Compressed Sensitivity Encoding Artificial Intelligence Accelerates Brain Metastasis Imaging by Optimizing Image Quality and Reducing Scan Time.

BACKGROUND AND PURPOSE: Accelerating the image acquisition speed of MR imaging without compromising the image quality is challenging. This study aimed to evaluate the feasibility of contrast-enhanced (CE) 3D T1WI and CE 3D-FLAIR sequences reconstructed with compressed sensitivity encoding artificial intelligence (CS-AI) for detecting brain metastases (BM) and explore the optimal acceleration factor (AF) for clinical BM imaging. MATERIALS AND METHODS: Fifty-one patients with cancer with suspected BM were included. Fifty participants underwent different customized CE 3D-T1WI or CE 3D-FLAIR sequence scans. Compressed SENSE encoding acceleration 6 (CS6), a commercially available standard sequence, was used as the reference standard. Quantitative and qualitative methods were used to evaluate image quality. The SNR and contrast-to-noise ratio (CNR) were calculated, and qualitative evaluations were independently conducted by 2 neuroradiologists. After exploring the optimal AF, sample images were obtained from 1 patient by using both optimized sequences. RESULTS: Quantitatively, the CNR of the CS-AI protocol for CE 3D-T1WI and CE 3D-FLAIR sequences was superior to that of the CS protocol under the same AF (P < .05). Compared with reference CS6, the CS-AI groups had higher CNR values (all P < .05), with the CS-AI10 scan having the highest value. The SNR of the CS-AI group was better than that of the reference for both CE 3D-T1WI and CE 3D-FLAIR sequences (all P < .05). Qualitatively, the CS-AI protocol produced higher image quality scores than did the CS protocol with the same AF (all P < .05). In contrast to the reference CS6, the CS-AI group showed good image quality scores until an AF of up to 10 (all P < .05). The CS-AI10 scan provided the optimal images, improving the delineation of normal gray-white matter boundaries and lesion areas (P < .05). Compared with the reference, CS-AI10 showed reductions in scan time of 39.25% and 39.93% for CE 3D-T1WI and CE 3D-FLAIR sequences, respectively. CONCLUSIONS: CE 3D-T1WI and CE 3D-FLAIR sequences reconstructed with CS-AI for the detection of BM may provide a more effective alternative reconstruction approach than CS. CS-AI10 is suitable for clinical applications, providing optimal image quality and a shortened scan time.

Leptin receptor deficiency impedes metabolic surgery related-weight loss through inhibition of energy expenditure in db/db mice.

BACKGROUND: Roux-en-Y gastric bypass (RYGB) surgery is an effective metabolic surgery against diabetes and obesity. Clinical evidence indicates that patients with severe obesity have a poor curative effect in losing weight if they suffer from leptin or its receptor deficiency, but the underlying mechanism remains elusive. Here, we investigated the effect of leptin receptor deficiency on metabolic dysfunction in db/db mice treated by RYGB surgery. METHODS: The db/db mice and their heterozygote control db/m mice were subjected to RYGB or sham surgery. Body weight, blood glucose, food intake and glucose tolerance were evaluated. Micro-PET/CT and histological analysis were performed to examine the glucose uptake of tissues and the fat changes in mice. The key factors in glucose and fatty acid metabolism were detected by western blot analysis. RESULTS: Compared with the sham group, the db/db mice in the RYGB group showed more significant weight regain after surgical recovery and improvement in hyperinsulinemia and glucose tolerance. However, the total body fat and multiple organ lipid deposition of RYGB-treated db/db mice was increased. The underlying mechanism studies suggested that the activation of AMPK regulated GLUT4 to increase glucose uptake, but AMPK could not promote fatty acid oxidation through the JAK2/STAT3 pathway under leptin receptor deficiency in db/db mice. CONCLUSION: We conclude that leptin receptor deficiency impedes the AMPK activation-mediated fat catabolism but does not affect AMPK-related glucose utilization after metabolic surgery in db/db mice. This result helps select surgical indications for patients with obesity and diabetes.

AHRR and SFRP2 in primary versus recurrent high-grade serous ovarian carcinoma and their prognostic implication.

