Yijia Wang

BACKGROUND: Evidence has demonstrated conditioned medium (CM) from periodontal ligament stem cells (PDLSCs) improved periodontal regeneration. Gingival mesenchymal stem cells (GMSCs) have been considered an alternative strategy for regenerative medicine. To determine whether GMSC-CM could promote periodontal wound healing, we compared the effects of GMSC-CM and PDLSC-CM on periodontal regeneration and the underlying mechanisms in rat periodontal defects. METHODS: Cell-free CMs were collected from PDLSCs, GMSCs, and gingival fibroblasts (GFs) using ultracentrifugation (100-fold concentration). Periodontal defects were created on the buccal side of the first molar in the left mandible of 90 rats by a surgical method. Collagen membranes loaded with concentrated CMs (α-MEM, GF-CM, GMSC-CM, PDLSC-CM) were transplanted into periodontal defects. After 1, 2, and 4 weeks, the animals were sacrificed and specimens including the first molar and the surrounding tissues were separated and decalcified. Hematoxylin-eosin and Masson's trichrome staining were performed to evaluate periodontal regeneration. Immunohistochemical staining for tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-10 was conducted to analyze inflammation. Immunohistochemistry of BSP-II and Runx2 was performed to analyze osteoblast differentiation. RESULTS: Histological analysis showed the amount of newly formed periodontal tissue was significantly higher in both the GMSC-CM and PDLSC-CM groups than in the other groups, with no significant difference between these two groups. At 1 and 2 weeks, the expression levels of TNF-α and IL-1β were significantly lower in the GMSC-CM and PDLSC-CM groups than in the other three groups, while there was no significant difference between these two groups. IL-10 expression was significantly higher in the GMSC-CM group than in the PDLSC-CM group and the other three groups. At 1, 2, and 4 weeks, BSP-II and Runx2 expressions were significantly higher in the GMSC-CM and PDLSC-CM groups than in the other three groups, with no significant difference between the two groups. CONCLUSIONS: Our results demonstrate that GMSC-CM transplantation can significantly promote periodontal regeneration in rats and achieve the same effect as PDLSC-CM. The mechanism of periodontal regeneration may involve the regulation of inflammatory factors and the promotion of osteogenic differentiation of bone progenitor cells in the wound region by CMs from MSCs.

BACKGROUND: Inflammatory bowel disease caused by microbial dysbiosis is an important factor contributing to colorectal cancer (CRC) initiation. The 'driver-passenger' model in human gut microbial dysbiosis suggests that 'driver' bacteria may colonize with low relative abundance on tumor site but persistently induce chronic change in normal intestinal epithelium and initiate CRC. They are gradually replaced by 'passenger' bacteria later on, due to their low adaptability to the on-tumor site niche. RESULTS: To reveal site-specific bacterial taxon markers in CRC patients, we analyzed the gut mucosal microbiome of 75 paired samples of on-tumor and tumor-adjacent sites, 75 off-tumor sites, and 26 healthy controls. Linear discriminant analysis of relative abundance profiles revealed unique bacterial taxon distribution correlated with specific tumor sites, with Eubacterium having the distribution characteristic of potential driver bacteria. We further show that Eubacterium rectale endotoxin activates the transcription factor NF-κΒ, which regulates multiple aspects of innate and adaptive immune responses in normal colon epithelial cells. Unlike the 'passenger' bacterium Fusobacterium nucleatum, E. rectale promotes dextran sodium sulfate-induced colitis in Balb/c mice. CONCLUSIONS: Our findings reveal that E. rectale functions as a 'driver' bacterium and contributes to cancer initiation via promoting inflammation.

