Abstract. Patients with the most common advanced human cancers such as lung, breast, uterus, and cancers of the digestive system almost always develop bone metastases, with painful and untreatable consequences. This study aimed to determine the prognostic implications of the neutrophil/lymphocyte (N/L) ratio in the peripheral blood of patients with malignant bone metastasis. Study participants were identified from a prospective cohort of cancer patients with bone metastasis. Data for the N/L ratios were obtained from clinical and pathological records and were analyzed together with other known prognostic factors in the multivariate and univariate analyses. The results showed the average N/L ratio of all 497 patients to be 4.25±2.44 (range 0.54-45.50 years). Multivariate analysis revealed that tumor type and a high N/L ratio were significantly associated with poor prognosis. For the high N/L ratio group, the estimated hazard ratio of death was 1.348 [95% confidence interval (CI), 1.062-1.712] compared with the low N/L ratio group. The average N/L ratio of the 225 patients in the surgery group was 2.79±2.46 (range 0.77-22.75 years). Multivariate analysis revealed that a preoperatively high N/L ratio (P=0.013; HR=2.945; 95% CI, 1.256-6.906) was significantly associated with poor prognosis after bone metastasis in the surgery group. In conclusion, the N/L ratio was confirmed to be an independent prognostic factor in patients with bone metastasis. Thus, the N/L ratio may serve as a clinically accessible and useful biomarker for patient survival.

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Abstract. As a natural compound, Ornithogalum caudatumAit is primarily used as an anti-inflammatory and antitumor agent in Chinese folk medicine. In 1992, OSW-1 was isolated from this compound, which is a new member of cholestane saponin family. In numerous recent studies, OSW-1 has been shown to have powerful cytotoxic anticancer effects against various malignant cells. However, the therapeutic efficacy of OSW-1 on colon cancer and the underlying mechanism are not understood. To explore the mechanism underlying OSW-1 in antitumor therapy, a therapeutic function analysis of OSW-1 on colon cancer was performed in vitro and in vivo. It was shown that with low toxicity on normal colonic cells, OSW-1 suppresses colon cancer cells in vitro and this inhibition was via the intrinsic apoptotic pathway, which increased cellular calcium, changed mitochondrial membrane potential, disrupted mitochondrial morphology, and led to the release of cytochrome c and the activation of caspase-3. Furthermore, in a nude mouse model, OSW-1 had a powerful effect on suppressing colon tumor proliferation without significant side effects through the apoptosis pathway. Taken together, these results demonstrate that OSW-1 is a potential drug for colon cancer treatment.

Introduction: The nucleated-cell differential count on the bone marrow aspirate smears is required for the clinical diagnosis of hematological malignancy. Manual bone marrow differential count is time consuming and lacks consistency. In this study, a novel artificial intelligence (AI)-based system was developed to perform cell automatic classification of bone marrow cells and determine its potential clinical applications. Materials and Methods: Bone marrow aspirate smears were collected from the Xinqiao Hospital of Army Medical University. First, an automated analysis system (Morphogo) scanned and generated whole digital images of bone marrow smears. Then, the nucleated marrow cells in the selected areas of the smears at a magnification of ×1,000 were analyzed by the software utilizing an AI-based platform. The cell classification results were further reviewed and confirmed independently by 2 experienced pathologists. The automatic cell classification performance of the system was evaluated using 3 categories: accuracy, sensitivity, and specificity. Correlation coefficients and linear regression equations between automatic cell classification by the AI-based system and concurrent manual differential count were calculated. Results: In 230 cases, the classification accuracy was above 85.7% for hematopoietic lineage cells. Averages of sensitivity and specificity of the system were found to be 69.4 and 97.2%, respectively. The differential cell percentage of the automated count based on 200–500 cell counts was correlated with differential cell percentage provided by the pathologists for granulocytes, erythrocytes, and lymphocytes (r ≥ 0.762, p < 0.001). Discussion/Conclusion: This pilot study confirmed that the Morphogo system is a reliable tool for automatic bone marrow cell differential count analysis and has potential for clinical applications. Current ongoing large-scale multicenter validation studies will provide more information to further confirm the clinical utility of the system.

Background: Venous thromboembolism (VTE) is a common complication in patients with cancer. Direct oral anticoagulants (DOACs) have been proved to be effective on anticoagulation therapy in many diseases. However, the efficacy and the safety of DOACs in the secondary prevention of cancer-associated thrombosis (CAT) remain unclear. To assess the value of DOACs in patients with CAT, we performed a systematic review and meta-analysis of randomized controlled trials and prospective cohort studies. Methods: Medline, Embase, and the Cochrane Library were searched from their earliest date through to June 2018. Two investigators independently assessed eligibility. Data were extracted by one investigator and verified by the second investigator. The efficacy outcome of this study was recurrent VTE, whereas the safety outcome was major and clinically relevant nonmajor bleeding. Relative risks (RRs) and their corresponding 95% confidence interval (CI) were determined. To pool the results, the Mantel–Haenszel fixed-effects or random-effects models were used. Results: A total of nine articles (six randomized controlled trials and three prospective studies) involving 2,697 patients with CAT who were prescribed DOACs (apixaban, edoxaban, rivaroxaban, or dabigatran) and 2,852 patients who were prescribed traditional anticoagulants [vitamin K antagonists (VKAs), low molecular weight heparin (LMWH), dalteparin, or enoxaparin] were compared. VTE recurrence in the DOAC group was significantly lower than that observed in the traditional anticoagulant group (RR: 0.60; 95%CI: 0.49–0.75; I 2 : 0%; p < 0.00001). No significant difference in bleeding risk between both groups was found (RR: 0.95; 95%CI: 0.67–1.36; I 2 : 75%; p = 0.79). Conclusions: Our findings showed that anticoagulant therapy with DOACs may be more effective than traditional anticoagulants to prevent recurrent VTE in patients with CAT, while the safety of DOACs may be equal to that of traditional anticoagulants. These findings support the use of DOACs as the first-line therapy for secondary prevention of CAT in most cancer patients.

