A precise molecular subtyping of ulcerative colitis reveals the immune heterogeneity and predicts clinical drug responses.

BACKGROUND AND AIMS: We sought to identify novel molecular subtypes of ulcerative colitis (UC) based on large-scale cohorts and establish a clinically applicable subtyping system for the precision treatment of the disease. METHODS: Eight microarray profiles containing colon samples from 357 patients were utilized. Expression heterogeneity was screened out and stable subtypes were identified among UC patients. Immune infiltration pattern and biological agent response were compared among subtypes to assess the value in guiding treatment. The relationship between PRLR and TNFSF13B genes with the highest predictive value was further validated by functional experiments. RESULTS: Three stable molecular subtypes were successfully identified. Immune cell infiltration analysis defined three subtypes as innate immune activated UC (IIA), whole immune activated UC (WIA), and immune homeostasis like UC (IHL). Notably, the response rate towards biological agents (infliximab/vedolizumab) in WIA patients was the lowest (less than 10%), while the response rate in IHL patients was the highest, ranging from 42 to 60%. Among the featured genes of subtypes, the ratio of PRLR to TNFSF13B could effectively screen for IHL UC subtype suitable for biological agent therapies (Area under curve: 0.961-0.986). Furthermore, we demonstrated that PRLR expressed in epithelial cells could inhibit the expression of TNFSF13B in monocyte-derived macrophages through the CXCL1-NF-κB pathway. CONCLUSIONS: We identified three stable UC subtypes with a heterogeneous immune pattern and different response rates towards biological agents for the first time. We also established a precise molecular subtyping system and classifier to predict clinical drug response and provide individualized treatment strategies for UC patients.

ADAM10 is involved in the oncogenic process and chemo-resistance of triple-negative breast cancer via regulating Notch1 signaling pathway, CD44 and PrPc.

BACKGROUND: Triple-negative breast cancer (TNBC) is the most challenging breast cancer subtype to treat, because it is so aggressive with shorter survival. Chemotherapy remains the standard treatment due to the lack of specific and effective molecular targets. The aim of the present study is to investigate the potential roles of A Disintegrin and Metalloproteinase 10 (ADAM10) on TNBC cells and the effects of combining ADAM10 expression and neoadjuvant chemotherapy treatment (NACT) to improve the overall survival in breast cancer patients. METHODS: Using a series of breast cancer cell lines, we measured the expression of ADAM10 and its substrates by quantitative real-time PCR assay (qRT-PCR) and western blot analysis. Cell migration and invasion, cell proliferation, drug sensitivity assay, cell cycle and apoptosis were conducted in MDA-MB-231 cells cultured with ADAM10 siRNA. The effect of ADAM10 down-regulation by siRNA on its substrates was assessed by western blot analysis. We performed immunohistochemical staining for ADAM10 in clinical breast cancer tissues in 94 patients receiving NACT. RESULTS: The active form of ADAM10 was highly expressed in TNBC cell lines. Knockdown of ADAM10 in MDA-MB-231 cells led to a significant decrease in cell proliferation, migration, invasion and the IC50 value of paclitaxel and adriamycin, while induced cell cycle arrest and apoptosis. And these changes were correlated with down-regulation of Notch signaling, CD44 and cellular prion protein (PrPc). In clinical breast cancer cases, a high ADAM10 expression in pre-NACT samples was strongly associated with poorer response to NACT and shorter overall survival. CONCLUSIONS: These data suggest the previously unrecognized roles of ADAM10 in contributing to the progression and chemo-resistance of TNBC.

MRI-derived radiomics assessing tumor-infiltrating macrophages enable prediction of immune-phenotype, immunotherapy response and survival in glioma.

BACKGROUND: The tumor immune microenvironment can influence the prognosis and treatment response to immunotherapy. We aimed to develop a non-invasive radiomic signature in high-grade glioma (HGG) to predict the absolute density of tumor-associated macrophages (TAMs), the preponderant immune cells in the microenvironment of HGG. We also aimed to evaluate the association between the signature, and tumor immune phenotype as well as response to immunotherapy. METHODS: In this retrospective setting, total of 379 patients with HGG from three independent cohorts were included to construct a radiomic model named Radiomics Immunological Biomarker (RIB) for predicting the absolute density of M2-like TAM using the mRMR feature ranking method and LASSO classifier. Among them, 145 patients from the TCGA microarray cohort were randomly allocated into a training set (N=101) and an internal validation set (N=44), while the immune-phenotype cohort (N=203) and the immunotherapy-treated cohort (N=31, patients from a prospective clinical trial treated with DC vaccine) recruited from Huashan Hospital were used as two external validation sets. The immunotherapy-treated cohort was also used to evaluate the relationship between RIB and immunotherapy response. Radiogenomic analysis was performed to find functional annotations using RNA sequencing data from TAM cells. RESULTS: An 11-feature radiomic model for M2-like TAM was developed and validated in four datasets of HGG patients (area under the curve = 0.849, 0.719, 0.674, and 0.671) using MRI images of post contrast enhanced T1-weighted (T1CE). Patients with high RIB scores had a strong inflammatory response. Four hub-genes (SLC7A7, RNASE6, HLA-DRB1 and CD300A) expressed by TAM were identified to be closely related to the RIB, providing important evidence for biological interpretation. Only individuals with a high RIB score were shown to have survival benefits from DC vaccine [DC vaccine vs. Placebo: median progression-free survival (mPFS), 10.0 mos vs. 4.5 mos, HR=0.17, P=0.0056, 95%CI=0.041-0.68; median overall survival (mOS), 15.0 mos vs. 7.0 mos, HR=0.17, P =0.0076, 95%CI=0.04-0.68]. Multivariate analyses also confirmed that treatment by DC vaccine was an independent factor for improved survival in the high RIB score group. However, in the low RIB score group, DC vaccine was not associated with improved survival. Furthermore, a radiomic nomogram based on the RIB score and clinical factors could efficiently predict the 1-, 2-, and 3-year survival rates, as confirmed by ROC curve analysis (AUC for 1-, 2- and 3-year survival: 0.705, 0.729 and 0.684, respectively). CONCLUSIONS: The radiomic model could allow for non-invasive assessment of the absolute density of TAM from MRI images in HGG patients. Of note, our RIB model is the first immunological radiomic model confirmed to have the ability to predict survival benefits from DC vaccine in gliomas, thereby providing a novel tool to inform treatment decisions and monitor patient treatment course by radiomics.