Novel clinical biomarkers in blood and pleural effusion for diagnosing patients with tuberculosis distinguishing from malignant tumor.

Pleural effusion (PE) is a common manifestation of tuberculosis (TB) and malignant tumors but tuberculous PE (TPE) is difficult to distinguish from malignant PE (MPE), especially by noninvasive detection indicators. This study aimed to find effective detection indices in blood and PE for differentiating TB from a malignant tumor. A total of 815 patients who were diagnosed with TB or cancer in Hubei Shiyan Taihe Hospital from 2014 to 2017 were collected. Amongst them, 717 were found to have PE by thoracoscopy. Clinical characteristics, patients' blood parameters and PE indicator information were summarized for analysis. Patients with MPE had higher percentages to be bloody and negative of Rivalta test in PE than those with TPE. For clinical indicators, comparison of the specific parameters in blood showed that 18 indicators were higher in the TPE group than in the MPE group. By contrast, 12 indicators were higher in the MPE group than in the TPE group (P < .01). In addition, in PE tests, 3 parameters were higher in the TPE group, whereas other 4 parameters were higher in the MPE group (P < .01). Then, for clinical diagnosing practice, ROC analysis and principal component analysis were applied. The top 6 relevant indicators with area under curve over 0.70 were screened out as follows: hydrothorax adenosine dehydrogenase (pADA, 0.90), hydrothorax high-sensitivity C reactive protein (0.79), percentage of blood monocyte (sMONp, 0.75), blood high-sensitivity C reactive protein (sHsCRP, 0.73), erythrocyte sedimentation rate (0.71) and blood D-dimer (0.70). Moreover, logistic regression model revealed that a specific combination of 3 biomarkers, namely, pADA, sMONp and sHsCRP, could enhance the distinguishment of TB from malignant tumor with PE (area under curve = 0.944, 95% confidence interval = 0.925-0.964). The diagnostic function of the top single marker pADA in patients from different groups was analyzed and it was found to maintain high specificity and sensitivity. The 6 indicators, namely, pADA, hydrothorax high-sensitivity C reactive protein, sMONp, sHsCRP, sESR and blood D-dimer, showed significant diagnostic value for clinicians. Further, the combination of pADA, sMONp and sHsCRP has high accuracy for differential diagnosis for the first time. Most interestingly, the single marker pADA maintained high specificity and sensitivity in patients with different statuses and thus has great value for rapid and accurate diagnosis of suspected cases.

The key role of sphingolipid metabolism in cancer: New therapeutic targets, diagnostic and prognostic values, and anti-tumor immunotherapy resistance.

Biologically active sphingolipids are closely related to the growth, differentiation, aging, and apoptosis of cancer cells. Some sphingolipids, such as ceramides, are favorable metabolites in the sphingolipid metabolic pathway, usually mediating antiproliferative responses, through inhibiting cancer cell growth and migration, as well as inducing autophagy and apoptosis. However, other sphingolipids, such as S1P, play the opposite role, which induces cancer cell transformation, migration and growth and promotes drug resistance. There are also other sphingolipids, as well as enzymes, played potentially critical roles in cancer physiology and therapeutics. This review aimed to explore the important roles of sphingolipid metabolism in cancer. In this article, we summarized the role and value of sphingolipid metabolism in cancer, including the distribution of sphingolipids, the functions, and their relevance to cancer diagnosis and prognosis. We also summarized the known and potential antitumor targets present in sphingolipid metabolism, analyzed the correlation between sphingolipid metabolism and tumor immunity, and summarize the antitumor effects of natural compounds based on sphingolipids. Through the analysis and summary of sphingolipid antitumor therapeutic targets and immune correlation, we aim to provide ideas for the development of new antitumor drugs, exploration of new therapeutic means for tumors, and study of immunotherapy resistance mechanisms.

Andrographolide suppresses non-small-cell lung cancer progression through induction of autophagy and antitumor immune response.

Despite recent advances in diagnosis and therapeutic strategies, treatment of non-small-cell lung cancer (NSCLC) remains unsatisfactory in terms of prognosis. Andrographolide (AD), a principal active component of Andrographis paniculata (Burm.f.) Nees, exerts anti-cancer therapeutic properties. AD has been used for centuries in China for clinical treatment of viral infections. However, the pharmacological biology of AD in NSCLC remains unknown. In this study, AD regulated autophagy and PD-L1 expression in NSCLC. Molecular dynamics simulations indicated that AD bound directly to signal transducer and activator of transcription-3 (STAT3) with high affinity. Proteomics analysis indicated that AD reduced the expression of tumour PD-L1 in NSCLC by suppressing JAK2/STAT3 signalling. AD modulated the P62-dependent selective autophagic degradation of PD-L1 by inhibiting STAT3 phosphorylation. In vivo study revealed that AD suppressed tumour growth in H1975 xenograft mice and Lewis lung carcinoma cell models, and better efficacy was obtained at higher concentrations. AD prolonged the survival time of the mice and enhanced the treatment efficacy of anti-PD-1 mAb immunotherapy by stimulating CD8+ T cell infiltration and function. This work elucidated the specific mechanism by which AD inhibited NSCLC. Treatment with the combination of AD and anti-PD-1 mAb immunotherapy could be a potential strategy for patients with NSCLC.