BACKGROUND: The aim of this study was to analyse transcriptomic differences between primary and recurrent high-grade serous ovarian carcinoma (HGSOC) to identify prognostic biomarkers. METHODS: We analysed 19 paired primary and recurrent HGSOC samples using targeted RNA sequencing. We selected the best candidates using in silico survival and pathway analysis and validated the biomarkers using immunohistochemistry on a cohort of 44 paired samples, an additional cohort of 504 primary HGSOCs and explored their function. RESULTS: We identified 233 differential expressed genes. Twenty-three showed a significant prognostic value for PFS and OS in silico. Seven markers (AHRR, COL5A2, FABP4, HMGCS2, ITGA5, SFRP2 and WNT9B) were chosen for validation at the protein level. AHRR expression was higher in primary tumours (p < 0.0001) and correlated with better patient survival (p < 0.05). Stromal SFRP2 expression was higher in recurrent samples (p = 0.009) and protein expression in primary tumours was associated with worse patient survival (p = 0.022). In multivariate analysis, tumour AHRR and SFRP2 remained independent prognostic markers. In vitro studies supported the anti-tumorigenic role of AHRR and the oncogenic function of SFRP2. CONCLUSIONS: Our results underline the relevance of AHRR and SFRP2 proteins in aryl-hydrocarbon receptor and Wnt-signalling, respectively, and might lead to establishing them as biomarkers in HGSOC.

Structure-function crosstalk in liver cancer research: Protein structuromics.

Liver cancer can be primary (starting in the liver) or secondary (cancer that has spread from elsewhere to the liver, known as liver metastasis). Liver metastasis is more common than primary liver cancer. Despite great advances in molecular biology methods and treatments, liver cancer is still associated with a poor survival rate and a high death rate, and there is no cure. Many questions remain regarding the mechanisms of liver cancer occurrence and development as well as tumor reoccurrence after treatment. In this study, we assessed the protein structural features of 20 oncogenes and 20 anti-oncogenes via protein structure and dynamic analysis methods and 3D structural and systematic analyses of the structure-function relationships of proteins. Our aim was to provide new insights that may inform research on the development and treatment of liver cancer.

Biomarkers for checkpoint inhibitor therapy in mucinous epithelial ovarian cancer.

OBJECTIVE: The prognosis of patients with advanced stage mucinous epithelial ovarian cancer remains poor due to a modest response to platinum-based chemotherapy and the absence of therapeutic alternatives. As targeted approaches may help to overcome these limitations, the present study evaluates biomarkers indicative of potential immune-checkpoint inhibitor therapy response. METHODS: All patients who underwent primary cytoreductive surgery from January 2001 to December 2020 and for whom formalin-fixed paraffin-embedded tissue samples were available were included (n=35; 12 International Federation of Gynecology and Obstetrics (FIGO) stage ≥IIb). To define sub-groups potentially suitable for checkpoint inhibition, expression of programmed death-ligand 1 (PD-L1), tumor-infiltrating lymphocytes (CD3+, CD8+, CD20+, CD45+, CD68+, FoxP3+), and AT-rich interactive domain-containing protein 1A (ARID1A) immunostaining were evaluated in whole tissue sections and compared with clinicopathologic parameters and next-generation sequencing results, where available (n=11). Survival analyses were performed to assess whether identified sub-groups were associated with specific clinical outcomes. RESULTS: In total, 34.3% (n=12/35) of tumors were PD-L1 positive. PD-L1 expression was associated with infiltrative histotype (p=0.027) and correlated with higher CD8+ (r=0.577, p<0.001) and CD45+ (r=0.424, p=0.011), but reduced ARID1A expression (r=-4.39, p=0.008). CD8+ expression was associated with longer progression-free survival (hazard ratio (HR) 0.85 (95% CI 0.72 to 0.99), p=0.047) and disease-specific survival (HR 0.85 (95% CI 0.73 to 1.00), p=0.044) in the sub-group with FIGO stage ≥IIb. Three (8.6%) samples demonstrated high PD-L1 expression at a combined positive score of >10, which was associated with increased CD8+ expression (p=0.010) and loss of ARID1A expression (p=0.034). Next-generation sequencing, which was available for all samples with a combined positive score of >10, showed KRAS mutations, BRCA wild-type status, and mismatch repair proficiency in all cases, but did not reveal genetic alterations potentially associated with a pro-immunogenic tumor environment. CONCLUSIONS: A sub-group of mucinous ovarian cancers appear to demonstrate a pro-immunogenic tumor environment with high PD-L1 expression, decreased ARID1A expression, and characteristic tumor-infiltrating lymphocyte infiltration patterns. Further clinical validation of anti-PD-L1/PD-1 targeting in selected mucinous ovarian cancers appears promising.

