Mucosal damage is a common side effect of many cancer treatments, especially radiotherapy and intensive chemotherapy, which often induce bone marrow (BM) suppression. We observed that acetic acid- (AA-) induced mucosal damage in the colon of mice was worsened by simultaneous treatment with irradiation or 5-FU. However, irradiation 14 days prior to the AA treatment augmented the recovery from mucosal damage, suggesting that the recovery from BM suppression had an advantageous effect on the mucosal repair. In addition, BM transplantation also augmented the recovery from AA-induced mucosal damage. We further confirmed that transplanted BM-derived cells, particularly F4/80+Gr1+ “inflammatory” monocytes (Subset 1), accumulated in the damaged mucosal area in the early healing phase, and both of Subset 1 and F4/80+Gr1− “resident” monocytes (Subset 2) accumulated in this area in later phases. Our results suggest that monocytes/macrophages contribute to the mucosal recovery and regeneration following mucosal damage by anticancer drug therapy.

We have established a new hematopoietic cell line from a patient with myelodysplastic syndrome (MDS), which was refractory anemia with excess blasts (RAEB). This cell line, designated TER-3, depends on several cytokines for long-term survival and growth, and requires interleukin-3 (IL-3) for continuous growth. Cytochemical analysis revealed that TER-3 cells are weakly dianisidine positive and nonspecific esterase positive, but peroxidase negative. The surface marker profile shows that the TER-3 cells are strongly positive for myeloid, lymphoid, and megakaryocytic antigens such as CD15, CD19, and CD61, and negative for some common multilineage antigens such as CD13, CD33, and CD34. Thus, this cell line has a multilineage phenotype, suggesting that the transformation event occurred in multipotent stem cells. Dianisidine- and nonspecific esterase-positive TER-3 cells increase with granulocyte-colony stimulating factor (G-CSF) rather than with IL-3. These results suggest that the cell line is useful for understanding the mechanism underlying G-CSF-associated hematopoietic cell differentiation and activation in the patient with MDS.

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Immunotherapy is currently recognized as the fourth modality in cancer therapy. CTL can detect cancer cells via complexes involving human leukocyte antigen (HLA) class I molecules and peptides derived from tumor antigens, resulting in antigen-specific cancer rejection. The peptides may be predicted in silico using machine learning-based algorithms. Neopeptides, derived from neoantigens encoded by somatic mutations in cancer cells, are putative immunotherapy targets, as they have high tumor specificity and immunogenicity. Here, we used our pipeline to select 278 neoepitopes with high predictive "SCORE" from the tumor tissues of 46 patients with hepatocellular carcinoma or metastasis of colorectal carcinoma. We validated peptide immunogenicity and specificity by in vivo vaccination with HLA-A2, A24, B35, and B07 transgenic mice using ELISpot assay, in vitro and in vivo killing assays. We statistically evaluated the power of our prediction algorithm and demonstrated the capacity of our pipeline to predict neopeptides (area under the curve = 0.687, P < 0.0001). We also analyzed the potential of long peptides containing the predicted neoepitopes to induce CTLs.Our study indicated that the short peptides predicted using our algorithm may be intrinsically present in tumor cells as cleavage products of long peptides. Thus, we empirically demonstrated that the accuracy and specificity of our prediction tools may be potentially improved in vivo using the HLA transgenic mouse model. Our data will help to design feedback algorithms to improve in silico prediction, potentially allowing researchers to predict peptides for personalized immunotherapy.