Efficacy and safety of a combination treatment of immune checkpoint inhibitors in metastatic breast cancer: a systematic review and meta-analysis.

PURPOSE: Immune checkpoint inhibitors (ICIs) in combination with chemotherapy have showed its benefits in clinical studies, and here we conducted a further evaluation on the safety and efficacy of this treatment strategy. METHODS: A systematic literature review was conducted in PubMed, Embase and Cochrane Library to identify clinical studies on ICIs and chemotherapy for metastatic breast cancer. The primary efficacy endpoints were progression-free survival (PFS) and overall survival (OS), and adverse events (AEs) were analyzed. Random or fixed effects models were used to estimate pooled Hazard ratio (HR), odds ratio (OR) and the data of 95% confidence interval (CI) depend on the Heterogeneity. Cochrane risk assessment tool was used to assess risk of bias. We also drew forest plots and funnel plots, respectively. RESULTS: Seven studies with intend-to-treat (ITT) population for 3255 patients were analyzed. ICIs pooled therapy showed clinical benefits compared with chemotherapy alone, improving PFS (HR = 0.81, 95% CI: 0.74-0.90) of patients with metastatic triple negative breast cancer (mTNBC), especially in patients with PD-L1-positive tumors. However, it had no effect on OS (HR = 0.92, 95% CI 0.85-1.01). Besides, mTNBC patients received pooled therapy were less frequently to have AEs (OR = 1.30, 95% CI: 1.09-1.54). In patients with metastatic Human Epidermal Growth Factor Receptor 2 (HER2) negative breast cancer, pooled therapy showed no benefit for PFS (HR = 0.80, 95% CI: 0.50-1.28) and OS (HR = 0.87, 95% CI: 0.48-1.58). CONCLUSION: Pooled therapy had improved PFS in mTNBC patients, especially in patients with PD-L1-positive tumors, and it was less likely to cause grade ≥ 3 AEs.

Immune profiles to predict bortezomib-based treatment response for multiple myeloma patients.

BACKGROUND: To evaluate the distribution of bone marrow immune cell subsets and their correlation with treatment efficacy in patients with multiple myeloma (MM). METHODS: We analyzed the bone marrow lymphocyte subsets of 186 newly diagnosed MM patients at diagnosis and their correlation with clinical characteristics. In our study, eight-color flow cytometry, a method commonly used to detect plasma cell phenotypes, was used to analyze seven bone marrow immune cell groups by change gate-strategy. RESULTS: First, for all the 7 immune cell groups, the percentage of immature B cells was significantly lower in stage III patients than in stage I patients, while the trend was reversed in memory B cells in both the International Staging System(p = 0.004) and Revised International Staging System(p = 0.018). Second, the percentage of naïve B cells were significantly lower in patients with severe anemia, while the percentage of memory B cells had reversed trend. The percentage of immature B cells were lower in patients with Cr ≥ 2 mg/dL than in patients with Cr < 2 mg/dL. Then we followed the treatment efficacy of 152 patients who received four cycles of induction therapy (bortezomib + dexamethasone or bortezomib + lenalidomide + dexamethasone) and analyzed the relationship between bone marrow lymphocyte subsets at the initial stage and treatment response datasets. We found that both the percentage of B cells(p＜0.001) and immature B(p = 0.002) were increased in patients who achieved very good partial remission(VGPR) after four cycles of induction therapy. The ROC results indicated the combination of the multiple immune subgroups had predictive values (AUC = 0.802, p<0.001) in the treatment effect after four cycles of induction therapy. CONCLUSIONS: Overall, these results suggest that the analysis of lymphocyte subsets along with plasma cell immunophenotyping could be a potential index for determining the prognosis of MM patients.

Targeting NKG2D/NKG2DL axis in multiple myeloma therapy.

Immune effector cells in patients with multiple myeloma (MM) are at the forefront of many immunotherapy treatments, and several methods have been developed to fully utilise the antitumour potential of immune cells. T and NK cell-derived immune lymphocytes both expressed activating NK receptor group 2 member D(NKG2D). This receptor can identify eight distinct NKG2D ligands (NKG2DL), including major histocompatibility complex class I (MHC) chain-related protein A and B (MICA and MICB). Their binding to NKG2D triggers effector roles in T and NK cells. NKG2DL is polymorphic in MM cells. The decreased expression of NKG2DL on the cell surface is explained by multiple mechanisms of tumour immune escape. In this review, we discuss the mechanisms by which the NKG2D/NKG2DL axis regulates immune effector cells and strategies for promoting NKG2DL expression and inhibiting its release in multiple myeloma and propose therapeutic strategies that increase the expression of NKG2DL in MM cells while enhancing the activation and killing function of NK cells.