[Diagnosis Significance of the Levels of Cytokines IL-6, IL-10 and CXCL-13 in Cerebrospinal Fluid for Central Nervous System Infiltration of Lymphoma].

OBJECTIVE: To evaluate the diagnostic value of the expression levels of cytokines interleukin-6(IL-6), interleukin-10 (IL-10) and chemokine （C-X-C motif） ligand-13 (CXCL-13) in cerebrospinal fluid (CSF) for central nervous system infiltration of lymphoma. METHODS: Forty patients diagnosed as lymphoma or acute lymphoblastic leukemia in General Hospital of Northern Theater Command from July 2020 to July 2021 were collected and recorded their CSF indexes, including pressure, protein, Pandy test, nucleated cell count, glucose and chlorine content in CSF. The levels of cytokines IL-6, IL-10 and CXCL-13 were detected by Enzyme-linked immunosorbent assay. RESULTS: The patients were divided into CNSI (central nervous system infiltration) group and non-CNSI group, the average levels of IL-6, IL-10, CXCL-13 and IL-10/IL-6 ratio in CNSI group were higher than those in non-CNS group, but the difference of IL-10/IL-6 ratio between the two groups was statistically significant (P<0.05). Then the patients were divided into protein elevated(n=14) group and protein normal group(n=26), the levels of IL-6 ï¼» (5.78±2.69) pg/ mlï¼½ and CXCL-13 ï¼»(0.83±0.59) pg/mlï¼½ in protein elevated group were significantly higher than those in the protein normal group ï¼»IL-6: (2.41±1.16) pg/ml; CXCL-13: (0.38±0.18) pg/mlï¼½ (P<0.05). Further analysis of the expression levels of the cytokines in non-CNSI group (n=32), IL-6, IL-10, CXCL-13 level and IL-10/IL-6 ratio in the protein elevated group (n=12) were higher than those in the protein normal group (n=20), but the difference was not statistically significant. CONCLUSION: The levels of IL-6, IL-10 and CXCL-13 in CSF of lymphoma patients with CNS infiltration were higher than those in non-CNS infiltration group, and those in patients with protein elevated group are higher than those in the protein normal group.

Constrained future brightening of solar radiation and its implication for China's solar power.

As Earth's primary energy source, surface downward solar radiation (R s) determines the solar power potential and usage for climate change mitigation. Future projections of R s based on climate models have large uncertainties that interfere with the efficient deployment of solar energy to achieve China's carbon-neutrality goal. Here we assess 24 models in the latest Coupled Model Intercomparison Project Phase 6 with historical observations in China and find systematic biases in simulating historical R s values likely due to model biases in cloud cover and clear-sky radiation, resulting in largely uncertain projections for future changes in R s. Based on emergent constraints, we obtain credible R s with narrowed uncertainties by ∼56% in the mid-twenty-first century and show that the mean R s change during 2050-2069 relative to 1995-2014 is 30% more brightening than the raw projections. Particularly in North China and Southeast China with higher power demand, the constrained projections present more significant brightening, highlighting the importance of considering the spatial changes in future Rs when locating new solar energy infrastructures.

Impact of BRCA Mutation Status on Tumor Dissemination Pattern, Surgical Outcome and Patient Survival in Primary and Recurrent High-Grade Serous Ovarian Cancer: A Multicenter Retrospective Study by the Ovarian Cancer Therapy-Innovative Models Prolong Survival (OCTIPS) Consortium.

