Fecal Microbiota Transplantation Repairs Radiation Enteritis Through Modulating the Gut Microbiota-Mediated Tryptophan Metabolism.

Radiation enteritis is a common complication of abdominal and pelvic radiotherapy. Several previous studies showed that fecal microbiota transplantation (FMT) could alleviate radiation enteritis. In this study, we investigated the efficacy of FMT in alleviating radiation enteritis and explored the mechanisms by multi-omics approaches. Briefly, C57BL/6J mice were subjected to 9 Gy irradiation to the localized abdominal field, and randomized received FMT from healthy donor mice or saline. H&E staining of harvested small intestine showed FMT decreased epithelial injury. Radiation-induced microbiota dysbiosis, characterized by a decrease in beneficial bacteria Lactobacillaceae and Lachnospiraceae, while these bacteria were restored by FMT. Fecal metabolomics analysis revealed that FMT modulated metabolic dysregulation. Two tryptophan pathway metabolites, indole-3-acetaldehyde and N-Acetyl-5-hydroxytryptamine were decreased after irradiation, whereas these metabolites showed a pronounced recovery in mice receiving FMT. Proteomics analysis of small intestine indicated that radiation enteritis triggered immune-inflammatory responses, which were potentially mitigated by FMT. In 21 patients receiving pelvic radiotherapy for cervical cancer, those who developed enteritis (n = 15) had higher abundance in Lachnospiraceae. Moreover, Indole-3-acetaldehyde was reduced after irradiation. These findings provide insights into the therapeutic effects of FMT in radiation enteritis and highlight Lachnospiraceae and the tryptophan metabolite, Indole-3-acetaldehyde may protect against radiation enteritis.

Prognostic value of proliferation markers Ki-67 and PCNA in esophageal squamous cell carcinoma.

BACKGROUND: Ki-67 and proliferating cell nuclear antigen (PCNA) are markers of proliferation used to assess the growth fraction of the cell population. The present study aimed to explore the prognostic value of these proliferative markers in patients with resected esophageal squamous cell cancer (ESCC) in a large cohort. METHODS: A total of 807 patients with ESCC who underwent radical resection were retrospectively reviewed. Ki-67 and PCNA index were examined as the percentage of positively nuclear-stained cells among total number of cancer cells in three high-power fields by a pathologist who was blinded to the patients' history and outcome. Overall survival (OS) and disease-free survival (DFS) were estimated. The Cox regression model was used to evaluate the independent factor. RESULTS: The cut-off value as 60 and 80% for Ki-67 and PCNA were verified, respectively. Higher Ki-67 expression was associated with low differentiation and more lymph node metastasis. Higher PCNA expression was associated with elevated T stage. However, either expression of Ki-67 or PCNA was not correlated with OS and DFS. While in combination of Ki-67 and PCNA analysis, higher expression of these two proliferative markers predicted worse prognosis (median OS, 47 months versus 54 months, P = 0.04). Whatever the combined proliferative marker, differentiation, lymph node metastasis stage and vascular invasion act as factors in univariate survival analysis, but combined Ki-67 and PCNA is not an independent prognostic variable in multivariate analysis (P = 0.10). CONCLUSION: Our results suggest that proliferative markers of Ki-67 and PCNA may correlate with tumor stage but cannot act as independent predictor of prognosis in ESCC patients.

Evaluation of auto-segmentation for brachytherapy of postoperative cervical cancer using deep learning-based workflow.

Objective. The purpose of this study was to evaluate the accuracy of brachytherapy (BT) planning structures derived from Deep learning (DL) based auto-segmentation compared with standard manual delineation for postoperative cervical cancer.Approach. We introduced a convolutional neural networks (CNN) which was developed and presented for auto-segmentation in cervical cancer radiotherapy. The dataset of 60 patients received BT of postoperative cervical cancer was used to train and test this model for delineation of high-risk clinical target volume (HRCTV) and organs at risk (OARs). Dice similarity coefficient (DSC), 95% Hausdorff distance (95%HD), Jaccard coefficient (JC) and dose-volume index (DVI) were used to evaluate the accuracy. The correlation between geometric metrics and dosimetric difference was performed by Spearman's correlation analysis. The radiation oncologists scored the auto-segmented contours by rating the lever of satisfaction (no edits, minor edits, major edits).Main results. The mean DSC values of DL based model were 0.87, 0.94, 0.86, 0.79 and 0.92 for HRCTV, bladder, rectum, sigmoid and small intestine, respectively. The Bland-Altman test obtained dose agreement for HRCTV_D90%, HRCTV_Dmean, bladder_D2cc, sigmoid_D2ccand small intestine_D2cc. Wilcoxon's signed-rank test indicated significant dosimetric differences in bladder_D0.1cc, rectum_D0.1ccand rectum_D2cc(P< 0.05). A strong correlation between HRCTV_D90%with its DSC (R= -0.842,P= 0.002) and JC (R= -0.818,P= 0.004) were found in Spearman's correlation analysis. From the physician review, 80% of HRCTVs and 72.5% of OARs in the test dataset were shown satisfaction (no edits).Significance. The proposed DL based model achieved a satisfied agreement between the auto-segmented and manually defined contours of HRCTV and OARs, although the clinical acceptance of small volume dose of OARs around the target was a concern. DL based auto-segmentation was an essential component in cervical cancer workflow which would generate the accurate contouring.

