LC-MS/MS platform-based serum untargeted screening reveals the diagnostic biomarker panel and molecular mechanism of breast cancer.

BACKGROUND: Breast cancer (BC), the most common form of malignant cancer affecting women worldwide, was characterized by heterogeneous metabolic disorder and lack of effective biomarkers for diagnosis. The purpose of this study is to search for reliable metabolite biomarkers of BC as well as triple-negative breast cancer (TNBC) using serum metabolomics approach. METHODS: In this study, an untargeted metabolomics technique based on ultra-high performance liquid chromatography combined with mass spectrometry (UHPLC-MS) was utilized to investigate the differences in serum metabolic profile between the BC group (n = 53) and non-BC group (n = 57), as well as between TNBC patients (n = 23) and non-TNBC subjects (n = 30). The multivariate data analysis, determination of the fold change and the Mann-Whitney U test were used to screen out the differential metabolites. Additionally, machine learning methods including receiver operating curve analysis and logistic regression analysis were conducted to establish diagnostic biomarker panels. RESULTS: There were 36 metabolites found to be significantly different between BC and non-BC groups, and 12 metabolites discovered to be significantly different between TNBC and non-TNBC patients. Results also showed that four metabolites, including N-acetyl-D-tryptophan, 2-arachidonoylglycerol, pipecolic acid and oxoglutaric acid, were considered as vital biomarkers for the diagnosis of BC and non-BC with an area under the curve (AUC) of 0.995. Another two-metabolite panel of N-acetyl-D-tryptophan and 2-arachidonoylglycerol was discovered to discriminate TNBC from non-TNBC and produced an AUC of 0.965. CONCLUSION: This study demonstrated that serum metabolomics can be used to identify BC specifically and identified promising serum metabolic markers for TNBC diagnosis.

Targeting tumor-associated macrophage: an adjuvant strategy for lung cancer therapy.

The emergence of immunotherapy has revolutionized the treatment landscape for various types of cancer. Nevertheless, lung cancer remains one of the leading causes of cancer-related mortality worldwide due to the development of resistance in most patients. As one of the most abundant groups of immune cells in the tumor microenvironment (TME), tumor-associated macrophages (TAMs) play crucial and complex roles in the development of lung cancer, including the regulation of immunosuppressive TME remodeling, metabolic reprogramming, neoangiogenesis, metastasis, and promotion of tumoral neurogenesis. Hence, relevant strategies for lung cancer therapy, such as inhibition of macrophage recruitment, TAM reprograming, depletion of TAMs, and engineering of TAMs for drug delivery, have been developed. Based on the satisfactory treatment effect of TAM-targeted therapy, recent studies also investigated its synergistic effect with current therapies for lung cancer, including immunotherapy, radiotherapy, chemotherapy, anti-epidermal growth factor receptor (anti-EGFR) treatment, or photodynamic therapy. Thus, in this article, we summarized the key mechanisms of TAMs contributing to lung cancer progression and elaborated on the novel therapeutic strategies against TAMs. We also discussed the therapeutic potential of TAM targeting as adjuvant therapy in the current treatment of lung cancer, particularly highlighting the TAM-centered strategies for improving the efficacy of anti-programmed cell death-1/programmed cell death-ligand 1 (anti-PD-1/PD-L1) treatment.

miR-34a/DRP-1-mediated mitophagy participated in cisplatin-induced ototoxicity via increasing oxidative stress.