BACKGROUND: This study seeks to evaluate the impact of breast cancer (BRCA) gene status on tumor dissemination pattern, surgical outcome and survival in a multicenter cohort of paired primary ovarian cancer (pOC) and recurrent ovarian cancer (rOC). PATIENTS AND METHODS: Medical records and follow-up data from 190 patients were gathered retrospectively. All patients had surgery at pOC and at least one further rOC surgery at four European high-volume centers. Patients were divided into one cohort with confirmed mutation for BRCA1 and/or BRCA2 (BRCAmut) and a second cohort with BRCA wild type or unknown (BRCAwt). Patterns of tumor presentation, surgical outcome and survival data were analyzed between the two groups. RESULTS: Patients with BRCAmut disease were on average 4 years younger and had significantly more tumor involvement upon diagnosis. Patients with BRCAmut disease showed higher debulking rates at all stages. Multivariate analysis showed that only patient age had significant predictive value for complete tumor resection in pOC. At rOC, however, only BRCAmut status significantly correlated with optimal debulking. Patients with BRCAmut disease showed significantly prolonged overall survival (OS) by 24.3 months. Progression-free survival (PFS) was prolonged in the BRCAmut group at all stages as well, reaching statistical significance during recurrence. CONCLUSIONS: Patients with BRCAmut disease showed a more aggressive course of disease with earlier onset and more extensive tumor dissemination at pOC. However, surgical outcome and OS were significantly better in patients with BRCAmut disease compared with patients with BRCAwt disease. We therefore propose to consider BRCAmut status in regard to patient selection for cytoreductive surgery, especially in rOC.

SLCO4A1 expression is associated with activated inflammatory pathways in high-grade serous ovarian cancer.

Patients with high-grade serous ovarian cancer (HGSOC) have a very poor overall survival. Current therapeutic approaches do not bring benefit to all patients. Although genetic alterations and molecular mechanisms are well characterized, the molecular pathological conditions are poorly investigated. Solute carrier organic anion transporter family member 4A1 (SLCO4A1) encodes OATP4A1, which is an uptake membrane transporter of metabolic products. Its expression may influence various signaling pathways associated with the molecular pathophysiological conditions of HGSOC and consequently tumor progression. RNA sequencing of 33 patient-derived HGSOC cell lines showed that SLCO4A1 expression was diverse by individual tumors, which was further confirmed by RT-qPCR, Western blotting and immunohistochemistry. Gene Set Enrichment Analysis revealed that higher SLCO4A1 level was associated with inflammation-associated pathways including NOD-like receptor, adipocytokine, TALL1, CD40, NF-κB, and TNF-receptor 2 signaling cascades, while low SLCO4A1 expression was associated with the mitochondrial electron transport chain pathway. The overall gene expression pattern in all cell lines was specific to each patient and remained largely unchanged during tumor progression. In addition, genes encoding ABCC3 along with SLCO4A1-antisense RNA 1, were associated with higher expression of the SLCO4A1, indicating their possible involvement in inflammation-associated pathways that are downstream to the prostaglandin E2/cAMP axis. Taken together, increased SLCO4A1/OATP4A1 expression is associated with the upregulation of specific inflammatory pathways, while the decreased level is associated with mitochondrial dysfunction. These molecular pathophysiological conditions are tumor specific and should be taken into consideration by the development of therapies against HGSOC.

Decision Theory versus Conventional Statistics for Personalized Therapy of Breast Cancer.

Estrogen and progesterone receptors being present or not represents one of the most important biomarkers for therapy selection in breast cancer patients. Conventional measurement by immunohistochemistry (IHC) involves errors, and numerous attempts have been made to increase precision by additional information from gene expression. This raises the question of how to fuse information, in particular, if there is disagreement. It is the primary domain of Dempster-Shafer decision theory (DST) to deal with contradicting evidence on the same item (here: receptor status), obtained through different techniques. DST is widely used in technical settings, such as self-driving cars and aviation, and is also promising to deliver significant advantages in medicine. Using data from breast cancer patients already presented in previous work, we focus on comparing DST with classical statistics in this work, to pave the way for its application in medicine. First, we explain how DST not only considers probabilities (a single number per sample), but also incorporates uncertainty in a concept of 'evidence' (two numbers per sample). This allows for very powerful displays of patient data in so-called ternary plots, a novel and crucial advantage for medical interpretation. Results are obtained according to conventional statistics (ODDS) and, in parallel, according to DST. Agreement and differences are evaluated, and the particular merits of DST discussed. The presented application demonstrates how decision theory introduces new levels of confidence in diagnoses derived from medical data.