Immune checkpoint inhibitors for multiple myeloma immunotherapy.

Multiple myeloma (MM) is related to immune disorders, recent studys have revealed that immunotherapy can greatly benefit MM patients. Immune checkpoints can negatively modulate the immune system and are closely associated with immune escape. Immune checkpoint-related therapy has attracted much attention and research in MM. However, the efficacy of those therapies need further improvements. There need more thoughts about the immune checkpoint to translate their use in clinical work. In our review, we aggregated the currently known immune checkpoints and their corresponding ligands, further more we propose various ways of potential translation applying treatment based on immune checkpoints for MM patients.

Cellular immunity in the era of modern multiple myeloma therapy.

Multiple myeloma (MM) is a relapsing clonal plasma cell malignancy and incurable thus far. With the increasing understanding of myeloma, highlighting the critical importance of the immune system in the pathogenesis of MM is essential. The immune changes in MM patients after treatment are associated with prognosis. In this review, we summarize currently available MM therapies and discuss how they affect cellular immunity. We find that the modern anti-MM treatments enhance antitumour immune responses. A deeper understanding of the therapeutic activity of individual drugs offers more effective treatment approaches that enhance the beneficial immunomodulatory effects. Furthermore, we show that the immune changes after treatment in MM patients can provide useful prognostic marker. Analysing cellular immune responses offers new perspectives for evaluating clinical data and making comprehensive predictions for applying novel therapies in MM patients.

Therapeutic strategies to enhance immune response induced by multiple myeloma cells.

Multiple myeloma (MM)as a haematological malignancy is still incurable. In addition to the presence of somatic genetic mutations in myeloma patients, the presence of immunosuppressive microenvironment greatly affects the outcome of treatment. Although the discovery of immunotherapy makes it possible to break the risk of high toxicity and side effects of traditional chemotherapeutic drugs, there are still obstacles of ineffective treatment or disease recurrence. In this review, we discuss therapeutic strategies to further enhance the specific anti-tumor immune response by activating the immunogenicity of MM cells themselves. New ideas for future myeloma therapeutic approaches are provided.

Enhanced metabolic activation of and platelet response to clopidogrel in T cell-deficient mice through induction of Cyp2c and Cyp3a and inhibition of Ces1.

BACKGROUND: T cells and platelets reciprocally coordinate mutual functions through crosstalk or interaction. However, it is not known whether metabolic activation of and platelet response to clopidogrel could be changed if T cells were deficient or impaired in some cases and, if any, how it would work. OBJECTIVES: The objective of this study was to dissect the potential changes in platelet responses to and metabolic activation of clopidogrel in the case of T cell deficiency and to elucidate their mechanisms involved. METHODS: BALB/c athymic nude mice or euthymic mice (controls) pretreated with cyclosporine A (CsA), thymosin α1 (Tα1), or their combination were used to investigate the changes in ADP-induced platelet activation and aggregation, systemic exposure of clopidogrel and its metabolites, and mRNA/protein expression and activity levels of clopidogrel-metabolizing enzymes in the liver, respectively. RESULTS: Nude mice exhibited significantly enhanced antiplatelet effects of clopidogrel due to increased formation of clopidogrel active metabolite in the liver, where the enzyme activity levels of Cyp2c and Cyp3a were significantly elevated compared with control mice. Furthermore, the effects of CsA pretreatment on the metabolism of clopidogrel in euthymic mice were identical to those seen in athymic mice. As expected, concomitant use of Tα1 reversed all the observed effects of CsA on clopidogrel metabolism and relevant metabolic enzymes. CONCLUSIONS: T cell deficiency or suppression enhances the antiplatelet effects of clopidogrel due to the boosted metabolic activation of clopidogrel in the liver through a dramatic induction of Cyp2c and Cyp3a in mice, suggesting that the metabolism of substrate drugs of Cyp2c and Cyp3a may be enhanced by T cell impairment.

The prognostic values of FOXP3+ tumor-infiltrating T cells in breast cancer: a systematic review and meta-analysis.