PURPOSE: Cisplatin is a widely used and effective chemotherapeutic agent for most solid malignant tumors. However, cisplatin-induced ototoxicity is a common adverse effect that limits the therapeutic efficacy of tumors in the clinic. To date, the specific mechanism of ototoxicity has not been fully elucidated, and the management of cisplatin-induced ototoxicity is also an urgent challenge. Recently, some authors believed that miR34a and mitophagy played a role in age-related and drug-induced hearing loss. Our study aimed to explore the involvement of miR-34a/DRP-1-mediated mitophagy in cisplatin-induced ototoxicity. METHODS: In this study, C57BL/6 mice and HEI-OC1 cells were treated with cisplatin. MiR-34a and DRP-1 levels were analyzed by qRT‒PCR and western blotting, and mitochondrial function was assessed via oxidative stress, JC-1 and ATP content. Subsequently, we detected DRP-1 levels and observed mitochondrial function by modulating miR-34a expression in HEI-OC1 cells to determine the effect of miR-34a on DRP-1-mediated mitophagy. RESULTS: MiR-34a expression increased and DRP-1 levels decreased in C57BL/6 mice and HEI-OC1 cells treated with cisplatin, and mitochondrial dysfunction was involved in this process. Furthermore, the miR-34a mimic decreased DRP-1 expression, enhanced cisplatin-induced ototoxicity and aggravated mitochondrial dysfunction. We further verified that the miR-34a inhibitor increased DRP-1 expression, partially protected against cisplatin-induced ototoxicity and improved mitochondrial function. CONCLUSION: MiR-34a/DRP-1-mediated mitophagy was related to cisplatin-induced ototoxicity and might be a novel target for investigating the treatment and protection of cisplatin-induced ototoxicity.

Diagnostic biomarker panels of osteoarthritis: UPLC-QToF/MS-based serum metabolic profiling.

Osteoarthritis (OA) is the most common joint disease in the world, characterized by pain and loss of joint function, which has led to a serious reduction in the quality of patients' lives. In this work, ultrahigh performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-QToF/MS) in conjunction with multivariate pattern recognition methods and an univariate statistical analysis scheme were applied to explore the serum metabolic signatures within OA group (n = 31), HC (healthy controls) group (n = 57) and non-OA group (n = 19) for early diagnosis and differential diagnosis of OA. Based on logistic regression analysis and receiver operating characteristic (ROC) curve analysis, seven metabolites, including phosphatidylcholine (18:0/22:6), p-cresol sulfate and so on, were identified as critical metabolites for the diagnosis of OA and HC and yielded an area under the curve (AUC) of 0.978. The other panel of unknown m/z 239.091, phosphatidylcholine (18:0/18:0) and phenylalanine were found to distinguish OA from non-OA and achieved an AUC of 0.888. These potential biomarkers are mainly involved in lipid metabolism, glucose metabolism and amino acid metabolism. It is expected to reveal new insight into OA pathogenesis from changed metabolic pathways.

A research review of experimental animal models with myelodysplastic syndrome.

Myelodysplastic syndrome (MDS) consists of a group of hematologic tumors that are derived from the clonal proliferation of hematopoietic stem cells, featuring abnormal hematopoietic cell development and ineffective hematopoiesis. Animal models are an important scientific research platform that has been widely applied in the research of human diseases, especially tumors. Animal models with MDS can simulate characteristic human genetic variations and tumor phenotypes. They also provide a reliable platform for the exploration of the pathogenesis and diagnostic markers of MDS as well as for a drug efficacy evaluation. This paper reviews the research status of three animal models and a new spontaneous mouse model with MDS.

Identification of a five-miRNA signature as a novel potential prognostic biomarker in patients with nasopharyngeal carcinoma.

BACKGROUND: MicroRNAs (miRNAs) are involved in the prognosis of nasopharyngeal carcinoma (NPC). This study used clinical data and expression data of miRNAs to develop a prognostic survival signature for NPC patients to detect high-risk subject. RESULTS: We identified 160 differentially expressed miRNAs using RNA-Seq data from the GEO database. Cox regression model consisting of hsa-miR-26a, hsa-let-7e, hsa-miR-647, hsa-miR-30e, and hsa-miR-93 was constructed by the least absolute contraction and selection operator (LASSO) in the training set. All the patients were classified into high-risk or low-risk groups by the optimal cutoff value of the 5-miRNA signature risk score, and the two risk groups demonstrated significant different survival. The 5-miRNA signature showed high predictive and prognostic accuracies. The results were further confirmed in validation and external validation set. Results from multivariate Cox regression analysis validated 5-miRNA signature as an independent prognostic factor. A total of 13 target genes were predicted to be the target genes of miRNA target genes. Both PPI analysis and KEGG analysis networks were closely related to tumor signaling pathways. The prognostic model of mRNAs constructed using data from the dataset GSE102349 had higher AUCs of the target genes and higher immune infiltration scores of the low-risk groups. The mRNA prognostic model also performed well on the independent immunotherapy dataset Imvigor210. CONCLUSIONS: This study constructed a novel 5-miRNA signature for prognostic prediction of the survival of NPC patients and may be useful for individualized treatment of NPC patients.

