Accurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients' treatment. The current heavy ...workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on daily image analyses.
Based on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC diagnosis using weakly labeled pathological whole-slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, > 14,680 WSIs, from > 9631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, the USA, and Germany.
Our innovative AI tool consistently and nearly perfectly agreed with (average Kappa statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multicenters. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.988 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells.
This first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. It will drastically alleviate the heavy clinical burden of daily pathology diagnosis and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.
The usefulness of pharmacokinetic parameters for glioma grading has been reported based on the perfusion data from parts of entire-tumor volumes. However, the perfusion values may not reflect the ...entire-tumor characteristics. Our aim was to investigate the feasibility of glioma grading by using histogram analyses of pharmacokinetic parameters including the volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue from T1-weighted dynamic contrast-enhanced perfusion MR imaging.
Twenty-eight patients (14 men, 14 women; mean age, 49.75 years; age range, 25-72 years) with histopathologically confirmed gliomas (World Health Organization grade II, n = 7; grade III, n = 8; grade IV, n = 13) were examined before surgery or biopsy with conventional MR imaging and T1-weighted dynamic contrast-enhanced perfusion MR imaging at 3T. Volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue were calculated from the entire-tumor volume. Histogram analyses from these parameters were correlated with glioma grades. The parameters with the best percentile from cumulative histograms were identified by analysis of the area under the curve of the receiver operating characteristic analysis and were compared by using multivariable stepwise logistic regression analysis for distinguishing high- from low-grade gliomas.
All parametric values increased with increasing glioma grade. There were significant differences among the 3 grades in all parameters (P < .01). For the differentiation of high- and low-grade gliomas, the highest area under the curve values were found at the 98th percentile of the volume transfer constant (area under the curve, 0.912; cutoff value, 0.277), the 90th percentile of extravascular extracellular space volume per unit volume of tissue (area under the curve, 0.939; cutoff value, 19.70), and the 84th percentile of blood plasma volume per unit volume of tissue (area under the curve, 0.769; cutoff value, 11.71). The 98th percentile volume transfer constant value was the only variable that could be used to independently differentiate high- and low-grade gliomas in multivariable stepwise logistic regression analysis.
Histogram analysis of pharmacokinetic parameters from whole-tumor volume data can be a useful method for glioma grading. The 98th percentile value of the volume transfer constant was the most significant measure.
This study explored programme recipients' and deliverers' experiences and perceived outcomes of accessing or facilitating a grocery gift card (GGC) programme from I Can for Kids (iCAN), a ...community-based programme that provides GGC to low-income families with children.
This qualitative descriptive study used Freedman et al's framework of nutritious food access to guide data generation and analysis. Semi-structured interviews were conducted between August and November 2020. Data were analysed using directed content analysis with a deductive-inductive approach.
Fifty-four participants were purposively recruited, including thirty-seven programme recipients who accessed iCAN's GGC programme and seventeen programme deliverers who facilitated it.
Calgary, Alberta, Canada.
Three themes were generated from the data. First, iCAN's GGC programme promoted a sense of autonomy and dignity among programme recipients as they appreciated receiving financial support, the flexibility and convenience of using GGC, and the freedom to select foods they desired. Recipients perceived these benefits improved their social and emotional well-being. Second, recipients reported that the use of GGC improved their households' dietary patterns and food skills. Third, both participant groups identified programmatic strengths and limitations.
Programme recipients reported that iCAN's GGC programme provided them with dignified access to nutritious food and improved their households' finances, dietary patterns, and social and emotional well-being. Increasing the number of GGC provided to households on each occasion, establishing clear and consistent criteria for distributing GGC to recipients, and increasing potential donors' awareness of iCAN's GGC programme may augment the amount of support iCAN could provide to households.
We aimed to establish whether programmed cell death-1 (PD-1) and programmed cell death ligand 1 (PD-L1) expression, in ovarian cancer tumor tissue and blood, could be used as biomarkers for ...discrimination of tumor histology and prognosis of ovarian cancer.
Immune cells were separated from blood, ascites, and tumor tissue obtained from women with suspected ovarian cancer and studied for the differential expression of possible immune biomarkers using flow cytometry. PD-L1 expression on tumor-associated inflammatory cells was assessed by immunohistochemistry and tissue microarray. Plasma soluble PD-L1 was measured using sandwich ELISA. The relationships among immune markers were explored using hierarchical cluster analyses.
