Screening mammography performance according to breast density: a comparison between radiologists versus standalone intelligence detection.

BACKGROUND: Artificial intelligence (AI) algorithms for the independent assessment of screening mammograms have not been well established in a large screening cohort of Asian women. We compared the performance of screening digital mammography considering breast density, between radiologists and AI standalone detection among Korean women. METHODS: We retrospectively included 89,855 Korean women who underwent their initial screening digital mammography from 2009 to 2020. Breast cancer within 12 months of the screening mammography was the reference standard, according to the National Cancer Registry. Lunit software was used to determine the probability of malignancy scores, with a cutoff of 10% for breast cancer detection. The AI's performance was compared with that of the final Breast Imaging Reporting and Data System category, as recorded by breast radiologists. Breast density was classified into four categories (A-D) based on the radiologist and AI-based assessments. The performance metrics (cancer detection rate [CDR], sensitivity, specificity, positive predictive value [PPV], recall rate, and area under the receiver operating characteristic curve [AUC]) were compared across breast density categories. RESULTS: Mean participant age was 43.5 ± 8.7 years; 143 breast cancer cases were identified within 12 months. The CDRs (1.1/1000 examination) and sensitivity values showed no significant differences between radiologist and AI-based results (69.9% [95% confidence interval [CI], 61.7-77.3] vs. 67.1% [95% CI, 58.8-74.8]). However, the AI algorithm showed better specificity (93.0% [95% CI, 92.9-93.2] vs. 77.6% [95% CI, 61.7-77.9]), PPV (1.5% [95% CI, 1.2-1.9] vs. 0.5% [95% CI, 0.4-0.6]), recall rate (7.1% [95% CI, 6.9-7.2] vs. 22.5% [95% CI, 22.2-22.7]), and AUC values (0.8 [95% CI, 0.76-0.84] vs. 0.74 [95% CI, 0.7-0.78]) (all P < 0.05). Radiologist and AI-based results showed the best performance in the non-dense category; the CDR and sensitivity were higher for radiologists in the heterogeneously dense category (P = 0.059). However, the specificity, PPV, and recall rate consistently favored AI-based results across all categories, including the extremely dense category. CONCLUSIONS: AI-based software showed slightly lower sensitivity, although the difference was not statistically significant. However, it outperformed radiologists in recall rate, specificity, PPV, and AUC, with disparities most prominent in extremely dense breast tissue.

Ultrathin Serpentine Insulation Layer Architecture for Ultralow Power Gas Sensor.

Toxic gases have surreptitiously influenced the health and environment of contemporary society with their odorless/colorless characteristics. As a result, a pressing need for reliable and portable gas-sensing devices has continuously increased. However, with their negligence to efficiently microstructure their bulky supportive layer on which the sensing and heating materials are located, previous semiconductor metal-oxide gas sensors have been unable to fully enhance their power efficiency, a critical factor in power-stringent portable devices. Herein, an ultrathin insulation layer with a unique serpentine architecture is proposed for the development of a power-efficient gas sensor, consuming only 2.3 mW with an operating temperature of 300 °C (≈6% of the leading commercial product). Utilizing a mechanically robust serpentine design, this work presents a fully suspended standalone device with a supportive layer thickness of only ≈50 nm. The developed gas sensor shows excellent mechanical durability, operating over 10 000 on/off cycles and ≈2 years of life expectancy under continuous operation. The gas sensor detected carbon monoxide concentrations from 30 to 1 ppm with an average response time of ≈15 s and distinguishable sensitivity to 1 ppm (ΔR/R0 = 5%). The mass-producible fabrication and heating efficiency presented here provide an exemplary platform for diverse power-efficient-related devices.

Novel HER2-targeted therapy to overcome trastuzumab resistance in HER2-amplified gastric cancer.