BACKGROUND: Emerging evidence links gut microbiota to various human diseases including colorectal cancer (CRC) initiation and development. However, gut microbiota profiles associated with CRC recurrence and patient prognosis are not completely understood yet, especially in a Chinese cohort. AIM: To investigate the relationship between gut mucosal microbiota profiles and CRC recurrence and patient prognosis. METHODS: We obtained the composition and structure of gut microbiota collected from 75 patients diagnosed with CRC and 26 healthy controls. The patients were followed up by regular examination to determine whether tumors recurred. Triplet-paired samples from on-tumor, adjacent-tumor and off-tumor sites of patients diagnosed with/without CRC recurrence were analyzed to assess spatial-specific patterns of gut mucosal microbiota by 16S ribosomal RNA sequencing. Next, we carried out bioinformatic analyses, Kaplan-Meier survival analyses and Cox regression analyses to determine the relationship between gut mucosal microbiota profiles and CRC recurrence and patient prognosis. RESULTS: . CONCLUSION: Our work suggests that intestinal microbiota can serve as biomarkers to predict the risk of CRC recurrence and patient death.

Introduction: Besides genetic and epigenetic alterations that lead to carcinogenesis and development of colorectal cancer (CRC), intestinal microbiomes are recently recognized to play a critical role in CRC progression. The abundant species associated with human CRC have been proposed for their roles in promoting tumorigenesis. However, a recent “driver-passenger” model suggests that these CRC-associated species with high relative abundances may be passenger bacteria that take advantage of the tumor environment instead of initiating CRC, whereas the driver species that initiate CRC have been replaced by passenger bacteria due to the alteration of the intestinal niche. Methods: Here, to reveal potential driver and passenger bacteria during CRC progression, we compare the gut mucosal microbiomes of 75 triplet-paired CRC samples collected from on-tumor site, adjacent-tumor site, and off-tumor site, and 26 healthy controls. Results: Our analyses revealed potential driver bacteria in four genera and two families, and potential passenger bacteria in 14 genera or families. Bacillus, Bradyrhizobium, Methylobacterium, Streptomyces, Intrasporangiaceae and Sinobacteraceae were predicted to be potential driver bacteria. Moreover, 14 potential passenger bacteria were identified and divided into five groups. Group I passenger bacteria contain Fusobacterium, Campylobacter, Streptococcus, Schwartzia , and Parvimonas . Group II passenger bacteria contain Dethiosulfatibacter, Selenomonas, Peptostreptococus, Leptotrichia . Group III passenger bacteria contain Granulicatella . Group IV passenger bacteria contain Shewanella, Mogibacterium , and Eikenella . Group V passenger bacteria contain Anaerococus . Co-occurrence network analysis reveals a low correlation relationship between driver and passenger bacteria in CRC patients compared with healthy controls. Discussion: These driver and passenger species may serve as bio-marker species for screening cohorts with high risk to initiate CRC or patients with CRC, respectively. Further functional studies will help understand the roles of driver and passenger bacteria in CRC initiation and development. Keywords: colorectal cancer, driver-passenger model, microbiota

Paclitaxel is a widely used chemotherapy drug, but development of resistance leads to treatment failure. Tumor cells that are treated with a sublethal dose of paclitaxel for a long period of time show the epithelial‐mesenchymal transition (EMT) phenotype, which leads to metastasis and resistance. All‐ trans retinoic acid (ATRA) is always used in combination with paclitaxel and can reverse EMT in many types of cancer cells. The ability of ATRA to reverse EMT in chemoresistant cells is still unknown. In the present study, the ability of ATRA to reverse EMT in paclitaxel‐resistant cells was investigated. Three colorectal cancer cell lines, HCT116, LoVo and CT26, were treated with sublethal doses of paclitaxel to create resistant cell lines. Western blotting, immunocytochemistry, and “parachute” dye‐coupling assays showed that ATRA reverses EMT, inhibits nuclear factor kappa B (NF‐κΒ), and upregulates gap junctions in paclitaxel‐resistant cells. Scratch wound‐healing and Transwell assays showed that ATRA decreases the migration and invasion abilities of paclitaxel‐resistant cells. In addition, the CT26 cell line was used in the Balb/c pulmonary metastasis model to show that ATRA reduces metastasis of paclitaxel‐resistant cells in vivo. Given these data, ATRA may reverse EMT by inhibiting NF‐κΒ and upregulating gap junctions in paclitaxel‐resistant cells.