.6% can be used for the response evaluation and earlier prediction of the pathological response after three rounds of chemotherapy.     

Comparison of Two Mathematical Models of Cellularity Calculation

OBJECT: Nowadays, there is increasing evidence that functional magnetic resonance imaging (MRI) modalities, namely, diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI (DCE MRI), can characterize tumor architecture like cellularity and vascularity. Previously, two formulas based on a logistic tumor growth model were proposed to predict tumor cellularity with DWI and DCE. The purpose of this study was to proof these formulas. METHODS: 16 patients with head and neck squamous cell carcinomas were included into the study. There were 2 women and 14 men with a mean age of 57.0 ± 7.5 years. In every case, tumor cellularity was calculated using the proposed formulas by Atuegwu et al. In every case, also tumor cell count was estimated on histopathological specimens as an average cell count per 2 to 5 high-power fields. RESULTS: There was no significant correlation between the calculated cellularity and histopathologically estimated cell count by using the formula based on apparent diffusion coefficient (ADC) values. A moderate positive correlation (r=0.515, P=.041) could be identified by using the formula including ADC and V_e values. CONCLUSIONS: The formula including ADC and V_e values is more sensitive to predict tumor cellularity than the formula including ADC values only.     

Integrated Analysis Identifies Molecular Signatures and Specific Prognostic Factors for Different Gastric Cancer Subtypes

BACKGROUND: Gastric cancer (GC) is the fifth leading cause of cancer-related deaths worldwide. As an effective and easily performed method, microscopy-based Lauren classification has been widely accepted by gastrointestinal surgeons and pathologists for GC subtyping, but molecular characteristics of different Lauren subtypes were poorly revealed. METHODS: GSE62254 was used as a derivation cohort, and GSE15459 was used as a validation cohort. The difference between diffuse and intestinal GC on the gene expression level was measured. Gene ontology (GO) enrichment analysis was performed for both subgroups. Hierarchical clustering and heatmap exhibition were also performed. Kaplan-Meier plot and Cox proportional hazards model were used to evaluate survival grouped by the given genes or hierarchical clusters. RESULTS: A total of 4598 genes were found differentially expressed between diffuse and intestinal GC. Immunity- and cell adhesion–related GOs were enriched for diffuse GC, whereas DNA repair– and cell cycle–related GOs were enriched for intestinal GC. We proposed a 40-gene signature (χ² = 30.71, P < .001) that exhibits better discrimination for prognosis than Lauren classification (χ² = 12.11, P = .002). FRZB [RR (95% CI) = 1.824 (1.115-2.986), P = .017] and EFEMP1 [RR (95% CI) = 1.537 (0.969-2.437), P = .067] were identified as independent prognostic factors only in diffuse GC but not in intestinal GC patients. KRT23 [RR (95% CI) = 1.616 (0.938-2.785), P = .083] was identified as an independent prognostic factor only in intestinal GC patients but not in diffuse GC patients. Similar results were achieved in the validation cohort. CONCLUSION: We found that GCs with different Lauren classifications had different molecular characteristics and identified FRZB, EFEMP1, and KRT23 as subtype-specific prognostic factors for GC patients.     

Correlations Between DCE MRI and Histopathological Parameters in Head and Neck Squamous Cell Carcinoma