Biomarkers from the discovery cohort that associated with PD-L1
cells were found. PD-L1
CD14
cells and PD-L1
CD11c
cells in the monocyte gate showed a distinct expression pattern when comparing benign tumors and epithelial ovarian cancers (EOCs)-confirmed in the validation cohort. Receiver operating characteristic curves showed PD-L1
and PD-L1
CD14
cells in the monocyte gate performed better than the well-established tumor marker CA-125 alone. Plasma soluble PD-L1 was elevated in patients with EOC compared with healthy women and patients with benign ovarian tumors. Low total PD-1
expression on lymphocytes was associated with improved survival.
Differential expression of immunological markers relating to the PD-1/PD-L1 pathway in blood can be used as potential diagnostic and prognostic markers in EOC. These data have implications for the development and trial of anti-PD-1/PD-L1 therapy in ovarian cancer.
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Adenoviruses (Ad) have been investigated for their efficacy in reducing primary tumors after local intratumoral administration. Despite high Ad concentrations and repetitive administration, the ...therapeutic efficacy of Ad has been limited because of rapid dissemination of the Ad into the surrounding normal tissues and short maintenance of Ad biological activity in vivo. To maximize the therapeutic potential of Ad-mediated gene therapeutics, we investigated the efficacy of local, sustained Ad delivery, using an injectable alginate gel matrix system. The biological activity of Ad loaded in alginate gel was prolonged compared with naked Ad, as evidenced by the high green fluorescent protein gene transduction efficiency over an extended time period. Moreover, oncolytic Ad encapsulated in alginate gel elicited 1.9- to 2.4-fold greater antitumor activity than naked Ad in both C33A and U343 human tumor xenograft models. Histological and quantitative PCR analysis confirmed that the oncolytic Ad/alginate gel matrix system significantly increased preferential replication and dissemination of oncolytic Ad in a larger area of tumor tissue in vivo. Taken together, these results show that local sustained delivery of oncolytic Ad in alginate gel augments therapeutic effect through selective infection of tumor cells, sustained release and prolonged maintenance of Ad activity.
Targeted therapies using small-molecule inhibitors (SMIs) are commonly used in metastatic renal cell cancer (mRCC) patients; patients often develop drug resistance and eventually succumb to disease. ...Currently, understanding of mechanisms leading to SMIs resistance and any identifiable predictive marker(s) are still lacking. We discovered that DAB2IP, a novel Ras-GTPase-activating protein, was frequently epigenetically silenced in RCC, and DAB2IP loss was correlated with the overall survival of RCC patients. Loss of DAB2IP in RCC cells enhances their sensitivities to growth factor stimulation and resistances to SMI (such as mammalian target of rapamycin (mTOR) inhibitors). Mechanistically, loss of DAB2IP results in the activation of extracellular signal-regulated kinase/RSK1 and phosphoinositide-3 kinase/mTOR pathway, which synergizes the induction of hypoxia-inducible factor (HIF)-2α expression. Consequently, elevated HIF-2α suppresses p21/WAF1 expression that is associated with resistance to mTOR inhibitors. Thus combinatorial targeting both pathways resulted in a synergistic tumor inhibition. DAB2IP appears to be a new prognostic/predictive marker for mRCC patients, and its function provides a new insight into the molecular mechanisms of drug resistance to mTOR inhibitors, which also can be used to develop new strategies to overcome drug-resistant mRCC.
Summary
The association between potential long‐term effects of previous schistosome infection (PSI) and the development of metabolic syndrome remains unknown. Therefore, we aimed to evaluate the ...association between them. Participants were from regions which were all reportedly heavily endemic for S. japonicum in China 40 years ago. One thousand five hundred and ninety‐seven men were enrolled. Among these, 465 patients with PSI were selected as study subjects and 1132 subjects served as controls. We found PSI significantly correlated with lower prevalences of metabolic syndrome and its components, including central obesity, hypertriglyceridemia and low high‐density lipoprotein cholesterol, which indicates that the potential long‐term effects of PSI may reduce the risk of metabolic syndrome. However, further studies are needed to investigate the protective immune effects of PSI.
No report has been published on the use of DSC MR imaging, DCE MR imaging, and DWI parameters in combination to create a prognostic prediction model in glioblastoma patients. The aim of this study ...was to develop a machine learning-based model to find preoperative multiparametric MR imaging parameters associated with prognosis in patients with glioblastoma. Normalized CBV, volume transfer constant, and ADC of the nonenhancing T2 high-signal-intensity lesions were evaluated using K-means clustering.
