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The measurement of cell viability plays an essential role in the area of cell biology. At present, the common methods for cell viability assay mainly on the responses of cells to different dyes. However, the additional steps of cell staining will consequently cause time-consuming and laborious efforts. Furthermore, the process of cell staining is invasive and may cause internal structure damage of cells, restricting their reuse in subsequent experiments. In this work, we proposed a label-free method to classify live and dead colonic adenocarcinoma cells by 2D light scattering combined with the deep learning algorithm. The deep convolutional network of YOLO-v3 was used to identify and classify light scattering images of live and dead HT29 cells. This method achieved an excellent sensitivity (93.6%), specificity (94.4%), and accuracy (94%). The results showed that the combination of 2D light scattering images and deep neural network may provide a new label-free method for cellular analysis.

Objective Circ-centro-some/spindle pole-associated protein (CSPP1) has been confirmed to be characterized in diverse human malignancies and its ectopic expression may regulate tumor progression and development. However, in hepatocellular carcinoma (HCC), its biological role, clinical significance and molecular mechanism are still unclear. Methods Circ-CSPP1 expression and its prognostic values in HCC tissues were detected by qRT-PCR or in situ hybridization (ISH), and enriched by using Rnase R. The functional experiments (Circ-CSPP1 was overexpressed or knocked down) were performed in HCC cells. The HCC cell growth was analyzed by CCK-8 assay, transwell, wound healing and colony formation assays. The interation between circ-CSPP1 and miR-577/miR-577 and cyclin E2 (CCNE2) were determined by dual luciferase assay or RNA binding protein immunoprecipitation (RIP) assay. The RNA fluorescence in situ hybridization (FISH) assay was used to detect the subcellular distribution. Finally, an in vivo nude mouse tumor model was constructed. Results In HCC patients and cells, circ-CSPP1 was aberrantly expressed, and its upregulation predicted poor prognosis, and closely correlated with tumor size and TNM stage. Circ-CSPP1 resisted RnaseR digestion, indicating it is a circular RNA structure. Moreover, overexpression of circ-CSPP1 promoted HCC cell viability, colony formation, migration, and invasion in vitro. Knockdown of circ-CSPP1 showed contrary results. Circ-CSPP1 acts as a miR-577 sponge and positively regulated the target of miR-577, CCNE2. Besides, miR-577 inhibitor rescued the suppressive effects of circ-CSPP1 knockdown on HCC cell growth, whereas was completely reversed by silencing of CCNE2. Finally, the in vivo experiments confirmed that circ-CSPP1 knockdown regulated xenograft tumor volume and downregulated CCNE2, p-Rb, E2F1 and c-myc expression. Conclusion These findings revealed that circ-CSPP1 contributed to HCC progression by positively regulating CCNE2 via miR-577, thus established its potential as new a prognostic and therapeutic marker for HCC patients.

Colorectal cancer (CRC) is a fatal disease ranking the third among the commonplace cancer types around the world. It is extremely significant to exploit effective treatments against CRC. FAM225A was proved to influence cell progression and forecast unfavorable prognosis in nasopharyngeal carcinoma. The role and function mechanism of FAM225A are still unclear in CRC. In this research, FAM225A was discovered presenting much higher expression in CRC tissues and cell lines. In addition, depleting FAM225A was capable of inhibiting cell proliferation, migration, and epithelial‐to‐mesenchymal transition (EMT) progress, and enhancing cell apoptosis ability. Furthermore, miR‐613 exerted important effects as a mediator between FAM225A and NOTCH3. NOTCH3 was negatively correlated with miR‐613, whereas was positively associated with FAM225A. Via competitively binding with miR‐613, FAM225A positively regulated NOTCH3 expression. FAM225A facilitated CRC occurrence and development through positively regulating NOTCH3 expression by binding with miR‐613. In a word, FAM225A/miR‐613/NOTCH3 axis may play a tumor‐facilitator in CRC cell progression. These data manifested the pivotal effect of FAM225A/miR‐613/NOTCH3 pathway in CRC cell proliferation, apoptosis, and migration process. The findings may provide some theoretical basis and different perspective for CRC treatment., FAM225A presents high expression in CRC tissues and cell lines. FAM225A expedites CRC cell proliferation, migration abilities, and impairs cell apoptosis capacity. FAM225A acts as a sponge of miR‐613 and is negatively correlated with miR‐613.