Tumor Growth Rate Estimates Are Independently Predictive of Therapy Response and Survival in Recurrent High-Grade Serous Ovarian Cancer Patients.

This study aimed to assess the predictive value of tumor growth rate estimates based on serial cancer antigen-125 (CA-125) levels on therapy response and survival of patients with recurrent high-grade serous ovarian cancer (HGSOC). In total, 301 consecutive patients with advanced HGSOC (exploratory cohort: n = 155, treated at the Medical University of Vienna; external validation cohort: n = 146, from the Ovarian Cancer Therapy-Innovative Models Prolong Survival (OCTIPS) consortium) were enrolled. Tumor growth estimates were obtained using a validated two-phase equation model involving serial CA-125 levels, and their predictive value with respect to treatment response to the next chemotherapy and the prognostic value with respect to disease-specific survival and overall survival were assessed. Tumor growth estimates were an independent predictor for response to second-line chemotherapy and an independent prognostic factor for second-line chemotherapy use in both univariate and multivariable analyses, outperforming both the predictive (second line: p = 0.003, HR 5.19 [1.73-15.58] vs. p = 0.453, HR 1.95 [0.34-11.17]) and prognostic values (second line: p = 0.042, HR 1.53 [1.02-2.31] vs. p = 0.331, HR 1.39 [0.71-2.27]) of a therapy-free interval (TFI) < 6 months. Tumor growth estimates were a predictive factor for response to third- and fourth-line chemotherapy and a prognostic factor for third- and fourth-line chemotherapy use in the univariate analysis. The CA-125-derived tumor growth rate estimate may be a quantifiable and easily assessable surrogate to TFI in treatment decision making for patients with recurrent HGSOC.

Xbp1s-FoxO1 axis governs lipid accumulation and contractile performance in heart failure with preserved ejection fraction.

Heart failure with preserved ejection fraction (HFpEF) is now the dominant form of heart failure and one for which no efficacious therapies exist. Obesity and lipid mishandling greatly contribute to HFpEF. However, molecular mechanism(s) governing metabolic alterations and perturbations in lipid homeostasis in HFpEF are largely unknown. Here, we report that cardiomyocyte steatosis in HFpEF is coupled with increases in the activity of the transcription factor FoxO1 (Forkhead box protein O1). FoxO1 depletion, as well as over-expression of the Xbp1s (spliced form of the X-box-binding protein 1) arm of the UPR (unfolded protein response) in cardiomyocytes each ameliorates the HFpEF phenotype in mice and reduces myocardial lipid accumulation. Mechanistically, forced expression of Xbp1s in cardiomyocytes triggers ubiquitination and proteasomal degradation of FoxO1 which occurs, in large part, through activation of the E3 ubiquitin ligase STUB1 (STIP1 homology and U-box-containing protein 1) a novel and direct transcriptional target of Xbp1s. Our findings uncover the Xbp1s-FoxO1 axis as a pivotal mechanism in the pathogenesis of cardiometabolic HFpEF and unveil previously unrecognized mechanisms whereby the UPR governs metabolic alterations in cardiomyocytes.

Decision theory for precision therapy of breast cancer.

Correctly estimating the hormone receptor status for estrogen (ER) and progesterone (PGR) is crucial for precision therapy of breast cancer. It is known that conventional diagnostics (immunohistochemistry, IHC) yields a significant rate of wrongly diagnosed receptor status. Here we demonstrate how Dempster Shafer decision Theory (DST) enhances diagnostic precision by adding information from gene expression. We downloaded data of 3753 breast cancer patients from Gene Expression Omnibus. Information from IHC and gene expression was fused according to DST, and the clinical criterion for receptor positivity was re-modelled along DST. Receptor status predicted according to DST was compared with conventional assessment via IHC and gene-expression, and deviations were flagged as questionable. The survival of questionable cases turned out significantly worse (Kaplan Meier p < 1%) than for patients with receptor status confirmed by DST, indicating a substantial enhancement of diagnostic precision via DST. This study is not only relevant for precision medicine but also paves the way for introducing decision theory into OMICS data science.