BACKGROUND: Tumor microenvironment is infiltrated by many immune cells, of which Regulatory T (Treg) cells are usually considered as negative regulators of the immune responses. However, the effect of FOXP3+ (forkhead box transcription factor 3) Treg cells infiltrated into the tumor areas on the prognosis of breast cancer is controversial. This meta-analysis aimed to dissect the potential values of FOXP3+ tumor-infiltrating lymphocytes (TILs) as a prognosis predictor of breast cancer. METHODS: After systematic retrieval of all relevant studies, 28 eligible articles were identified for meta-analysis. Odd ratio (OR), hazard ratio (HR), and 95% confidence interval (CI) were obtained for pooled analyses of pathological complete response (pCR), overall survival (OS), and corresponding forest plots and funnel plots were plotted, respectively. RESULTS: Pooled results revealed that patients with higher levels of FOXP3+ TILs experienced better pCR (OR: 1.24, 95% CI 1.09-1.41) and OS (HR: 0.79, 95% CI 0.64-0.97). Subgroup analysis revealed that elevated FOXP3+ TILs were significantly associated with improved pCR (OR: 1.20, 95% CI 1.02-1.40) and OS (HR: 0.22, 95% CI 0.06-0.88) in human epidermal growth factor receptor 2 positive (HER2+) breast cancer patients. Furthermore, FOXP3+ TILs in the stromal area were statistically correlated with the favorable pCR (OR: 1.22, 95% CI 1.08-1.38) and OS (HR: 0.68, 95% CI 0.49-0.96). CONCLUSIONS: The predictive role of FOXP3+ TILs in the prognosis of breast cancer is influenced by various factors such as molecular subtype of breast cancer and the location of Treg. In HER2+ breast cancer and triple-negative breast cancer, FOXP3+ TILs are associated with better pCR and OS. Additionally, FOXP3+ TILs in stromal represent a favourable prognosis.

Few-Electrode EEG from the Wearable Devices Using Domain Adaptation for Depression Detection.

Nowadays, major depressive disorder (MDD) has become a crucial mental disease that endangers human health. Good results have been achieved by electroencephalogram (EEG) signals in the detection of depression. However, EEG signals are time-varying, and the distributions of the different subjects' data are non-uniform, which poses a bad influence on depression detection. In this paper, the deep learning method with domain adaptation is applied to detect depression based on EEG signals. Firstly, the EEG signals are preprocessed and then transformed into pictures by two methods: the first one is to present the three channels of EEG separately in the same image, and the second one is the RGB synthesis of the three channels of EEG. Finally, the training and prediction are performed in the domain adaptation model. The results indicate that the domain adaptation model can effectively extract EEG features and obtain an average accuracy of 77.0 ± 9.7%. This paper proves that the domain adaptation method can effectively weaken the inherent differences of EEG signals, making the diagnosis of different users more accurate.

Effects of CYP2C19 genetic polymorphisms on the cure rates of H. pylori in patients treated with the proton pump inhibitors: An updated meta-analysis.

Background: The cure rates of Helicobacter pylori (H. pylori) treatment using a proton pump inhibitor (PPI) are gradually decreasing due to antibiotic resistance, poor compliance, high gastric acidity, and cytochrome P450 2C19 (CYP2C19) polymorphism, and the effects of PPI depend on metabolic enzymes, cytochrome P450 enzymes. The aim of this meta-analysis was to determine whether CYP2C19 polymorphisms affect H. pylori cure rates in patients treated with different proton pump inhibitors (PPIs) according to stratified analysis. Materials and methods: The literature was searched with the key words "H. pylori" and "CYP2C19" in PubMed, CNKI, and Wanfang up to 31 May 2022, and the studies were limited to clinical observational or randomized controlled trials (RCTs). Finally, seven RCTs and 29 clinical observational studies met the inclusion criteria and were used for the meta-analysis via STATA version 16. Results: The cure rates were significantly different between genotypes of homozygous extensive metabolizers (EM) and poor metabolizers (PM) (OR = 0.58, 95% CI: 0.47-0.71) and between EM and heterozygous extensive metabolizers (IM) (OR = 0.71, 95% CI: 0.59-0.86), but not between IM and PM. Moreover, there was a significantly lower H. pylori cure rate in EM subjects than that in IM subjects when treated with omeprazole (66.4% vs. 84.1%), lansoprazole (76.1% vs. 85.6%), but not rabeprazole, esomeprazole, or pantoprazole. In addition, there was a significantly lower H. pylori cure rate in EM subjects than that in IM subjects when treated with a PPIs for 7 days (77.4% vs. 82.1%), but not 14 days (85.4% vs. 90.0%). Conclusion: Carriers of CYP2C19 loss-of-function variant alleles (IM and PM) exhibit a significantly greater cure rate of H. pylori than noncarriers (EM) regardless of other factors (84.7% vs. 79.2%). In addition, pantoprazole- and rabeprazole-based quadruple therapy for H. pylori treatment is less dependent on the CYP2C19 genotype and should be prioritized in Asian populations with H. pylori.