Trastuzumab is used to treat HER2-amplified metastatic gastric cancer; however, most patients become trastuzumab-resistant within a year. Knowledge of the mechanisms underlying trastuzumab resistance is required to overcome this limitation. Here, we aimed to elucidate this resistance mechanism using four trastuzumab-resistant (TR) cell lines and investigate the efficacy of HER2-targeted therapies to overcome treatment resistance. Each TR cell line had different phenotypic characteristics. Interestingly, HER2 expression remained as high as the parental cell lines in TR cell lines, suggesting that HER2-targeted agents were still useful. As expected, three tyrosine kinase inhibitors (lapatinib, neratinib, and tucatinib) and one antibody-drug conjugate (trastuzumab deruxtecan: T-DXd) exhibited good antitumor effects against TR cell lines. We further investigated the potential biological mechanism of T-DXd. When treated with trastuzumab or T-DXd, HER2 or its downstream signals were disrupted in parental cell lines, but not in TR cell lines. Moreover, T-DXd induced the expression of pH2A.X and cPARP and caused cell cycle arrest in the S or G2-M phase in TR cell lines. T-DXd showed promising antitumor activity in both parental and TR cell lines, suggesting that it is a potential candidate for overcoming trastuzumab resistance.

Trastuzumab Combined With Ramucirumab and Paclitaxel in Patients With Previously Treated Human Epidermal Growth Factor Receptor 2-Positive Advanced Gastric or Gastroesophageal Junction Cancer.

PURPOSE: Trastuzumab-containing chemotherapy is the recommended first-line regimen for human epidermal growth factor receptor 2 (HER2)-positive advanced gastric or gastroesophageal junction (G/GEJ) cancer. We evaluated the safety and efficacy of trastuzumab combined with ramucirumab and paclitaxel as second-line treatment for HER2-positive G/GEJ cancer. PATIENTS AND METHODS: Patients with HER2-positive advanced G/GEJ cancer who progressed after first-line treatment with trastuzumab-containing chemotherapy were enrolled from five centers in the Republic of Korea. Patients were administered a 28-day cycle of trastuzumab (once on days 1, 8, 15, and 22: 2 mg/kg followed by 4 mg/kg loading dose), ramucirumab (once on days 1 and 15: 8 mg/kg), and paclitaxel (once on days 1, 8, and 15: dose level 1, 80 mg/m2; or dose level -1, 70 mg/m2). Phase II was conducted with the recommended phase II dose (RP2D). Primary end points were determination of RP2D during phase Ib and investigator-assessed progression-free survival (PFS) in patients treated with RP2D. RESULTS: Dose-limiting toxicity at dose level 1 was not documented during phase Ib, and a full dose combination was selected as the RP2D. Among 50 patients with a median follow-up duration of 27.5 months (95% CI, 17.4 to 37.6), median PFS and overall survival were 7.1 months (95% CI, 4.8 to 9.4) and 13.6 months (95% CI, 9.4 to 17.7), respectively. Objective response rate was 54% (27 of 50, including one complete response), and disease control rate was 96% (48 of 50). Loss of HER2 expression was observed in 34.8% (8 of 23) patients after first-line treatment, and no definite association between HER2 expression and the outcome was revealed. Safety profiles were consistent with previous reports. CONCLUSION: Trastuzumab combined with ramucirumab and paclitaxel showed appreciable efficacy with manageable safety profiles in patients with previously treated HER2-positive G/GEJ cancer.

Sub-10 fJ/bit radiation-hard nanoelectromechanical non-volatile memory.

With the exponential growth of the semiconductor industry, radiation-hardness has become an indispensable property of memory devices. However, implementation of radiation-hardened semiconductor memory devices inevitably requires various radiation-hardening technologies from the layout level to the system level, and such technologies incur a significant energy overhead. Thus, there is a growing demand for emerging memory devices that are energy-efficient and intrinsically radiation-hard. Here, we report a nanoelectromechanical non-volatile memory (NEM-NVM) with an ultra-low energy consumption and radiation-hardness. To achieve an ultra-low operating energy of less than 10 [Formula: see text], we introduce an out-of-plane electrode configuration and electrothermal erase operation. These approaches enable the NEM-NVM to be programmed with an ultra-low energy of 2.83 [Formula: see text]. Furthermore, due to its mechanically operating mechanisms and radiation-robust structural material, the NEM-NVM retains its superb characteristics without radiation-induced degradation such as increased leakage current, threshold voltage shift, and unintended bit-flip even after 1 Mrad irradiation.

Video-based assessment of intraoperative surgical skill.