Vitamin D Analogs Regulate the Vitamin D System and Cell Viability in Ovarian Cancer Cells.

BACKGROUND: Ovarian cancer (OC) is one of the most lethal cancers in women. The active form of vitamin D3, 1,25-dihydroxyvitamin D3 (1,25D3, calcitriol) has anticancer activity in several cancers, including ovarian cancer, but the required pharmacological doses may cause hypercalcemia. We hypothesized that newly developed, low calcemic, vitamin D analogs (an1,25Ds) may be used as anticancer agents instead of calcitriol in ovarian cancer cells. METHODS: We used two patient-derived high-grade serous ovarian cancer (HGSOC) cell lines with low (13781) and high (14433) mRNA expression levels of the gene encoding 1,25-dihydroxyvitamin D3 24-hydroxylase CYP24A1, one of the main target genes of calcitriol. We tested the effect of calcitriol and four structurally related series of an1,25Ds (PRI-1906, PRI-1907, PRI-5201, PRI-5202) on cell number, viability, the expression of CYP24A1, and the vitamin D receptor (VDR). RESULTS: CYP24A1 mRNA expression increased in a concentration-dependent manner after treatment with all compounds. In both cell lines, after 4 h, PRI-5202 was the most potent analog (in 13781 cells: EC50 = 2.98 ± 1.10 nmol/L, in 14433 cells: EC50 = 0.92 ± 0.20 nmol/L), while PRI-1907 was the least active one (in 13781 cells: EC50 = n/d, in 14433 cells: EC50 = n/d). This difference among the analogs disappeared after 5 days of treatment. The 13781 cells were more sensitive to the an1,25Ds compared with 14433 cells. The an1,25Ds increased nuclear VDR levels and reduced cell viability, but only in the 13781 cell line. CONCLUSIONS: The an1,25Ds had different potencies in the HGSOC cell lines and their efficacy in increasing CYP24A1 expression was cell line- and chemical structure-dependent. Therefore, choosing sensitive cancer cell lines and further optimization of the analogs' structure might lead to new treatment options against ovarian cancer.

Changes in the Tumor Immune Microenvironment during Disease Progression in Patients with Ovarian Cancer.

Anti-PD1/PDL1 therapy has proven efficacious against many cancers but only reached modest objective response rates against recurrent ovarian cancer. A deeper understanding of the tumor microenvironment (TME) may reveal other immunosuppressive mechanisms that warrant investigation as immunotherapeutic targets for this challenging disease. Matched primary and recurrent tumors from patients with high-grade serous ovarian carcinoma (HGSC) were analyzed by multicolor immunohistochemistry/immunofluorescence for the presence of T cells, B cells, macrophages, and for the expression of immunosuppressive and HLA molecules. Cancer- and immune-related gene expression was assessed by NanoString analysis. Recurrent tumors showed increased infiltration by immune cells, displayed higher expression of PDL1, IDO, and HLA molecules, and contained more stromal tissue. NanoString analysis demonstrated increased expression of gene signatures related to chemokines and T cell functions in recurrent tumors. The ovarian tumors showed high gene expression of LAG3 and HAVCR2 (TIM3) and enhanced levels of TIGIT and CTLA4 in recurrent tumors compared to primary tumors. The majority of HGSC developed into a more inflamed phenotype during progression from primary to recurrent disease, including indications of adaptive immune resistance. This suggests that recurrent tumors may be particularly sensitive to inhibition of adaptive immune resistance mechanisms.

Microarray Normalization Revisited for Reproducible Breast Cancer Biomarkers.