Gastric cancer (GC) is one of the leading causes of cancer-related deaths in our country. Circular RNAs (circRNAs) are being found to have relevance to human cancers, including GC. The purpose of this study was to investigate the functional role of circRNA BTG3 associated nuclear protein (circBANP) in GC and underlying mechanisms governing it. CircBANP was identified using RNase R assay and polymerase chain reaction (PCR) with specific primers. The levels of circBANP, let-7a and Frizzled-5 (FZD5) mRNA were assessed by quantitative real-time PCR (qRT-PCR). Cell proliferation, colony formation ability, apoptosis, and migration and invasion were determined by Cell Counting Kit-8 (CCK-8) assay, colony formation assay, flow cytometry, transwell assay, respectively. The targeted interaction between let-7a and circBANP or FZD5 was confirmed by dual-luciferase reporter assay or RNA pull-down assay. Western blot analysis was performed to detect the indicated protein expression. A xenograft model assay was established to observe the role of circBANP in vivo. We found that circBANP was up-regulated in GC tissues and cell lines, and associated with clinicopathologic features of GC patients. CircBANP knockdown repressed the proliferation, migration, invasion, and promoted the apoptosis in GC cells. CircBANP sequestered let-7a by acting as a molecular sponge of let-7a. Moreover, the regulatory effect of circBANP on GC cell progression in vitro was mediated by let-7a. CircBANP protected against FZD5 repression by sponging let-7a in GC cells. Wnt/β-catenin signaling was involved in the regulatory network of the circBANP/let-7a axis in GC cell progression. Additionally, circBANP depletion retarded tumor growth in vivo. In conclusion, our study suggested that the knockdown of circBANP suppressed GC cell progression in vitro and in vivo at least partially through sponging let-7a and regulating FZD5/Wnt/β-catenin signaling, providing a novel mechanism for understanding the pathogenesis of GC.

Purpose Long non-coding RNA (lncRNA) HOX transcript antisense RNA (HOTAIR) has been reported to dysregulate in many tumors. However, the mechanism of HOTAIR was rarely reported in GC. Methods The levels of HOTAIR, microRNA-618 (miR-618) and Krueppel-like factor 12 (KLF12) in GC tissues and cells were detected by quantitative real-time polymerase chain reaction (qRT-PCR). The cell viability and apoptotic rate were assessed via cell counting kit-8 (CCK-8) assay and flow cytometry, respectively. The migrating and invading abilities were tested by Transwell assay. The protein levels of KLF12, p-PI3K, PI3K, p-ATK and ATK were measured by Western blot assay. These interactions between miR-618 and HOTAIR or KLF12 were predicted by DIANA tools, and then, dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay were conducted to validate these interactions. Besides, the xenograft tumor experiment was performed to further verify the roles of HOTAIR in GC. Results The levels of HOTAIR and KLF12 were significantly upregulated and the level of miR-618 was strikingly downregulated in GC tissues and cells. miR-618 was verified as a direct target of HOTAIR or KLF12. HOTAIR silencing blocked GC progression and PI3K/ATK signaling pathway by sponging miR-618 and also restrained xenograft tumor growth in vivo. miR-618 inhibited GC progression and PI3K/ATK signaling pathway by targeting KLF12. Mechanistically, HOTAIR modulated KLF12 expression by sponging miR-618 in GC cells. Conclusion These data unraveled that HOTAIR promoted GC progression through PI3K/ATK signaling pathway via miR-618/KLF12 axis.

Background Gastric cancer (GC) is the second most common cause of cancer-related death worldwide. Novel anticancer drugs against gastric cancer are urgently needed. Methods Compound 10 was designed and synthesized via a molecular hybridization strategy based on the natural product formononetin. It was evaluated for their antiproliferative activity against three gastric cancer cell lines (SGC7901, MKN45 and MGC803). Results Derivative 10 displayed potently antiproliferative activity with an IC50 value of 1.07 μM against SGC7901 cells. Derivative 10 could inhibit the growth and migration against gastric cancer SGC7901 cells through the Wnt/β-Catenin and AKT/mTOR pathways. From the in vivo expremints, it could effectively inhibited SGC7901 xenograft tumor growth in vivo without significant loss of the body weight. Conclusion Derivative 10 is an novel antitumor agent with potential for further clinical applications to treat gastric cancer.