PURPOSE: Surgeons' skill in the operating room is a major determinant of patient outcomes. Assessment of surgeons' skill is necessary to improve patient outcomes and quality of care through surgical training and coaching. Methods for video-based assessment of surgical skill can provide objective and efficient tools for surgeons. Our work introduces a new method based on attention mechanisms and provides a comprehensive comparative analysis of state-of-the-art methods for video-based assessment of surgical skill in the operating room. METHODS: Using a dataset of 99 videos of capsulorhexis, a critical step in cataract surgery, we evaluated image feature-based methods and two deep learning methods to assess skill using RGB videos. In the first method, we predict instrument tips as keypoints and predict surgical skill using temporal convolutional neural networks. In the second method, we propose a frame-wise encoder (2D convolutional neural network) followed by a temporal model (recurrent neural network), both of which are augmented by visual attention mechanisms. We computed the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and predictive values through fivefold cross-validation. RESULTS: To classify a binary skill label (expert vs. novice), the range of AUC estimates was 0.49 (95% confidence interval; CI = 0.37 to 0.60) to 0.76 (95% CI = 0.66 to 0.85) for image feature-based methods. The sensitivity and specificity were consistently high for none of the methods. For the deep learning methods, the AUC was 0.79 (95% CI = 0.70 to 0.88) using keypoints alone, 0.78 (95% CI = 0.69 to 0.88) and 0.75 (95% CI = 0.65 to 0.85) with and without attention mechanisms, respectively. CONCLUSION: Deep learning methods are necessary for video-based assessment of surgical skill in the operating room. Attention mechanisms improved discrimination ability of the network. Our findings should be evaluated for external validity in other datasets.

Gas-Phase Alkali Metal-Assisted MOCVD Growth of 2D Transition Metal Dichalcogenides for Large-Scale Precise Nucleation Control.

Advances in large-area and high-quality 2D transition metal dichalcogenides (TMDCs) growth are essential for semiconductor applications. Here, the gas-phase alkali metal-assisted metal-organic chemical vapor deposition (GAA-MOCVD) of 2D TMDCs is reported. It is determined that sodium propionate (SP) is an ideal gas-phase alkali-metal additive for nucleation control in the MOCVD of 2D TMDCs. The grain size of MoS2 in the GAA-MOCVD process is larger than that in the conventional MOCVD process. This method can be applied to the growth of various TMDCs (MoS2 , MoSe2 , WSe2 , and WSe2 ) and the generation of large-scale continuous films. Furthermore, the growth behaviors of MoS2 under different SP and oxygen injection time conditions are systematically investigated to determine the effects of SP and oxygen on nucleation control in the GAA-MOCVD process. It is found that the combination of SP and oxygen increases the grain size and nucleation suppression of MoS2 . Thus, the GAA-MOCVD with a precise and controllable supply of a gas-phase alkali metal and oxygen allows achievement of optimum growth conditions that maximizes the grain size of MoS2 . It is expected that GAA-MOCVD can provide a way for batch fabrication of large-scale atomically thin electronic devices based on 2D semiconductors.

Inhibition of the bromodomain and extra-terminal family of epigenetic regulators as a promising therapeutic approach for gastric cancer.

PURPOSE: Epigenetic dysregulation is a common characteristic of cancers, including gastric cancer (GC), and contributes to cancer development and progression. Although the efficacy of BET (an epigenetic regulator) inhibition has been demonstrated in various cancer types, predictive genetic markers of its efficacy in GC are currently lacking. Therefore, we aimed to identify markers that predict the response of BET inhibition in GC and, suggest an effective treatment regimen through combined therapy. METHODS: The effect of BET inhibition was evaluated using iBET-151, a small-molecule inhibitor of BET proteins, in a large panel (n = 49) of GC cell lines and xenograft mouse models. Comprehensive genetic information was used to identify cell lines sensitive to iBET-151. Flow cytometry, Western blotting, and colony-formation and migration assays were used to evaluate the effects of iBET-151 and/or paclitaxel. The synergistic effect of iBET-151 and paclitaxel was evaluated using an organoid model. RESULTS: We found that iBET-151 showed a modest growth-inhibitory effect in GC cells (73%, 36/49). iBET-151 inhibited tumorigenicity in vitro and significantly promoted cell cycle arrest and apoptosis. Based on comprehensive genetic information analysis in relation to BET family expression, we found that BRD4 was highly expressed in the iBET-151-sensitive cell lines. We also identified WNT5B and IRS2 as potential biomarkers that are predictive for sensitivity to iBET-151. In GC xenograft model mice, iBET-151 significantly decreased tumor volumes and Ki-67 and BRD4 expression. Combination treatment showed that iBET-151 increased the sensitivity of GC cells to paclitaxel in approximately 70% of the cell lines (34/49) tested. iBET-151 plus paclitaxel significantly promoted cell cycle arrest and apoptosis and suppressed c-Myc, Bcl-2 and Bcl-xL expression. In GC organoids, iBET-151 and paclitaxel showed a synergistic effect. CONCLUSIONS: Collectively, our data suggest that iBET-151 is a potential therapeutic agent for GC, especially in combination with paclitaxel, and that WNT5B and IRS2 may predict iBET-151 sensitivity.

p16 methylation is a potential predictive marker for abemaciclib sensitivity in gastric cancer.