A total of 142 patients with glioblastoma who underwent preoperative MR imaging and total resection were included in this retrospective study. From the normalized CBV, volume transfer constant, and ADC maps, the parametric data were sorted using the K-means clustering method. Patients were divided into training and test sets (ratio, 1:1), and the optimal number of clusters was determined using receiver operating characteristic analysis. Kaplan-Meier survival analysis and log-rank tests were performed to identify potential parametric predictors. A multivariate Cox proportional hazard model was conducted to adjust for clinical predictors.
The nonenhancing T2 high-signal-intensity lesions were divided into 6 clusters. The cluster (class 4) with the relatively low normalized CBV and volume transfer constant value and the lowest ADC values was most associated with predicting glioblastoma prognosis. The optimal cutoff of the class 4 volume fraction of nonenhancing T2 high-signal-intensity lesions predicting 1-year progression-free survival was 9.70%, below which the cutoff was associated with longer progression-free survival. Two Kaplan-Meier curves based on the cutoff value showed a statistically significant difference (
= .037). When we adjusted for all clinical predictors, the cluster with the relatively low normalized CBV and volume transfer constant values and the lowest ADC value was an independent prognostic marker (hazard ratio, 3.04;
= .048). The multivariate Cox proportional hazard model showed a concordance index of 0.699 for progression-free survival.
Our model showed that nonenhancing T2 high-signal-intensity lesions with the relatively low normalized CBV, low volume transfer constant values, and the lowest ADC values could serve as useful prognostic imaging markers for predicting survival outcomes in patients with glioblastoma.
Cancer stem cell (CSC), the primary source of cancer-initiating population, is involved in cancer recurrence and drug-resistant phenotypes. This study demonstrates that the loss of DAB2IP, a novel ...Ras-GTPase activating protein frequently found in many cancer types, is associated with CSC properties. Mechanistically, DAB2IP is able to suppress stem cell factor receptor (c-kit or CD117) gene expression by interacting with a newly identified silencer in the c-kit gene. Moreover, DAB2IP is able to inhibit c-kit-PI3K-Akt-mTOR signaling pathway that increases c-myc protein to activate ZEB1 gene expression leading to the elevated CSC phenotypes. An inverse correlation between CD117 or ZEB1 and DAB2IP is also found in clinical specimens. Similarly, Elevated expression of ZEB1 and CD117 are found in the prostate basal cell population of DAB2IP knockout mice. Our study reveals that DAB2IP has a critical role in modulating CSC properties via CD117-mediated ZEB1 signaling pathway.
(
) promoter methylation status in primary and recurrent glioblastoma may change during treatment. The purpose of this study was to correlate
promoter methylation status changes with DWI and DSC PWI ...features in patients with recurrent glioblastoma after standard treatment.
Between January 2008 and November 2016, forty patients with histologically confirmed recurrent glioblastoma were enrolled. Patients were divided into 3 groups according to the
promoter methylation status for the initial and recurrent tumors: 2 groups whose
promoter methylation status remained, group methylated (
= 13) or group unmethylated (
= 18), and 1 group whose
promoter methylation status changed from methylated to unmethylated (
= 9). Normalized ADC and normalized relative CBV values were obtained from both the enhancing and nonenhancing regions, from which histogram parameters were calculated. The ANOVA and the Kruskal-Wallis test followed by post hoc tests were performed to compare histogram parameters among the 3 groups. The
test and Mann-Whitney
test were used to compare parameters between group methylated and group methylated to unmethylated. Receiver operating characteristic curve analysis was used to measure the predictive performance of the normalized relative CBV values between the 2 groups.
Group methylated to unmethylated showed significantly higher means and 90th and 95th percentiles of the cumulative normalized relative CBV values of the nonenhancing region of the initial tumor than group methylated and group unmethylated (all
< .05). The mean normalized relative CBV value of the nonenhancing region of the initial tumor was the best predictor of methylation status change (
< .001), with a sensitivity of 77.78% and specificity of 92.31% at a cutoff value of 2.594.
promoter methylation status might change in recurrent glioblastoma after standard treatment. The normalized relative CBV values of the nonenhancing region at the first preoperative MR imaging were higher in the
promoter methylation change group from methylation to unmethylation in recurrent glioblastoma.
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