Adenosinergic axis and immune checkpoint combination therapy in tumor: A new perspective for immunotherapy strategy.

There are two figures and one table in this review, the review consists of 5823 words, without the description of figures and table, but including references. Tumor cells escape anti-tumor immune responses in various ways, including functionally shaping the microenvironment through the secretion of various chemokines and, cytokines. Adenosine is a powerful immunosuppressive metabolite, that is frequently elevated in the extracellular tumor microenvironment (TME). Thus, it has recently been proposed as a novel antitumor immunoassay for targeting adenosine- generating enzymes, such as CD39, CD73, and adenosine receptors. In recent years, the discovery of the immune checkpoints, such as programmed cell death 1(PD-1) and cytotoxic T lymphocyte antigen 4 (CTLA-4), has also greatly changed treatment methods and ideas for malignant tumors. Malignant tumor immunotherapy has been developed from point-to-point therapy targeting immune checkpoints, combining different points of different pathways to create a therapy based on the macroscopic immune regulatory system network. This article reviews the theoretical basis of the adenosine energy axis and immune checkpoint combined therapy for malignant tumors and the latest advances in malignant tumors.

The diagnostic and prognostic value of the miR-17-92 cluster in hepatocellular carcinoma: A meta-analysis.

Previous studies demonstrated that microRNAs (miRNAs) could serve as biomarkers in various cancers. This meta-analysis aimed to determine the roles of a miR-17-92 cluster in hepatocellular carcinoma (HCC). Here, eligible included studies were searched through PubMed, Embase, and Wan Fang databases up to 1st February 2022. Relevant data were extracted from each eligible study to evaluate the relationship between miRNA-17-92 cluster miRNA expression and the diagnosis and prognosis of HCC. Finally, a total of 21 studies were pooled and included in the meta-analysis, of which four articles were used for diagnostic meta-analysis and eight articles were used for prognostic meta-analysis. The pooled sensitivity, specificity, and diagnostic odds ratios (DOR) of the miR17-92 cluster for diagnosis of HCC were 0.75 [95% confidence interval (CI): 0.64-0.83], 0.73 (95% CI: 0.65-0.79), and 7.87 (95% CI: 5.36-11.54), respectively. Also, the area under the curve (AUC) for the miR-17-92 cluster when diagnosing HCC was 0.79 (95% CI: 0.76-0.83). For prognostic analysis, hazard ratios (HRs) with 95% CIs were extracted from the included studies and pooled HRs were determined to assess the associations. Patients with increased expression of miR17-92 cluster miRNA were associated with poor overall survival (OS) and recurrence-free survival (RFS) (HR=1.86, 95% CI: 1.04-3.33; HR = 4.18, 95% CI: 3.02-5.77, respectively), but not progression-free survival (PFS) (HR = 0.43, 95% CI: 0.25-0.73), while no association of the miR-17-92 cluster high-expression was detected with disease-free survival (DFS) (HR: 0.95, 95% CI: 0.21-4.34). In short, current pieces of evidence suggested that the miR-17-92 cluster may serve as a novel diagnostic and prognostic biomarker for HCC. However, given the limited study number, larger-size, multi-center, and higher-quality studies are indispensable in the future.

Genetic Variation of Inflammatory Genes to Ischemic Stroke Risk in a Chinese Han Population.