Sanggenon C is a well-known, major active agent of the flavonoid derivative of benzopyrone with valuable biological properties, including anticancer, anti-inflammatory, antimicrobial, antiviral, antithrombotic, and immune-modulatory activities. In this study, we investigated the molecular mechanisms by which sanggenon C mediated the induction of cell death in colorectal cancer cells (CRC). Treatment of colorectal cancer cells (LoVo, HT-29 and SW480) with sanggenon C (0, 5, 10, 20, 40 and 80 µM) resulted in inhibited proliferation of colon cancer cells. In addition, Sanggenon C (10, 20, 40 µM) induces apoptosis of HT-29 colon cancer cells as well as the increased ROS generation. Furthermore, treatment with sanggenon C increased the level of intracellular Ca2+ and ATP, while inhibited the nitric oxide production via inhibiting inducible nitric oxide synthase expression. This resulted in the activation of mitochondrial apoptosis pathway as evidenced by the decrease in Bcl-2 protein expression. Consistently, the anti-growth and pro-apoptosis effects of sanggenon C on xenograft colon tumor were further confirmed in vivo. Collectively, our results demonstrated sanggenon C induced apoptosis of colon cancer cells by increased reactive oxygen species generation and decreased nitric oxide production, which is associated with inhibition of inducible nitric oxide synthase expression and activation of mitochondrial apoptosis pathway.

Colorectal cancer (CRC) is the third leading cause of cancer-related death in China. It usually originates from the non-cancerous neoplasm polyps of the colon or rectal epithelium. Some polyps will evolve into precancerous lesions and eventually turn into colorectal cancer, Early screening and removal of adenomas can reduce the risk of colorectal cancer if screened. Unfortunately, more than 60% of colorectal cancer cases are attributed to missed polyps. Therefore, a deep learning network referred to as the faster_rcnn_inception_ resnet_v2 model was introduced for the localization and classification of precancerous lesions. It enables high-precision classification of polyps and adenomas under white light endoscopic images. The Mean Average Precision reached 90.645% when the Intersection over Union is set to 0.5. As an aid to clinicians, the model can improve the detection rate of adenomas and the diagnostic accuracy of early CRC.

Intestinal metaplasia is a precancerous lesion, gastric cancer is a very common malignant tumor, and many people die every year from stomach cancer. Early diagnosis of gastric cancer is critical to reducing patient mortality and overall medical burden. However, traditional endoscopic intestinal metaplasia on the gastric mucosa lacks specific performance. Consequently, subtle changes in precancerous intestinal metaplasia are not obvious limiting diagnostic accuracy. As a clinical computer aid in the diagnosis of early gastric cancer, a deep learning framework model called W-Deeplab was proposed for the identification and localization of intestinal metaplasia lesions. It achieves high-precision semantic segmentation of endoscopic images. As a computer aid to clinicians, it can improve the accuracy and efficiency of intestinal metaplasia diagnosis and reduce misdiagnosis.

Colorectal cancer is one of the most common cancers in China. The occurrence of most colorectal cancer is closely related to colorectal polyps. Colonoscopy is the gold standard for the diagnosis of intestinal lesions. Usually, existing colonoscopy is performed by physicians to determine the location of polyps by observing the results of detection with the naked eye. The detection rate of polyps is also affected by the doctor’s experience, fatigue, detection rate, and other factors, so there is a certain degree of polyp missed detection. Therefore, to improve diagnostic accuracy and reduce the rate of missed diagnosis, the paper proposes an improved_ssd model based on deep learning. The model is extended from the ssd_inception_v2 model, and the inception_v2 basic framework is used to extract features from multiple dimensions and fuse them, which improve the accuracy of polyp location. The test results show that the AP of this method is 94.92%, the accuracy is 96.04%, the sensitivity is 93.67%, and the specificity is 98.36%. This method realizes the accurate localization of polyps in colonoscopy and provides a reference for doctors' diagnosis.

