Search

The therapeutic efficacy of immunotherapy is limited in the majority of colorectal cancer patients due to the low mutational and neoantigen burdens in this immunogenically “cold” microsatellite stability-colorectal cancer (MSS-CRC) cohort. Here, we showed that DNA methyltransferase (DNMT) inhibition upregulated neoantigen-bearing gene expression in MSS-CRC, resulting in increased neoantigen presentation by MHC class I in tumor cells and leading to increased neoantigen-specific T-cell activation in combination with radiotherapy. The cytotoxicity of neoantigen-reactive T cells (NRTs) to DNMTi-treated cancer cells was highly cytotoxic, and these cells secreted high IFNγ levels targeting MSS-CRC cells after ex vivo expansion of NRTs with DNMTi-treated tumor antigens. Moreover, the therapeutic efficacy of NRTs further increased when NRTs were combined with radiotherapy in vivo. Administration of DNMTi-augmented NRTs and radiotherapy achieved an ∼50 % complete response and extended survival time in an immunocompetent MSS-CRC animal model. Moreover, remarkably, splenocytes from these mice exhibited neoantigen-specific T-cell responses, indicating that radiotherapy in combination with DNMTi-augmented NRTs prolonged and increased neoantigen-specific T-cell toxicity in MSS-CRC patients. In addition, these DNMTi-augmented NRTs markedly increase the therapeutic efficacy of cancer vaccines and immune checkpoint inhibitors (ICIs). These data suggest that a combination of radiotherapy and epi-immunotherapeutic agents improves the function of ex vivo-expanded neoantigen-reactive T cells and increases the tumor-specific cytotoxic effector population to enhance therapeutic efficacy in MSS-CRC.

Background The systemic inflammatory response index (SIRI), served as a novel inflammatory biomarker, is the synthesis of neutrophils, monocytes and lymphocytes.Aims We hypothesized that SIRI has predictive value for contrast-associated acute kidney injury (CA-AKI) and long-term mortality in patients undergoing elective percutaneous coronary intervention (PCI).Methods We retrospectively observed 5685 patients undergoing elective PCI from January 2012 to December 2018. Venous blood samples were collected to obtain the experimental data on the day of admission or the morning of the next day. SIRI = neutrophil count × monocyte count/lymphocyte count. CA-AKI was defined as an increase of 50% or 0.3 mg/dl in SCr from baseline within 48 h after contrast exposure.Results The incidence of CA-AKI was 6.1% (n = 352). The best cutoff value of SIRI for predicting CA-AKI was 1.39, with a sensitivity of 52.3% and a specificity of 67.3%. [AUC: 0.620, 95% confidence interval (CI): 0.590–0.651, p 1.39) was a strong independent predictor of CA-AKI in patients undergoing elective PCI compared with the low SIRI group (SIRI ≤ 1.39) (odds ratio = 1.642, 95% CI: 1.274–2.116, p 1.39 was significantly associated with long-term mortality at a median follow-up of 2.8 years. [Hazard ratio (HR)=1.448, 95%CI: 1.188–1.765; p

Background Cancer-intrinsic type I interferon (IFN-I) production triggered by radiotherapy (RT) is mainly dependent on cytosolic double-stranded DNA (dsDNA)-mediated cGAS/STING signaling and increases cancer immunogenicity and enhances the antitumor immune response to increase therapeutic efficacy. However, cGAS/STING deficiency in colorectal cancer (CRC) may suppress the RT-induced antitumor immunity. Therefore, we aimed to evaluate the importance of the dsRNA-mediated antitumor immune response induced by RT in patients with CRC.Methods Cytosolic dsRNA level and its sensors were evaluated via cell-based assays (co-culture assay, confocal microscopy, pharmacological inhibition and immunofluorescent staining) and in vivo experiments. Biopsies and surgical tissues from patients with CRC who received preoperative chemoradiotherapy (neoCRT) were collected for multiplex cytokine assays, immunohistochemical analysis and SNP genotyping. We also generated a cancer-specific adenovirus-associated virus (AAV)-IFNβ1 construct to evaluate its therapeutic efficacy in combination with RT, and the immune profiles were analyzed by flow cytometry and RNA-seq.Results Our studies revealed that RT stimulates the autonomous release of dsRNA from cancer cells to activate TLR3-mediated IFN-I signatures to facilitate antitumor immune responses. Patients harboring a dysfunctional TLR3 variant had reduced serum levels of IFN-I-related cytokines and intratumoral CD8+ immune cells and shorter disease-free survival following neoCRT treatment. The engineered cancer-targeted construct AAV-IFNβ1 significantly improved the response to RT, leading to systematic eradication of distant tumors and prolonged survival in defective TLR3 preclinical models.Conclusion Our results support that increasing cancer-intrinsic IFNβ1 expression is an immunotherapeutic strategy that enhances the RT-induced antitumor immune response in locally patients with advanced CRC with dysfunctional TLR3.

Abstract ATP and its receptor P2RX7 exert a pivotal effect on antitumor immunity during chemotherapy-induced immunogenic cell death (ICD). Here, we demonstrated that TNFα-mediated PANX1 cleavage was essential for ATP release in response to chemotherapy in colorectal cancer (CRC). TNFα promoted PANX1 cleavage via a caspase 8/3-dependent pathway to enhance cancer cell immunogenicity, leading to dendritic cell maturation and T-cell activation. Blockade of the ATP receptor P2RX7 by the systemic administration of small molecules significantly attenuated the therapeutic efficacy of chemotherapy and decreased the infiltration of immune cells. In contrast, administration of an ATP mimic markedly increased the therapeutic efficacy of chemotherapy and enhanced the infiltration of immune cells in vivo. High PANX1 expression was positively correlated with the recruitment of DCs and T cells within the tumor microenvironment and was associated with favorable survival outcomes in CRC patients who received adjuvant chemotherapy. Furthermore, a loss-of-function P2RX7 mutation was associated with reduced infiltration of CD8+ immune cells and poor survival outcomes in patients. Taken together, these results reveal that TNFα-mediated PANX1 cleavage promotes ATP-P2RX7 signaling and is a key determinant of chemotherapy-induced antitumor immunity.