Emodin induces apoptosis and suppresses non-small-cell lung cancer growth via downregulation of sPLA2-IIa.

BACKGROUND: Lung cancer has become the principal cause of cancer-related deaths. Emodin is a Chinese herb-derived compound extracted from the roots of Rheum officinale that exhibits numerous pharmacological characteristics. Secretory phospholipase A2-IIa (sPLA2-IIa) is overexpressed in cancers and plays an important role in cancer development. PURPOSE: This study aims to investigate the anti-tumor mechanism of emodin in non-small-cell lung cancer (NSCLC). METHODS: MTT assay was applied to detect the sensitivity of emodin to NSCLC cell line. Flow cytometry was used to examine the effect of emodin on cell cycle distribution and evaluate ROS level and apoptosis. Western blot analysis was utilised to examine the expression levels of sPLA2-IIa, PKM2, and AMPK and its downstream pathways induced by emodin. Enzyme inhibition assay was applied to investigate the inhibitory effect of emodin on sPLA2-IIa. The anticancer effect of emodin was also detected using an in vivo model. RESULTS: Emodin significantly inhibited NSCLC proliferation in vivo and in vitro and was relatively less cytotoxic to normal lung cell lines. Most importantly, emodin inhibited the proliferation of KRAS mutant cell lines by decreasing the expression of sPLA2-IIa and NF-κB pathways. Emodin also inhibited mTOR and AKT and activated the AMPK pathway. Furthermore, emodin induced apoptosis, increased the reactive oxygen species (ROS) level, and arrested the cell cycle. CONCLUSION: Emodin exhibited a novel anti-tumor mechanism of inhibiting the proliferation of KRAS mutant cell lines by decreasing the expression levels of sPLA2-IIa and NF-κB pathways. Hence, emodin can potentially serve as a therapeutic target in NSCLC.

Potential prognostic factors in progression-free survival for patients with cervical cancer.

BACKGROUND: Cervical cancer continues to be one of the leading causes of cancer deaths among females in low and middle-income countries. In this study, we aimed to assess the independent prognostic value of clinical and potential prognostic factors in progression-free survival (PFS) in cervical cancer. METHODS: We conducted a retrospective study on 92 cervical cancer patients treated from 2017 to 2019 at the Zhuhai Hospital of Traditional Chinese and Western Medicine. Tumor characteristics, treatment options, progression-free survival and follow-up information were collected. Kaplan-Meier method was used to assess the PFS. RESULTS: Results showed that the number of retrieved lymph nodes had a statistically significant effect on PFS of cervical cancer patients (P = 0.002). Kaplan-Meier survival curve analysis showed that cervical cancer patients with initial symptoms age 25-39 had worse survival prognoses (P = 0.020). And the using of uterine manipulator in laparoscopic treatment showed a better prognosis (P < 0.001). A novel discovery of our study was to verify the prognostic values of retrieved lymph nodes count combining with FIGO staging system, which had never been investigated in cervical cancer before. According to the Kaplan-Meier survival curve analysis and receiver operating characteristic (ROC) curve analysis, significant improvements were found after the combination of retrieved lymph nodes count and FIGO stage in predicting PFS for cervical cancer patients (P < 0.001, AUC = 0.826, 95% CI: 0.689-0.962). CONCLUSION: Number of retrieved lymph nodes, initial symptoms age, uterine manipulator, and retrieved lymph nodes count combining with FIGO staging system could be potential prognostic factors for cervical cancer patients.

Early lung cancer diagnostic biomarker discovery by machine learning methods.

Early diagnosis has been proved to improve survival rate of lung cancer patients. The availability of blood-based screening could increase early lung cancer patient uptake. Our present study attempted to discover Chinese patients' plasma metabolites as diagnostic biomarkers for lung cancer. In this work, we use a pioneering interdisciplinary mechanism, which is firstly applied to lung cancer, to detect early lung cancer diagnostic biomarkers by combining metabolomics and machine learning methods. We collected total 110 lung cancer patients and 43 healthy individuals in our study. Levels of 61 plasma metabolites were from targeted metabolomic study using LC-MS/MS. A specific combination of six metabolic biomarkers note-worthily enabling the discrimination between stage I lung cancer patients and healthy individuals (AUC = 0.989, Sensitivity = 98.1%, Specificity = 100.0%). And the top 5 relative importance metabolic biomarkers developed by FCBF algorithm also could be potential screening biomarkers for early detection of lung cancer. Naïve Bayes is recommended as an exploitable tool for early lung tumor prediction. This research will provide strong support for the feasibility of blood-based screening, and bring a more accurate, quick and integrated application tool for early lung cancer diagnostic. The proposed interdisciplinary method could be adapted to other cancer beyond lung cancer.