Cell cycle control is often disrupted in gastric cancer (GC), making it an attractive therapeutic target. Abemaciclib is a specific CDK4/6 inhibitor that has been shown to improve treatment efficacy in hormone receptor-positive advanced breast cancer; however, its potential therapeutic value and predictive markers have not yet been revealed in GC. In this study, we investigated the efficacy of abemaciclib using preclinical GC models representing defined molecular subtypes from The Cancer Genome Atlas. In these 49 GC cell lines, Epstein-Barr virus (EBV) and high microsatellite instability (MSI-H)-type cell lines were p16 methylated and sensitive to abemaciclib; further, genomically stable (GS), and chromosomal instability (CIN)-type cell lines with p16 methylation and intact Rb were also found to be responsive. In addition, we found that GC patients with p16 methylation often displayed a poor prognosis. Collectively, these data provide a foundation for clinical trials to assess the therapeutic efficacy of abemaciclib in GC and suggest that p16 methylation could be used as a predictive marker to identify patients with GC who may benefit from abemaciclib-based therapies.

Serum concentration of sex hormone-binding globulin in healthy volunteers and patients with breast cancer stratified by sex and age.

The objective of the present study was to compare sex hormone-binding globulin (SHBG) levels according to sex (healthy male and female volunteers) and age to determine reference values. Serum SHBG expression levels in patients with breast cancer with different tumor burden states were also determined. A total of 109 samples were obtained from 34 patients in 3 different disease states (non-tumor, localized tumor and systemic metastasis) during follow-up. A sandwich ELISA was conducted to measure SHBG, cancer antigen (CA)15-3 and CA125 expression levels. Wilcoxon rank-sum tests were performed on non-normally distributed data and an unpaired t-test was used for normally distributed variables. SHBG expression levels were higher in females compared with males (P<0.0001). When SHBG expression levels were compared by sex, the difference was maintained in the age groups <30, 30-39 and ≥50 years, but not in the 40-49 years group. In males, SHBG expression levels increased until the age of 49 and then decreased (P=0.01). In females, SHBG expression levels exhibited a decreased trend until the age of 49 (P=0.66). In patients with breast cancer, the SHBG expression levels revealed a decreasing trend after the age of 50, which was different compared with the healthy females. There was a decreasing trend of SHBG expression levels from pre-menopause to post-menopause healthy volunteers (P=0.74). CA15-3 (r2=0.07; P=0.59) and CA 125 (r2=-0.18; P=0.17) levels did not exhibit any significant correlation with SHBG expression levels. There was a significant difference in the SHBG expression levels between male and female healthy volunteers. SHBG expression levels also revealed different patterns between healthy female volunteers and female patients with breast cancer ≥50 years of age. The present study demonstrated that SHBG does not have value as a biomarker, but different reference values according to age and sex may aid in predicting high-risk groups for hormone-dependent cancer and guide treatment direction for post-menopausal breast cancer.

Transcriptome analysis of iBET-151, a BET inhibitor alone and in combination with paclitaxel in gastric cancer cells.

BET inhibitor, as an epigenetic regulator inhibitor, reduces the expression of oncogenes such as Myc and Bcl-2, which affects cancer growth and development. However, it has modest activity because of the narrow therapeutic index. Therefore, combination therapy is necessary to increase the anti-tumor effect. Paclitaxel, an anti-mitotic inhibitor, is used as second-line therapy for gastric cancer (GC) as a monotherapy or combination. In this study, we performed RNA sequencing of GC cells treated with iBET-151 and/or paclitaxel to identify the differentially expressed genes associated with possible mechanisms of synergistic effect. We also performed Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses to determine the most enriched terms and pathways of upregulated and downregulated genes. We found 460 genes in which iBET-151 and paclitaxel combination treatment changed more than single-treatment or no-treatment. Thus, additional functional studies are needed, but our results provide the first evidence of the synergistic effect between iBET-151 and paclitaxel in regulating the transcriptome of GC cells.