BACKGROUND: Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) can characterize perfusion and vascularization of tissues. DCE MRI parameters can differentiate between malignant and benign lesions and predict tumor grading. The purpose of this study was to correlate DCE MRI findings and various histopathological parameters in head and neck squamous cell carcinoma (HNSCC). PATIENTS AND METHODS: Sixteen patients with histologically proven HNSCC (11 cases primary tumors and in 5 patients with local tumor recurrence) were included in the study. DCE imaging was performed in all cases and the following parameters were estimated: K^trans, V_e, K_ep, and iAUC. The tumor proliferation index was estimated on Ki 67 antigen stained specimens. Microvessel density parameters (stained vessel area, total vessel area, number of vessels, and mean vessel diameter) were estimated on CD31 antigen stained specimens. Spearman''s non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters. RESULTS: The mean values of DCE perfusion parameters were as follows: K^trans 0.189 ± 0.056 min⁻¹, K_ep 0.390 ± 0.160 min⁻¹, V_e 0.548 ± 0.119%, and iAUC 22.40 ± 12.57. Significant correlations were observed between K_ep and stained vessel areas (r = 0.51, P = .041) and total vessel areas (r = 0.5118, P = .043); between V_e and mean vessel diameter (r = −0.59, P = .017). Cell count had a tendency to correlate with V_e (r = −0.48, P = .058). In an analysis of the primary HNSCC only, a significant inverse correlation between K^trans and KI 67 was identified (r = −0.62, P = .041). Our analysis showed significant correlations between DCE parameters and histopathological findings in HNSCC.Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) has been reported as a technique which is able to characterize perfusion and vascularization of tissues [1], [2]. It has been shown that DCE MRI can be helpful to differentiate between malignant and benign lesions [1]. For example, Yuan et al. reported that lung cancer had a larger volume transfer constant (K^trans) and a lower volume of the extravascular extracellular leakage space (V_e) in comparison to benign lesions [3]. Similar results were reported by Li et al. for breast lesions [4]. Furthermore, according to Cho et al., DCE MRI parameters can be used to distinguish prostatic cancer from benign changes [5]. Moreover, DCE MRI parameters can also predict tumor grading. As reported previously, K^trans correlated well with Gleason score in prostatic cancer [5], [6]. According to other reports, K^trans and V_e correlated with glioma grade [7], [8].DCE MRI parameters were also associated with prognosis in several malignancies [9], [10]. Koo et al. showed that breast cancers with higher K^trans or lower V_e had poor prognostic factors and were often of the triple-negative subtype [10].According to the literature, DCE MRI parameters can predict response to therapy in different tumors. For instance, some authors mentioned that low pretreatment K^trans in regional lymph node metastases in head and neck cancer was associated with a poor response to concurrent chemoradiation therapy [11].Furthermore, Andersen et al. showed that DCE MR parameters obtained prior to chemoradiotherapy predicted survival of patients with cervical cancer [12].Presumably, DCE MRI parameters may be based on tissue composition, such as cellularity and vascular density. However, in this regard there are contradictory data in the literature. While some studies identified significant correlations between DCE MRI and histopathological parameters, others did not [13], [14], [15], [16].The purpose of this study was to correlate DCE MRI findings and various histopathological parameters in head and neck squamous cell carcinoma (HNSCC).     

The Mutant p53-Targeting Compound APR-246 Induces ROS-Modulating Genes in Breast Cancer Cells

TP53 is the most frequently mutated gene in human cancer and thus an attractive target for novel cancer therapy. Several compounds that can reactive mutant p53 protein have been identified. APR-246 is currently being tested in a phase II clinical trial in high-grade serous ovarian cancer. We have used RNA-seq analysis to study the effects of APR-246 on gene expression in human breast cancer cell lines. Although the effect of APR-246 on gene expression was largely cell line dependent, six genes were upregulated across all three cell lines studied, i.e., TRIM16, SLC7A11, TXNRD1, SRXN1, LOC344887, and SLC7A11-AS1. We did not detect upregulation of canonical p53 target genes such as CDKN1A (p21), 14-3-3σ, BBC3 (PUMA), and PMAIP1 (NOXA) by RNA-seq, but these genes were induced according to analysis by qPCR. Gene ontology analysis showed that APR-246 induced changes in pathways such as response to oxidative stress, gene expression, cell proliferation, response to nitrosative stress, and the glutathione biosynthesis process. Our results are consistent with the dual action of APR-246, i.e., reactivation of mutant p53 and modulation of redox activity. SLC7A11, TRIM16, TXNRD1, and SRXN1 are potential new pharmacodynamic biomarkers for assessing the response to APR-246 in both preclinical and clinical studies.     

Significance of Liquid Biopsy for Monitoring and Therapy Decision of Colorectal Cancer

PURPOSE: Despite therapeutic improvements, all patients with nonresectable metastatic colorectal cancer (mCRC) acquire resistance to treatment probably due to the growth of mutated clones. In contrast to tissue-based studies, liquid biopsies have enabled the opportunity to reveal emerging resistance to treatment by detecting mutated clones and noninvasively monitoring clonal dynamics during therapy. METHODS: The courses of three patients with mCRC who were initially RAS wild-type were monitored longitudinally using liquid biopsy with long-term follow-up of up to 20 sequential samples. Detection of fragmented RAS mutated circulating cell-free DNA (cf)DNA in plasma was performed by BEAMing. In addition, plasma digital droplet PCR was used to detect and quantify BRAF and PIK3CA mutated cfDNA. Changes of mutational load were correlated with imaging data. RESULTS: A combination of liquid biopsy and radiological imaging enabled visualization of the occurrence of clonal redistribution after discontinuation of anti-EGFR mAb therapy, as well as emerging RAS mutations during therapy with anti-EGFR mAb indicating resistance. Furthermore, we found that growth of RAS mutated clones is independent of direct selective pressure by anti-EGFR therapy, which is a significant and new finding of this study. CONCLUSIONS: Our findings demonstrated the whole spectrum of clonal selection and redistribution of mutated cell clones leading to acquired resistance. Given our observation that the growth of RAS mutated clones can evolve even in the absence of anti-EGFR mAb therapy, there is a clear imperative to monitor RAS mutations in serial blood draws in all RAS wild-type patients in general and independent of the therapy.     