BACKGROUND The formation of liver fibrosis is mainly caused by the activation of hepatic stellate cells (HSCs) and the imbalance of extracellular matrix (ECM) production and degradation. The treatment of liver fibrosis mainly includes removing the cause, inhibiting the activation of HSCs, and inhibiting inflammation. NOD-like receptor (NLR) family, caspase activation and recruitment domain (CARD) domain containing 5/NOD27/CLR16.1 (NLRC5) is a highly conserved member of the NLR family and is involved in inflammation and immune responses by regulating various signaling pathways such as nuclear factor-κB (NF-κB) signaling. It has been found that NLRC5 plays an important role in liver fibrosis, but its specific effect and possible mechanism remain to be fully elucidated. AIM To investigate the role of NLRC5 in the activation and reversion of HSCs induced with transforming growth factor-β (TGF-β) and MDI, and to explore its relationship with liver fibrosis. METHODS A total of 24 male C57BL/6 mice were randomly divided into three groups, including normal, fibrosis, and recovery groups. Twenty-four hours after a liver fibrosis and spontaneous reversion model was established, the mice were sacrificed and pathological examination of liver tissue was performed to observe the degree of liver fibrosis in each group. LX-2 cells were cultured in vitro and treated with TGF-β1 and MDI. Real-time quantitative PCR (qPCR) and Western blot were used to analyze the expression levels of NLRC5, α-smooth muscle actin (α-SMA), and collagen type I alpha1 (Col1a1) in each group. The activity of NF-κB in each group of cells transfected with NLRC5-siRNA was detected. RESULTS Compared with the normal mice, the expression level of NLRC5 increased significantly (P < 0.01) in the fibrosis group, but decreased significantly in the recovery group (P < 0.01). In in vitro experiments, the content of NLRC5 was enhanced after TGF-β1 stimulation and decreased to a lower level when treated with MDI (P < 0.01). The expression of α-SMA and Col1a1 proteins and mRNAs in TGF-β1-mediated cells was suppressed by transfection with NLRC5-siRNA (P < 0.01). Western blot analysis showed that the expression of NF-κB p65 protein and phosphorylated IκBα (p-IκBα) was increased in the liver of mice in the fibrosis group but decreased in the recovery group (P < 0.01), and the protein level of nuclear p65 and p-IκBα was significantly increased after treatment with NLRC5-siRNA (P < 0.01). CONCLUSION NLRC5 may play a key role in the development and reversal of hepatic fibrosis through the NF-κB signaling pathway, and it is expected to be one of the clinical therapeutic targets.

Esophageal cancer is one of the most common malignant tumors which responses for about 400,000 deaths each year. Early identifying lesions is critical for reducing esophageal cancer mortality and the overall esophageal cancer burden. However, identification of early esophageal cancerous lesions can be very challenging for clinicians owing to the mild clinical symptoms and lack of specificity of esophageal cancer. Consequently, precancer or subtle early neoplastic changes may not be evident, limiting the diagnostic accuracy. As a clinical assistance for early esophageal cancer identification, a deep learning framework referred to as the M-Deeplab model was proposed for the localization and recognition of esophageal mucosa lesion. The proposed M-Deeplab model was extended from the Deeplabv3+ model by employing an encoder-decoder structure for accuracy improvement. It achieves high-precision semantic segmentation for different staining degrees and different sizes of endoscopic images. The overall accuracy reaches 97.31% and the MIoU reaches 92.09%. Moreover, it takes only 0.05s to judge one image by the M-Deeplab model. The M-Deeplab model exhibits good performance both in accuracy and speed for early esophageal cancerous lesions identification, comparable to the experienced clinicians. As an assistance for the clinicians, the proposed model could possibly increase the early esophageal cancer diagnosis accuracy and decrease the misdiagnosis.

Background TRIP13 is highly expressed in several cancers and is closely connected with cancer progression. However, its roles on the growth and metastasis of hepatocellular carcinoma (HCC), and the underlying mechanism are still unclear. Methods Combining bioinformatics with previous studies, the correlation between TRIP13 and HCC was predicted. TRIP13 expressions from 52 HCC patients and several cell lines were determined. The effects of silencing TRIP13 on cell viability, apoptosis, migration and invasion were respectively detected using CCK-8, flow cytometry and Transwell. qRT-PCR and western blot were performed to reveal associated mechanism. A HCC model was established in BALB/c-nu mice by transplanting HepG2 cells. TRIP13 protein expression and apoptosis in mice tissues were accordingly detected by Immunohistochemistry and TUNEL. Results High expression of TRIP13 in HCC affected the survival rate and it was enriched in RNA degradation and fatty acid metabolism according to bioinformatics and prediction from previous literature. Increased expression of TRIP13 in HCC patient tissues was associated with the progression of HCC. Silencing TRIP13 inhibited cell viability, migration and invasion, and induced cell apoptosis. TRIP13 knockdown also suppressed the formation of tumor in vivo. Meanwhile, silencing TRIP13 decreased the expressions of Ki67 and MMP-2 and increased the expressions of TIMP-2, active-caspase-3 and TGF-β1/smad3 signaling- related genes. Conclusions Silencing TRIP13 acts as a tumor suppresser of HCC to repress cell growth and metastasis in vitro and in vivo, and such a phenomenon possibly involved activation of TGF-β1/smad3 signaling.