Precision medicine for breast cancer relies on biomarkers to select therapies. However, the reliability of biomarkers drawn from gene expression arrays has been questioned and calls for reassessment, in particular for large datasets. We revisit widely used data-normalization procedures and evaluate differences in outcome in order to pinpoint the most reliable reprocessing methods biomarkers can be based upon. We generated a database of 3753 breast cancer patients out of 38 studies by downloading and curating patient samples from NCBI-GEO. As gene-expression biomarkers, we select the assessment of receptor status and breast cancer subtype classification. Each normalization procedure is applied separately, and biomarkers are then evaluated for each patient. Differences between normalization pipelines are quantified as percentages of patients having outcomes different for each pipeline. Some normalization procedures lead to quite consistent biomarkers, differing only in 1-2% of patients. Other normalization procedures-some of them have been used in many clinical studies-end up with distrusting discrepancies (10% and more). A good deal of doubt regarding the reliability of microarrays may root in the haphazard application of inadequate preprocessing pipelines. Several modes of batch corrections are evaluated regarding a possible improvement of receptor prediction from gene expression versus the golden standard of immunohistochemistry. Finally, we nominate those normalization methods yielding consistent and trustable results. Adequate bioinformatics data preprocessing is key and crucial for any subsequent statistics to arrive at trustable results. We conclude with a suggestion for future bioinformatics development to further increase the reliability of cancer biomarkers.

Meta-analysis of the diagnostic performance of diffusion magnetic resonance imaging with apparent diffusion coefficient measurements for differentiating glioma recurrence from pseudoprogression.

OBJECTIVE: The accurate differentiation of glioma recurrence from pseudoprogression (PSP) after therapy remains a considerable clinical challenge. Several studies have shown that diffusion magnetic resonance imaging (MRI) has potential value in distinguishing these 2 outcomes. The current meta-analysis examined the diagnostic accuracy of diffusion MRI with the apparent diffusion coefficient (ADC) in the differentiation of glioma recurrence from PSP. METHOD: PubMed, Embase, Cochrane Library, and Chinese Biomedical databases were reviewed to identify studies that fulfilled our inclusion/exclusion criteria and were published on or before May 5, 2019. Threshold effects; heterogeneity; pooled sensitivity (SENS), specificity, positive likelihood ratio, and negative likelihood ratio; and diagnostic odds ratio were calculated. The overall diagnostic usefulness of diffusion MRI-derived ADC values was assessed by calculating the area under the curve (AUC) following summary receiver operating characteristic (SROC) analysis. RESULTS: Six eligible studies examined a total of 214 patients. Calculation of pooled values indicated the SENS was 0.95 (95% confidence interval [CI] = 0.89-0.98), specificity was 0.83 (95% CI = 0.72-0.91), positive likelihood ratio was 4.82 (95% CI = 2.93-7.93), negative likelihood ratio was 0.08 (95% CI = 0.04-0.17), and diagnostic odds ratio was 59.63 (95% CI = 22.63-157.37). The SROC AUC was 0.9322. Publication bias was not significant, and SENS analysis indicated the results were relatively stable. CONCLUSIONS: Our meta-analysis indicated that diffusion MRI with quantitative ADC is an effective approach for differentiation of glioma recurrence from PSP, and can be used as an auxiliary tool to diagnose glioma progression.

Gene Expression of Kallikreins in Breast Cancer Cell Lines.

BACKGROUND/AIM: This study analyzed the gene expression of the "classic" KLK1 and "new" kallikreins KLK4-KLK15, in relation to the molecular characteristics and in vitro invasiveness of 21 breast cancer (BC) and three normal breast-derived cell lines (CLs). MATERIALS AND METHODS: Gene expression of KLKs was determined by using real-time polymerase chain reaction (PCR). The invasiveness of the CLs was examined using a fibroblast-collagen-based in vitro cell culture assay. RESULTS: KLK5 and KLK7-KLK11 were down-regulated in several BCCLs. In contrast, KLK4, KLK8, KLK12 and KLK15 demonstrated strikingly high expression in two BCCLs, UACC 812 and MDA-MB 330. The KLK expression differed frequently according to the presence of androgen receptor (KLK1 and KLK5-KLK9), and occasionally according to estrogen receptor (KLK9) and EGFR (KLK7). Two KLK clusters were detected (first: KLK1, 4, 12, 15; second: all other KLKs), with two subclasses within the second cluster (KLK5-9 and KLK10, 11, 13, and 14). The CLs that expressed at least six KLKs belonged predominantly to basal or HER2 intrinsic subtypes. No KLK predicted the in vitro invasiveness of CLs. CONCLUSION: Gene expression of KLKs was altered in BCCLs. This change was mostly down-regulation and often related to the presence of androgen receptor. The observed clusters point to a possible functional interplay of selected KLKs in BCCLs.