Abstract Regional lymph node metastasis is an important predictor for survival outcome and an indicator for postoperative adjuvant chemotherapy in patients with colorectal cancer. Even with advances in adjuvant chemotherapeutic regimens, 5-year distant metastasis and survival rates are still unsatisfactory. Here, we evaluate the clinical significance of polymorphisms in receptors for HMGB1, which is the hallmark of chemotherapy-induced immunogenic cell death, in patients with stage II–III colon carcinoma (COAD). We found that high cytosolic HMGB1 is elicited in stage III COAD patients who received adjuvant chemotherapy. Patients with the TLR1-N248S polymorphism (rs4833095), which causes loss-of-function in HMGB1-mediated TLR1–TLR2 signaling, may influence the therapeutic efficacy of adjuvant chemotherapy, leading to a high risk of distant metastasis within 5 years [HR = 1.694, 95% CI = 1.063–2.698, p = 0.027], suggesting that TLR1-N248S is an independent prognostic factor for locally advanced colon carcinoma patients. We found that defective TLR1 impaired TLR1/2 signaling during dendritic cell (DC) maturation for the antitumor immune response under immunogenic chemotherapy oxaliplatin (OXP) treatment. Defective TLR1 on DCs impaired their maturation ability by HMGB1 and reduced the secretion of IFNγ from T cells to eradicate tumor cells in vitro. Moreover, systemic inhibition of TLR1/2 dramatically reduced the tumor-infiltrating immune cells by OXP treatment, leading to poor therapeutic response to OXP. In contrast, administration of a TLR1/2 agonist synergistically increased the benefit of OXP treatment and triggered a high density of tumor-infiltrating immune cells. We also observed that fewer tumor-infiltrating cytotoxic T lymphocytes were located within the tumor microenvironment in patients bearing the TLR1-N248S polymorphism. Overall, our results suggest that dysfunctional TLR1 may reduce the therapeutic response to adjuvant chemotherapy by impairing HMGB1-mediated DC maturation and attenuating the antitumor immune response in locally advanced colon carcinoma patients.

Groundwater systems, or also commonly known as large-scale closed and saturated porous media systems in general, are important sources of potable water, especially in arid countries. However, maintenance of groundwater systems is operationally expensive and time-consuming, hence requiring field engineers to optimally predict the system’s breakthrough phase. To address this engineering challenge, this study developed an alternative physics informed machine learning model, termed as multiscale homogenized physics informed neural network (MHPINN), to model and predict the effluent discharge concentrations from closed and saturated porous media systems when removing different contaminants. The proposed MHPINN model mainly exploits the homogenization theory, coupled with multiscale perturbation analysis, for hydrodynamic modelling to extract important model input features pertaining to the pore-scale clogging behavior in porous media. Together with available experimental data, the extracted model features then set the input layer for training neural network model to predict the discharge concentration of emulated porous media groundwater systems. At the same time, the model training is performed with modified mean square error (MSE) cost function, based upon homogenized mathematical representations derived from a series of rigorous mathematical constructs and formulations, to better facilitate the model’s learning, especially under sparse data constraint. To verify the proposed methodology, MPINN is trained (and validated) with data obtained from five historical experimental studies, which emulated porous media systems to remove ammonium ions and fine-scaled colloids, to model and predict the discharge concentration in each study. Overall, MHPINN outperformed other conventional machine learning models (random forest, support vector machines, etc.) by obtaining higher predictive accuracy of around 4% on average from the model’s validation step across the five different experimental studies. Therefore, the predictive analysis underscored the effectiveness of MHPINN to combine both physics-based modelling and machine learning to model complex porous media systems, under sparse experimental data constraints, hence demonstrating the potential of the proposed methodology to extend to other physical systems.

Acoustic sensors are widely deployed to detect hidden leakages in water distribution networks (WDNs). However, few studies have been conducted to quantitatively understand the dominant leakage acoustic characteristics, which are usually mixed with unknown environmental noises, coupled with the constraint of sparse deployment of acoustic sensors. In this paper, a comprehensive approach, that performs acoustic data feature analysis, is developed to detect pipe leakages in near real-time via a series of systematic analyses, namely: (1) data quality assessment; (2) features identifications; (3) outlier detection and event classification; and finally (4) near real-time leakage detection. The proposed solution has been tested on two major WDNs in Singapore having around 1,000 km of water pipelines installed with 74 permanently installed hydrophone sensors. The leakage detection results obtained from our case study demonstrate that the dominant leakage acoustic characteristics can be captured in lower intrinsic mode functions (IMFs), to within the frequency range of 100–750 Hz approximately, by decomposing the original acoustic signal. Systemwide leakage event detection and classification models are subsequently trained and tested on acoustic datasets collected over 13 historical months, where more than 70% F1-scores can be obtained from the emulated near real-time leakage detection analysis. HIGHLIGHTS Developed acoustic feature-based methodology for near real-time leakage event detection and classification.; Verified methodology with 74 permanently installed hydrophones in two water supply zones having 1,000 km water pipelines in Singapore.; Achieved F1-score of >70% for leakage event detection and classification analyses on imbalanced acoustic datasets collected over 13 months.;