Comprehensive immune profiling and immune-monitoring using body fluid of patients with metastatic gastric cancer.

BACKGROUND: The aim of this study is to profile the cytokines and immune cells of body fluid from metastatic gastric cancer (mGC), and evaluate the potential role as a prognostic factor and the feasibility as a predictive biomarker or monitoring source for immune checkpoint inhibitor. METHODS: Body fluid including ascites and pleural fluid were obtained from 55 mGC patients and 24 matched blood. VEGF-A, IL-10, and TGF-ß1 were measured and immune cells were profiled by fluorescence assisted cell sorting (FACS). RESULTS: VEGF-A and IL-10 were significantly higher in body fluid than in plasma of mGC. Proportion of T lymphocytes with CD69 or PD-1, memory T cell marked with CD45RO, and number of Foxp3+ T regulatory cells (Tregs) were significantly higher in body fluid than those in blood of mGC. Proportion of CD8 T lymphocyte with memory marker (CD45RO) and activation marker (HLA-DR), CD3 T lymphocyte with PD-1, and number of FoxP3+ Tregs were identified as independent prognostic factors. When patients were classified by molecular subgroups of primary tumor, VEGF-A was significantly higher in genomically stable (GS)-like group than that in chromosomal instability (CIN)-like group while PD-L1 positive tumor cells (%) showed opposite results. Monitoring immune dynamics using body fluid was also feasible. Early activated T cell marked with CD25 was significantly increased in chemotherapy treated group. CONCLUSIONS: By analyzing cytokines and proportion of immune cells in body fluid, prognosis of patients with mGC can be predicted. Immune monitoring using body fluid may provide more effective treatment for patients with mGC.

Inhibiting casein kinase 2 overcomes paclitaxel resistance in gastric cancer.

PURPOSE: Casein kinase (CK) 2 activation has been implicated in the proliferation of various tumor types and resistance to chemotherapy. We investigated the mechanistic basis for the association between CK2 activation and paclitaxel resistance in a gastric cancer (GC). EXPERIMENTAL DESIGN: CK2 expression was evaluated in 59 advanced GC patients treated with paclitaxel as the second-line therapy. The efficacy of a CK2 inhibitor, CX-4945, and paclitaxel was evaluated in GC cell lines and a xenograft model. RESULTS: Patients with high CK2 expression (29/59, 39%) showed lower disease control rates (47.7% vs. 72.3%, p = 0.017) and shorter progression-free survival (2.8 vs. 4.8 months, p = 0.009) than patients with low CK2 expression. CK2 protein expression was associated with sensitivity to paclitaxel in 49 GC cell lines. Combination therapy with CX-4945 and paclitaxel exerted synergistic antiproliferative effects and inhibited the downregulation of phosphatidylinositol 3-kinase/AKT signaling in SNU-1 cells. In the SNU-1 xenograft model, the combination treatment was significantly superior to either single agent, suppressing tumor growth without notable toxicities. CONCLUSIONS: These results demonstrated that CK2 activation was related to paclitaxel resistance and that CX-4945 in combination with paclitaxel could be used as a potential treatment for paclitaxel resistance in GC.

Assessment of Automated Identification of Phases in Videos of Cataract Surgery Using Machine Learning and Deep Learning Techniques.