The changes in pyroptosis-related inflammatory factors in the peripheral blood of patients with Henoch-Schonlein purpura.

BACKGROUND: Henoch-Schonlein purpura (HSP) is a common capillary allergic bleeding disease. To explore the variation of pyroptosis-related inflammatory factors level in the peripheral blood of patients with HSP. METHODS: A total of 87 HSP patients treated in our hospital from June 2020 to March 2021 were selected and divided into the renal impairment group (n=29) and the non-renal impairment group (n=58) according to the presence of hematuria and proteinuria. A total of 50 healthy individuals from the hospital were selected as the control group. The renal impairment and non-renal impairment groups were treated with a regular regimen of compound glycyrrhizin tablets and glucocorticoids, respectively. Serum interleukin (IL)-18, IL-1ß, and peripheral caspase-1-positive cells were compared pre- and post-treatment among the three groups. RESULTS: The pre-treatment serum IL-1ß levels in the renal impairment and non-renal impairment groups were significantly higher than that in the control group (P<0.01). After treatment, the IL-1ß level in the non-renal impairment group was not significantly different from that in the control group (P>0.05). However, the IL-1ß level in the renal impairment group post-treatment was significantly higher than that in the other two groups (P<0.01). The positive rate of caspase-1 expression in peripheral blood before treatment in the renal impairment group and non-renal impairment group was significantly higher than that in the control group (P<0.01). After treatment, the positive rate of caspase-1 expression in the non-renal impairment group was comparable to that in the control group (P>0.05), whereas the rate in the renal impairment group was significantly higher than that in the other two groups (P<0.01). After treatment, the serum IL-1ß levels and caspase-1 positive rate in HSP patients who were responsive to treatment (as assessed by hematuria or proteinuria levels after treatment) were lower than that in patients who were unresponsive to treatment P<0.001), but not significantly different to the control group (P>0.05). CONCLUSIONS: The levels of serum IL-1ß and caspase-1 changed in response to alterations in the disease condition and treatment response in HSP patients, which suggested that pyroptosis-related inflammatory factors may have potential application value in predicting disease progression and efficacy of hormone therapy.

[Application of serum amino acid profile in urolithiasis based on gas chromatography-mass spectrometry].

An overall workflow based on gas chromatography-mass spectrometry (GC-MS) was established for the analysis of the serum amino acid profile between urolithiasis patients (n=80, age (46.82±13.39) years) and healthy controls (n=37, age (43.46±12.79) years). The raw data from GC-MS analysis were processed by multivariate statistical methods to build the model. Following this, student's t-test and logistic regression were performed and receiver operator characteristic (ROC) curve was plotted to identify the potential biomarkers. Good linearities were observed for the target amino acids, with correlation coefficients (R2) greater than 0.9985. The limits of detection (LODs) were 0.1-4.0 µmol/L. The results indicated a significant discrimination between the urolithiasis and control groups. Five significantly differentially expressed amino acids (variable importance in projection (VIP)>1 and p<0.05) were found to provide the scientific evidence for the early diagnosis of urolithiasis, while the sensitivity of the integrated five differential amino acids was up to 97.3%. In particular, the area under the curve (AUC) of serine reached 0.819, which suggested a great clinical screening value.