Substrate binding site of microsomal cytochrome P-450 directly faces membrane lipids

Cytochrome P-450, purified from liver microsomes of phenobarbital-treated rabbits, was incorporated into dimyristoylphosphatidylcholine liposomes. The binding of benzphetamine to the liposome-bound cytochrome P-450 was examined by measuring the benzphetamine-induced spectral change at various temperatures. The van't Hoff plot of the apparent spectral dissociation constant showed a distinct break at the temperature of phase transition of the synthetic lipid. On the other hand, no such break was observed for benzphetamine binding to microsomal bound cytochrome P-450. These results suggest that the substrate binding site of cytochrome P-450 is embedded in the apolar interior of phospholipid bilayer membranes.     

Impact of Human Cytomegalovirus Infection and its Immune Response on Survival of Patients with Ovarian Cancer

Human cytomegalovirus (HCMV) has been detected in various types of tumors. We studied the prevalence of HCMV in ovarian cancer and its relation to clinical outcome. Paraffin-embedded tissues obtained prospectively from 45 patients with ovarian cancer and 30 patients with benign ovarian cystadenoma were analyzed for expression of HCMV immediate-early protein (IE) and HCMV tegument protein (pp65) by immunohistochemistry. Plasma was analyzed for HCMV serology. HCMV-IgG levels were higher in patients with ovarian cancer or benign cystadenoma than in age-matched controls (P?=?.002, P?<?.0001, respectively). HCMV IgM was detected in 12% of ovarian cancer patients and 3% of patients with benign tumors but was absent in controls. In patients with ovarian cancer, higher IgG levels were associated with better outcomes (P?=?.04). Extensive HCMV-IE protein expression was detected in 75% of ovarian cancers and 26% of benign tumors; pp65 was detected in 67% of ovarian cancers and 14% of benign tumors. A higher grade of HCMV infection was associated with higher stage of disease. Extensive HCMV-pp65 expression was associated with shorter median overall survival than focal expression (39 versus 42.5?months, P?=?.03). At study closure, 58% of ovarian cancer patients with focal pp65 expression were alive versus 27% of patients with extensive pp65 expression (P?=?.03). Thus, HCMV proteins are detected at different levels in ovarian tumors and benign cystadenomas. Ovarian cancer patients with focal HCMV-pp65 expression in their tumors and high IgG levels against HCMV lived longer, highlighting a need for in-depth studies of the oncomodulatory role of HCMV in ovarian cancer.     

Proving of a Mathematical Model of Cell Calculation Based on Apparent Diffusion Coefficient

OBJECTIVES: Recently, Atuegwu et al. proposed a mathematical model based on ADC_mean and ADC_min to calculation of cellularity. Our purpose was to compare the calculated cellularity according to the formula with the estimated cell count by histopathology in different tumors. METHODS: For this study, we re-analyzed our previous data regarding associations between ADC parameters and histopathological findings. Overall, 134 patients with different tumors were acquired for the analysis. For all tumors, the number of tumor cells was calculated according to Atuegwu et al. 2013. We performed a correlation analysis between the calculated and estimated cellularity. Thereby, Pearson's correlation coefficient was used and P < .05 was taken to indicate statistical significance in all instances. RESULTS: The estimated and calculated cellularity correlated well together in HNSCC (r = 0.701, P = .016) and lymphomas (r = 0.661, P = .001), and moderately in rectal cancer (r = 0.510, P = .036). There were no statistically significant correlations between the estimated and calculated cellularity in uterine cervical cancer, meningiomas, and in thyroid cancer. CONCLUSION: The proposed formula for cellularity calculation does not apply for all tumors. It may be used for HNSCC, cerebral lymphomas and rectal cancer, but not for uterine cervical cancer, meningioma, and thyroid cancer. Furthermore, its usefulness should be proved for other tumors.