Evaluation of auto-segmentation for EBRT planning structures using deep learning-based workflow on cervical cancer.

Deep learning (DL) based approach aims to construct a full workflow solution for cervical cancer with external beam radiation therapy (EBRT) and brachytherapy (BT). The purpose of this study was to evaluate the accuracy of EBRT planning structures derived from DL based auto-segmentation compared with standard manual delineation. Auto-segmentation model based on convolutional neural networks (CNN) was developed to delineate clinical target volumes (CTVs) and organs at risk (OARs) in cervical cancer radiotherapy. A total of 300 retrospective patients from multiple cancer centers were used to train and validate the model, and 75 independent cases were selected as testing data. The accuracy of auto-segmented contours were evaluated using geometric and dosimetric metrics including dice similarity coefficient (DSC), 95% hausdorff distance (95%HD), jaccard coefficient (JC) and dose-volume index (DVI). The correlation between geometric metrics and dosimetric difference was performed by Spearman's correlation analysis. The right and left kidney, bladder, right and left femoral head showed superior geometric accuracy (DSC: 0.88-0.93; 95%HD: 1.03 mm-2.96 mm; JC: 0.78-0.88), and the Bland-Altman test obtained dose agreement for these contours (P > 0.05) between manual and DL based methods. Wilcoxon's signed-rank test indicated significant dosimetric differences in CTV, spinal cord and pelvic bone (P < 0.001). A strong correlation between the mean dose of pelvic bone and its 95%HD (R = 0.843, P < 0.001) was found in Spearman's correlation analysis, and the remaining structures showed weak link between dosimetric difference and all of geometric metrics. Our auto-segmentation achieved a satisfied agreement for most EBRT planning structures, although the clinical acceptance of CTV was a concern. DL based auto-segmentation was an essential component in cervical cancer workflow which would generate the accurate contouring.

The landscape of prognostic and immunological role of myosin light chain 9 (MYL9) in human tumors.

INTRODUCTION: Recent studies have shown that myosin light chain 9 (MYL9) plays a vital role in immune infiltration, tumor invasion, and metastasis; however, the prognostic and immunological role of MYL9 has not been reported. The purpose of this study was to explore the potential prognostic and immunological roles of MYL9 in human cancers by public datasets mainly including the cancer genome atlas (TCGA) and Gene expression omnibus. METHODS: The expression pattern and prognostic value of MYL9 were analyzed across multiple public datasets in different cancer. The correlations between MYL9 expression and immune infiltration among multiple cancers were analyzed by using the TIMER2.0. The MYL9-related gene enrichment analysis was implemented by mainly using KEGG and GO datasets. RESULTS: MYL9 was lowly expressed in most cancers, such as breast cancer, lung adenocarcinoma and squamous cell carcinoma, and stomach adenocarcinoma; but it was highly expressed in several cancers, such as cholangiocarcinoma, head and neck squamous cell carcinoma, and liver hepatocellular carcinoma. Furthermore, MYL9 expression was distinctively associated with prognosis in adrenocortical carcinoma, colon adenocarcinoma, brain glioma, lung cancer, ovarian cancer, gastric cancer, breast cancer, blood cancer, and prostate cancer patients. The expressions of MYL9 were significantly associated with the infiltration of cancer-associated fibroblasts, B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, dendritic cell in different tumors as well as immune markers. In addition, we found that the functional mechanisms of MYL9 involved muscle contraction and focal adhesion. CONCLUSION: MYL9 can serve as a prognostic signature in pan-cancer and is associated with immune infiltration. This pan-cancer study is the first to show a relatively comprehensive understanding of the prognostic and immunological roles of MYL9 across different cancers.

The Immune Microenvironment in Brain Metastases of Non-Small Cell Lung Cancer.

Brain metastasis of non-small cell lung cancer is associated with poor survival outcomes and poses rough clinical challenges. At the era of immunotherapy, it is urgent to perform a comprehensive study uncovering the specific immune microenvironment of brain metastases of NSCLC. The immune microenvironment of brain is distinctly different from microenvironments of extracranial lesions. In this review, we summarized the process of brain metastases across the barrier and revealed that brain is not completely immune-privileged. We comprehensively described the specific components of immune microenvironment for brain metastases such as central nervous system-derived antigen-presenting cells, microglia and astrocytes. Besides, the difference of immune microenvironment between brain metastases and primary foci of lung was particularly demonstrated.

Irradiation increases the immunogenicity of lung cancer cells and irradiation-based tumor cell vaccine elicits tumor-specific T cell responses in vivo.