Bone marrow smear examination is an indispensable diagnostic tool in the evaluation of hematological diseases, but the process of manual differential count is labor extensive. In this study, we developed an automatic system with integrated scanning hardware and machine learning-based software to perform differential cell count on bone marrow smears to assist diagnosis. The initial development of the artificial neural network was based on 3000 marrow smear samples retrospectively archived from Sir Run Run Shaw Hospital affiliated to Zhejiang University School of Medicine between June 2016 and December 2018. The preliminary field validating test of the system was based on 124 marrow smears newly collected from the Second Affiliated Hospital of Harbin Medical University between April 2019 and November 2019. The study was performed in parallel of machine automatic recognition with conventional manual differential count by pathologists using the microscope. We selected representative 600,000 marrow cell images as training set of the algorithm, followed by random captured 30,867 cell images for validation. In validation, the overall accuracy of automatic cell classification was 90.1% (95% CI, 89.8–90.5%). In a preliminary field validating test, the reliability coefficient (ICC) of cell series proportion between the two analysis methods were high (ICC ≥ 0.883, P < 0.0001) and the results by the two analysis methods were consistent for granulocytes and erythrocytes. The system was effective in cell classification and differential cell count on marrow smears. It provides a useful digital tool in the screening and evaluation of various hematological disorders.

Introduction: Urine cytology plays an important role in diagnosing urothelial carcinoma (UC). However, urine cytology interpretation is subjective and difficult. Morphogo (ALAB, Boston, MA, USA), equipped with automatic acquisition and scanning, optical focusing, and automatic classification with convolutional neural network has been developed for bone marrow aspirate smear analysis of hematopoietic diseases. The goal of this preliminary study was to determine the feasibility of developing a machine learning algorithm on Morphogo for identifying abnormal urothelial cells in urine cytology slides. Methods: Thirty-seven achieved abnormal urine cytology slides from cases with the diagnosis of atypical urothelial cells and above (suspicions or positive for UC) were obtained from 1 hospital. A pathologist (J.R.) reviewed the slides and manually selected and annotated representative cells to feed into Morphogo with following categories: benign (urothelial cells, squamous cells, degenerated cells, and inflammatory cells), atypical cells, and suspicious cells. Initial validation of the algorithm was performed on a subset of the original 37 cases. Urine samples from additional 12 unknown cases with various histological diagnoses (6 cases of high-grade urothelial carcinoma (HGUC), 1 case of lowgrade urothelial carcinoma (LGUC), 1 case of prostate adenocarcinoma, 1 case of renal cell carcinoma, and 4 cases of nonneoplastic conditions) were collected from another hospital for initial blind testing. Results: A total of 1,910 benign and 1,978 abnormal (atypical and suspicious) cells from 37 slides were annotated for developing and training of the algorithm. This algorithm was validated on 27 slides that resulted in identification of at least 1 abnormal cell per slide, with a total of 200 abnormal cells, and an average of 7.4 cells per slide. Of the 12 unknown cases tested, the original cytology was positive for tumor cells in 2 HGUC samples. Morphogo was abnormal (atypical or suspicious) for 6 samples from patients with UC, including one with LGUC and one with prostate adenocarcinoma. Conclusion: Morphogo machine learning algorithm is capable of identifying abnormal urothelial cells. Further validation studies with a larger number of urine samples will be needed to determine if it can be used to assist the cytological diagnosis of UC.

The present study demonstrated the anti-tumor effects of the quinoline derivative [5-(3-chloro-oxo-4-phenyl-cyclobutyl)-quinoli-8-yl-oxy] acetic acid hydrazide (CQAH) against colorectal carcinoma. Substantial apoptotic effects of CQAH on HCT116 and LoVo human colon cancer cell lines were observed. Apoptosis was identified based on cell morphological characteristics, including cell shrinkage and chromatin condensation as well as Annexin V/propidium iodide double staining followed by flow cytometric analysis and detection of apoptosis-associated proteins by western blot analysis. CQAH induced caspase-3 and PARP cleavage, reduced the expression of the anti-apoptotic proteins myeloid cell leukemia-1 and B-cell lymphoma (Bcl) extra large protein and elevated the expression of the pro-apoptotic protein Bcl-2 homologous antagonist killer. In addition, pharmacological inhibition of c-Jun N-terminal kinase (JNK), but not extracellular signal-regulated kinase or p38, significantly reduced CQAH-mediated cell death as well as cleavage of caspase-3 and PARP. Co-treatment of CQAH with the commercial chemotherapeutics 5-fluorouracil and camptothecin-11 significantly improved their efficacies. Comparison of the apoptotic effects of CQAH with those of two illustrated structure-activity associations for this compound type, indicating that substitution at position-4 of the azetidine phenyl ring is pivotal for inducing apoptosis. In conclusion, the results of the present study indicated CQAH and its analogues are potent candidate drugs for the treatment of colon carcinoma.