SUMMARY Development of cancer has been linked to chronic inflammation, particularly via interleukin-23 (IL-23) and IL-17 signaling pathways. However, the cellular source of IL-17 and underlying mechanisms by which IL-17-producing cells promote human colorectal cancer (CRC) remain poorly defined. Here, we demonstrate that innate γδT (γδT17) cells are the major cellular source of IL-17 in human CRC. Microbial products elicited by tumorous epithelial barrier disruption correlated with inflammatory dendritic cell (inf-DC) accumulation and γδT17 polarization in human tumors. Activated inf-DCs induced γδT17 cells to secrete IL-8, tumor necrosis factor alpha, and GM-CSF with a concomitant accumulation of immunosuppressive PMN-MDSCs in the tumor. Importantly, γδT17 cell infiltration positively correlated with tumor stages and other clinicopathological features. Our study uncovers an inf-DC-γδT17-PMN-MDSC regulatory axis in human CRC that correlates MDSC-meditated immunosuppression with tumor-elicited inflammation. These findings suggest that γδT17 cells might be key players in human CRC progression and have the potential for treatment or prognosis prediction.

BackgroundNumerous agents targeting PD-L1/PD-1 check-point are in clinical development. However, the correlation between PD-L1expression and prognosis of solid tumor is still in controversial. Here, we elicit a systematic review and meta-analysis to investigate the potential value of PD-L1 in the prognostic prediction in human solid tumors.MethodsElectronic databases were searched for studies evaluating the expression of PD-L1 and overall survival (OS) of patients with solid tumors. Odds ratios (ORs) from individual studies were calculated and pooled by using a random-effect model, and heterogeneity and publication bias analyses were also performed.ResultsA total of 3107 patients with solid tumor from 28 published studies were included in the meta-analysis. The median percentage of solid tumors with PD-L1 overexpression was 52.5%. PD-L1 overexpression was associated with worse OS at both 3 years (OR = 2.43, 95% confidence interval (CI) = 1.60 to 3.70, P < 0.0001) and 5 years (OR = 2.23, 95% CI = 1.40 to 3.55, P = 0.0008) of solid tumors. Among the tumor types, PD-L1 was associated with worse 3 year-OS of esophageal cancer, gastric cancer, hepatocellular carcinoma, and urothelial cancer, and 5 year-OS of esophageal cancer, gastric cancer and colorectal cancer.ConclusionsThese results suggest that expression of PD-L1 is associated with worse survival in solid tumors. However, the correlations between PD-L1 and prognosis are variant among different tumor types. More studies are needed to investigate the clinical value of PD-L1 expression in prognostic prediction and treatment option.

Despite recent progresses in tumor therapy and increased knowledge in tumor biology, tumor remains a common and lethal disease worldwide. Cancer stem cells (CSCs) are a subset of cancer cells with a stem cell-like ability, which may drive tumor growth and recurrence and are resistant to many current anticancer treatments. Solid tumors are regarded as "organs" which are comprised of cancer cells and the tumor stroma. The tumor microenvironment makes up the stroma of the tumor, which occupies the majority of the tumor mass, including the extracellular matrix (ECM), mesenchymal stem cells (MSCs), endothelial cells, immune cells, and, what is more, networks of cytokines and growth factors. The microenvironment or niche surrounding CSCs largely governs their cellular fate. Recent work has revealed that the microenvironment supports CSC self-renewal and simultaneously serves as a physical barrier to drug delivery. The tumor microenvironment plays pivotal roles in each stage of tumor development. Knowledge about the interactions of CSCs with their microenvironment would seem to be of most importance for developing new treatment strategies.

Deciphering chemical mechanism of action (MoA) enables the development of novel therapeutics (e.g. drug repositioning) and evaluation of drug side effects. Development of novel computational methods for chemical MoA assessment under a systems pharmacology framework would accelerate drug discovery and development with greater efficiency and low cost. EXPERIMENTAL APPROACHIn this study, we proposed an improved network-based inference method, balanced substructure-drug-target network-based inference (bSDTNBI), to predict MoA for old drugs, clinically failed drugs and new chemical entities. Specifically, three parameters were introduced into network-based resource diffusion processes to adjust the initial resource allocation of different node types, the weighted values of different edge types and the influence of hub nodes. The performance of the method was systematically validated by benchmark datasets and bioassays. KEY RESULTSHigh performance was yielded for bSDTNBI in both 10-fold and leave-one-out cross validations. A global drug-target network was built to explore MoA of anticancer drugs and repurpose old drugs for 15 cancer types/subtypes. In a case study, 27 predicted candidates among 56 commercially available compounds were experimentally validated to have binding affinities on oestrogen receptor α with IC 50 or EC 50 values ≤10 μM. Furthermore, two dual ligands with both agonistic and antagonistic activities ≤1 μM would provide potential lead compounds for the development of novel targeted therapy in breast cancer or osteoporosis. CONCLUSION AND IMPLICATIONSIn summary, bSDTNBI would provide a powerful tool for the MoA assessment on both old drugs and novel compounds in drug discovery and development.Abbreviations bSDTNBI, balanced substructure-drug-target network-based inference; DTI, drug-target interaction; e P , precision enhancement; e R , recall enhancement; ERα, oestrogen receptor α; E2, estradiol; MoA, mechanism of action; NBI, network-based inference; P, precision; R, recall; ROC, receiver operating characteristic

BackgroundIL–10 is an important immunosuppressive cytokine which is frequently elevated in tumor microenvironment. Some studies have reported that overexpression of serous IL–10 is correlated with worse outcome in patients with malignant tumor. Here, we conducted a meta-analysis to assess the prognostic impact of serous IL–10 expression in cancer patients.MethodsWe searched PubMed and EBSCO for studies in evaluating the association of IL–10 expression—in serum and clinical outcome in cancer patients. Overall survival (OS) was the primary prognostic indicator and disease-free survival (DFS) was the secondary indicator. Extracted data were computed into odds ratios (ORs) and 95% confidence interval (CI) or a P value for survival at 1, 3 and 5 years. Pooled data were weighted using the Mantel–Haenszel Fixed-effect model. All statistical tests were two-sided.ResultsA total of 1788 patients with cancer from 21 published studies were incorporated into this meta-analysis. High level of serum IL–10 was significantly associated with worse OS at 1-year (OR = 3.70, 95% CI = 2.81 to 4.87, P < 0.00001), 3-year (OR = 3.33, 95% CI = 2.53 to 4.39, P < 0.0001) and 5-year (OR = 2.80, 95% CI = 1.90 to 4.10, P < 0.0001) of cancer. Subgroup analysis showed that the correlation between serous IL–10 expression and outcome of patients with solid tumors and hematological malignancies are consistent. The association of IL–10 with worse DFS at 1-year (OR = 3.34, 95% CI = 1.40 to 7.94, P = 0.006) and 2-year (OR = 3.91, 95% CI = 1.79 to 8.53, P = 0.0006) was also identified.ConclusionsHigh expression of serous IL–10 leads to an adverse survival in most types of cancer. IL–10 is a valuable biomarker for prognostic prediction and targeting IL–10 treatment options for both solid tumors and hematological malignancies.