Background: During the past decades, great efforts have been built to develop lung cancer vaccines. Whole tumor cell lysate (TCL) are ideal sources of antigens for cancer vaccine design, which however have limited efficacy due to insufficient immunogenicity. Recently, radiotherapy has been closely related to immunotherapy. Numerous studies have demonstrated the regulatory effect of irradiation (IR) on tumor immune response. Purpose: To explore the immunogenicity modulation effect of IR on lung cancer cells. Methods: RNA-sequence and qPCR assay was used to evaluate the change of tumor antigens expression after repeated X rays radiation on A549 cells. Vaccine based on TCL of irradiated Lewis lung cancer cells (IR-LLC) was established; therapeutic effect of TCL (IR-LLC) was examined in xenografted tumor model of mice. Flow cytometry was conducted to evaluate the rate of immune cells in spleen; ELISA was used to detect the level of cytokines in plasma. Immunohistochemistry was performed to evaluate the infiltrations of T-cell in tumor tissues; TIMER analysis was used to explore the correlations between tumor antigen expressions and the abundances of immune infiltrates. Results: IR upregulated the expression of tumor antigens in A549 cells. Compared to the control group and unirradiated tumor cell vaccine, TCL(IR-LLC) had a significantly stronger anti-tumor effect in mice bearing with LLC xenografts. TCL(IR-LLC) significantly increased matured DCs and total CD4+ T cells but downregulated Tregs and PD-1+ CD8+ T cells in mice spleen; TCL(IR-LLC) vaccine upregulated the level of IFN-γ and IL-4 while decreased IL-10 in serum; increased infiltrations of CD4+ T-cells and CD8+ T-cells were observed in the tumor issues of mice immunized with TCL(IR-LLC). Tumor antigens including FN1, MFGE8, MMP2, MYL9 may contribute to the enhanced T-cell response. Conclusion: This study confirmed the immunogenicity modulation effect of IR in NSCLC cells, indicating IR might be an effective strategy to enhance the anti-tumor immunity of cancer cell vaccine.

[6]-Gingerol enhances the cisplatin sensitivity of gastric cancer cells through inhibition of proliferation and invasion via PI3K/AKT signaling pathway.

Cisplatin-based chemotherapy is a widely used chemotherapeutic regimen for gastric cancer; however, drug resistance limits its efficacy. [6]-Gingerol has been found to exhibit anticancer effects. Here, we aim to explore the potential of [6]-gingerol in combination with cisplatin as a new regimen for gastric cancer. CCK-8 assay and colony formation assay were used to determine the effect of [6]-gingerol in combination with cisplatin on cell viability of gastric cancer cells. Flow cytometry was performed to assess cell cycle distribution. Wound-healing assay and transwell invasion assay were conducted to examine the migration and invasion abilities. Cell cycle and invasion-related proteins and mRNAs, as well as PI3K/AKT signaling proteins, were assessed by western blotting and quantitative real-time polymerase chain reaction. Combination of [6]-gingerol with cisplatin inhibited cell viability and enhanced cell cycle arrest at G1 phase compared with cisplatin alone. The combination treatment inhibited cell migration and invasion ability and decreased cyclin D1, cyclin A2, matrix metalloproteinase-9, p-PI3K, AKT, and p-AKT protein expressions and increased P21 and P27 mRNA levels. Our study demonstrates that [6]-gingerol enhances the cisplatin sensitivity of gastric cancer cells and that the mechanisms involve G1 phase arrest, migration and invasion suppression via PI3K/AKT signaling pathway.

[6]-Gingerol enhances the radiosensitivity of gastric cancer via G2/M phase arrest and apoptosis induction.

Ionizing radiation (IR) is the main modality for locoregional control of unresectable gastric cancer (GC). [6]-Gingerol is an active major phenolic compound isolated from ginger (Zingiber officinale Roscoe), and it has been demonstrated to possess antitumor activity in previous studies. In the present study, we aimed to evaluate the potential activity of [6]-gingerol as a radiosensitizer and to further explore the underlying mechanism. A CCK-8 assay revealed that [6]-gingerol inhibited the cell viability of HGC-27 cells in a dose-dependent manner (P<0.05). Colony formation assay indicated that pretreatment of [6]-gingerol prior to IR decreased the clonogenic survival of HGC-27 cells. Notably, the combination of [6]-gingerol with IR enhanced IR-induced cell cycle arrest at the G2/M phase compared with IR alone (41.3% in IR alone vs. 53.5% in [6]-gingerol+IR; P=0.006), and increased IR-induced apoptosis compared with IR alone (9.6% in IR alone group vs. 15.1% in [6]-gingerol+IR; P=0.07). DAPI staining detected the apoptotic nuclear morphological changes in the cells treated with [6]-gingerol and/or IR. Furthermore, western blotting and qRT-PCR revealed that [6]-gingerol pretreatment following IR downregulated the protein expression of cyclin B1, cyclin A2, CDC2 and cyclin D1, upregulated the mRNA expression of p27, and induced active caspase-9, active caspase-3 and cytochrome c. In conclusion, the present study demonstrated that [6]-gingerol enhanced radiosensitivity of GC cells, and that the mechanisms involved at least G2/M phase arrest and apoptosis induction.