BACKGROUND: Inflammation proteins play an important role in stroke occurrence. IL1A, IL1B, PTGS2, MMP2, and MMP9 were the mediators involved in the immune response, and the association of these genetic variations with ischemic stroke (IS) risk was still unclear. METHODS: To investigate the susceptibility of genetic variations of IL1A, IL1B, PTGS2, MMP2, and MMP9 to IS risk, we performed a case-control study involving 299 patients and 300 controls in a Chinese population. Thirteen genetic variations of investigated genes of all participants were genotyped using an improved multiplex ligase detection-reaction technique. RESULTS: No SNP in all genes showed an association with overall IS. However, in subgroup analysis, PTGS2 rs689466 (dominant model: CT vs TT - ORadjusted= 2.51, 95% CI: 1.22-5.16, p = 0.012; co-dominant model: CT/CC vs TT - ORadjusted= 2.53, 95% CI: 1.26-5.07, p = 0.009; additive model - ORadjusted= 2.26, 95% CI: 1.19-4.28, p = 0.013) and rs5275 (dominant model: GG vs AA - ORadjusted= 0.31, 95% CI: 0.12-0.80, p = 0.016; co-dominant model: GA/GG vs AA - ORadjusted= 0.45, 95% CI: 0.21-0.95, p = 0.036; additive model - ORadjusted= 0.60, 95% CI: 0.39-0.92, p = 0.020) were associated with IS type of small-vessel occlusion. CONCLUSION: Our study suggested that PTGS2 rs689466 C and rs5275 A were potentially associated with IS subtype of small-vessel occlusion. Our result should be confirmed with further large sample sized studies.

Deep Neural Network with Joint Distribution Matching for Cross-Subject Motor Imagery Brain-Computer Interfaces.

Motor imagery brain-computer interfaces (BCIs) have demonstrated great potential and attract world-spread attentions. Due to the nonstationary character of the motor imagery signals, costly and boring calibration sessions must be proceeded before use. This prevents them from going into our realistic life. In this paper, the source subject's data are explored to perform calibration for target subjects. Model trained on source subjects is transferred to work for target subjects, in which the critical problem to handle is the distribution shift. It is found that the performance of classification would be bad when only the marginal distributions of source and target are made closer, since the discriminative directions of the source and target domains may still be much different. In order to solve the problem, our idea comes that joint distribution adaptation is indispensable. It makes the classifier trained in the source domain perform well in the target domain. Specifically, a measure for joint distribution discrepancy (JDD) between the source and target is proposed. Experiments demonstrate that it can align source and target data according to the class they belong to. It has a direct relationship with classification accuracy and works well for transferring. Secondly, a deep neural network with joint distribution matching for zero-training motor imagery BCI is proposed. It explores both marginal and joint distribution adaptation to alleviate distribution discrepancy across subjects and obtain effective and generalized features in an aligned common space. Visualizations of intermediate layers illustrate how and why the network works well. Experiments on the two datasets prove the effectiveness and strength compared to outstanding counterparts.

Role of autophagy in sonodynamic therapy-induced cytotoxicity in S180 cells.

Few reports have been published on the potential role of autophagy in the efficacy of sonodynamic therapy (SDT). This study was to determine whether autophagy occurred after SDT and to investigate its relationship with apoptosis by performing inhibitor studies. In vitro murine sarcoma 180 (S180) cells were examined at different time points following SDT. Transmission electron microscopy (TEM) was used to identify the formation of autophagosomes. Western blots were used to assess the processing of LC3-I to LC3-II. Confocal microscopy was performed to reveal co-localization between mitochondria and autophagic vacuoles and re-distribution of apoptosis related proteins after sono-damage. Inhibitors of apoptosis and autophagy were used to determine the contributions of the two cellular responses to SDT efficacy. Autophagy was indentified by TEM observation of the presence of double-membrane delineated autophagic vesicles and by immunoblot observation of the increased LC3-II levels. The autophagy inhibitors, both 3-methyladenine (3-MA) and Bafilomycin A1 (Ba A1), were found to significantly enhance SDT-induced cell death. Blocking autophagy also led to increased dissipation of mitochondria potential, caspase-3 activity and the ultimate cell apoptosis. Whereas the pan-caspase inhibitor, z-VAD-fmk partially prevented SDT-induced cytotoxicity but did not obviously improve the autophagic vacuolization and mitochondria depolarization. This study suggests for the first time that autophagy participate in SDT-induced cell death and combination of SDT with autophagy inhibitors, especially preventing autophagy at the early stage by 3-MA, can significantly enhance the anti-tumor effect of SDT through induction of apoptosis and necrosis.