Importance: Competence in cataract surgery is a public health necessity, and videos of cataract surgery are routinely available to educators and trainees but currently are of limited use in training. Machine learning and deep learning techniques can yield tools that efficiently segment videos of cataract surgery into constituent phases for subsequent automated skill assessment and feedback. Objective: To evaluate machine learning and deep learning algorithms for automated phase classification of manually presegmented phases in videos of cataract surgery. Design, Setting, and Participants: This was a cross-sectional study using a data set of videos from a convenience sample of 100 cataract procedures performed by faculty and trainee surgeons in an ophthalmology residency program from July 2011 to December 2017. Demographic characteristics for surgeons and patients were not captured. Ten standard labels in the procedure and 14 instruments used during surgery were manually annotated, which served as the ground truth. Exposures: Five algorithms with different input data: (1) a support vector machine input with cross-sectional instrument label data; (2) a recurrent neural network (RNN) input with a time series of instrument labels; (3) a convolutional neural network (CNN) input with cross-sectional image data; (4) a CNN-RNN input with a time series of images; and (5) a CNN-RNN input with time series of images and instrument labels. Each algorithm was evaluated with 5-fold cross-validation. Main Outcomes and Measures: Accuracy, area under the receiver operating characteristic curve, sensitivity, specificity, and precision. Results: Unweighted accuracy for the 5 algorithms ranged between 0.915 and 0.959. Area under the receiver operating characteristic curve for the 5 algorithms ranged between 0.712 and 0.773, with small differences among them. The area under the receiver operating characteristic curve for the image-only CNN-RNN (0.752) was significantly greater than that of the CNN with cross-sectional image data (0.712) (difference, -0.040; 95% CI, -0.049 to -0.033) and the CNN-RNN with images and instrument labels (0.737) (difference, 0.016; 95% CI, 0.014 to 0.018). While specificity was uniformly high for all phases with all 5 algorithms (range, 0.877 to 0.999), sensitivity ranged between 0.005 (95% CI, 0.000 to 0.015) for the support vector machine for wound closure (corneal hydration) and 0.974 (95% CI, 0.957 to 0.991) for the RNN for main incision. Precision ranged between 0.283 and 0.963. Conclusions and Relevance: Time series modeling of instrument labels and video images using deep learning techniques may yield potentially useful tools for the automated detection of phases in cataract surgery procedures.

Objective assessment of intraoperative technical skill in capsulorhexis using videos of cataract surgery.

PURPOSE: Objective assessment of intraoperative technical skill is necessary for technology to improve patient care through surgical training. Our objective in this study was to develop and validate deep learning techniques for technical skill assessment using videos of the surgical field. METHODS: We used a data set of 99 videos of capsulorhexis, a critical step in cataract surgery. One expert surgeon annotated each video for technical skill using a standard structured rating scale, the International Council of Ophthalmology's Ophthalmology Surgical Competency Assessment Rubric:phacoemulsification (ICO-OSCAR:phaco). Using two capsulorhexis indices in this scale (commencement of flap and follow-through, formation and completion), we specified an expert performance when at least one of the indices was 5 and the other index was at least 4, and novice otherwise. In addition, we used scores for capsulorhexis commencement and capsulorhexis formation as separate ground truths (Likert scale of 2 to 5; analyzed as 2/3, 4 and 5). We crowdsourced annotations of instrument tips. We separately modeled instrument trajectories and optical flow using temporal convolutional neural networks to predict a skill class (expert/novice) and score on each item for capsulorhexis in ICO-OSCAR:phaco. We evaluated the algorithms in a five-fold cross-validation and computed accuracy and area under the receiver operating characteristics curve (AUC). RESULTS: The accuracy and AUC were 0.848 and 0.863 for instrument tip velocities, and 0.634 and 0.803 for optical flow fields, respectively. CONCLUSIONS: Deep neural networks effectively model surgical technical skill in capsulorhexis given structured representation of intraoperative data such as optical flow fields extracted from video or crowdsourced tool localization information.

Casein Kinase 2 Inhibitor, CX-4945, as a Potential Targeted Anticancer Agent in Gastric Cancer.

BACKGROUND/AIM: Casein kinase 2 (CK2) is involved in multiple cellular processes. Furthermore, its overexpression in several human cancers has been associated with tumor progression. In this study, we evaluated the efficacy of the CK2 inhibitor, CX-4945, in gastric cancer cell lines and explored the potential predictive biomarkers for CX-4945 sensitivity. MATERIALS AND METHODS: The sensitivity to CX-4945 was screened in 49 gastric cancer cell lines by the MTT assay. The mRNA and protein expression of CK2 subunits (α and α') were determined using qRT-PCR and western blot. Furthermore, the activity of CK2α was measured by ELISA. Gene expression and mutations were analyzed via whole-exome and RNA sequencing. RESULTS: The sensitivity to CX-4945 was determined by the inhibition rate (%) at the effective dose (10 µM) which ranged from -1% to 89% in 49 gastric cancer cell lines. CK2α', but not CK2α, mRNA expression was correlated with CX-4945 sensitivity. CONCLUSION: In this study, CX-4945 showed modest antitumor efficacy in gastric cancer cell lines. CK2 might represent a potential therapeutic target for gastric cancer.

Aberrant cystatin-C expression in blood from patients with breast cancer is a suitable marker for monitoring tumor burden.

The present study was performed to evaluate the efficacy of circulating cystatin-C as a tumor monitoring biomarker at different clinical time points in patients with breast cancer over a long-term follow-up period. In addition, the secretory rate of circulating cystatin-C from cancer tissue was investigated by comparing the blood and tissue expression levels of cystatin-C. Blood samples from healthy volunteers (40 males and 40 females) were obtained at yearly health examinations if laboratory and imaging abnormalities were not detected. Blood samples from 34 patients with breast cancer were obtained at 205 different time points of clinical progression. Blood levels of cystatin-C were measured using ELISA and the tissue levels were measured using immunohistochemistry. No age-associated effect was observed in male and female blood cystatin-C levels. The positivity rate was 46% in patients (38/83) and 40% in samples collected at different time points (82/205). Blood cystatin-C levels were lowest following surgery compared with patients with systemic metastasis (P<0.001). The sensitivity, specificity and accuracy rates of ELISA were 53.6, 63.6 and 53.9%, respectively. The concordance rate between blood and tissue expression was 38%. The main reason for discordance between tissue and serum expression of cytostatin-C came from low serum positivity in samples showing tissue cytostatin-C (3/11, 27%). The specificity between cytostatin-C and CA-125 was highest in tumor absence state. In conclusion, elevated blood levels of cystatin-C were observed in 40% of breast cancer cases and were tumor-volume dependent. However, the concordance rate between tissue and blood was quite low, suggesting tumor heterogeneity of cystatin-C expression or co-acting pathway activation, such as cathepsin D. As one-third of breast cancer tissues express cystatin-C without cancer antigen 15-3 elevation, cystatin-C may represent a good tumor-monitoring marker in breast cancer.

Forty-nine gastric cancer cell lines with integrative genomic profiling for development of c-MET inhibitor.

Receptor tyrosine kinase MET (c-MET) has received considerable attention as a potential target for gastric cancer (GC) therapy and a number of c-MET inhibitors have been developed. For successful drug development, proper preclinical studies especially using patient derived cancer cell lines are very important. We profiled MET and MET-related characteristics in 49 GC cell lines to utilize them as models in preclinical studies of GC. Forty-nine cell lines were analyzed for genetic, biological, and molecular status to characterize MET and MET-related molecules. Four c-MET inhibitors were tested to elucidate the dependency on MET pathway in the 49 GC cell lines. Six of 49 cell lines were MET amplified with overexpression of c-MET and p-MET. The variants of MET were not associated with c-MET expression or amplification. Hs746T showed an exon 14 deletion in conjunction with MET amplification. The cell lines were divided into 6 MET amplified, 2 c-MET overexpressed, 2 hepatocyte growth factor (HGF) overexpressed, and 39 MET-negative subgroups. Except tivantinib, the c-MET inhibitors showed higher inhibition (%) in MET amplified than in MET nonamplified cell lines that MET amplified cell lines showed MET pathway dependency. However, the c-MET overexpressed and HGF overexpressed cell lines showed moderate dependency on MET pathway. Well-characterized cell lines are very important in studying drug development. Our 49 GC cell lines had various characteristics of MET and MET-related molecules and MET pathway dependency. These provide a promising platform for development of various RTK inhibitors including c-MET inhibitors.

Changes in telomerase activity due to alternative splicing of human telomerase reverse transcriptase in colorectal cancer.

Human telomerase reverse transcriptase (hTERT) expression level may not always correlate with telomerase activity. The present study analyzed hTERT splicing patterns with respect to hTERT and telomerase activity in colorectal cancer. Telomerase activity was determined by telomeric repeat amplification protocol assay, and spliced variants of hTERT were identified by reverse transcription-polymerase chain reaction in 40 colorectal cancer tissue samples. In the lower range of telomerase activity (0-100 units), the percentage of the ß variant decreased with the increment in telomerase activity, whereas in the higher range of telomerase activity (>100 units), total hTERT expression level revealed a trend toward increment. There was a positive correlation between the full-length variant level and ß variant level. Conversely, there was a negative correlation between the percentage of the full-length variant and ß variant. Tumor-node-metastasis stage was the strongest prognostic factor in multivariate analysis and the percentage of the full-length variant was an independent prognostic factor for survival. Telomerase activity was primarily altered with changes in alternative splicing of the full-length and ß variants of hTERT in colorectal cancer.