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Background: Myeloid Sarcoma with monocytic differentiation is rare and quite likely is missed by surgical pathologists. However it is frequently misdiagnosed because of its non-specific imaging and histological pattern. Case presentation: We report the case of a 64-year-old woman with gastric primary myeloid sarcoma with monocytic differentiatio. Upper endoscopy revealed a neoplastic growth at the junction of the lesser curvature and gastric antrum. Except for a slightly increased peripheral monocyte count, no abnormalities were found on hematological and bone-marrow examination. Gastroscopic biopsy showed poorly differentiated atypical large cells with visible nucleoli and nuclear fission. Immunohistochemistry showed positive CD34, CD4, CD43, and CD56 expression, and weakly positive lysozyme expression. Immune markers for poorly differentiated adenocarcinoma, malignant melanoma, and lymphohematopoietic-system tumors were negative. The final diagnosis was myeloid sarcoma with monocytic differentiation. Chemotherapy did not shrink the tumor, so, radical surgery was performed. Although the tumor morphology did not change postoperatively, the immunophenotype did. CD68 and lysozyme expression (tumor tissue markers) changed from negative and weakly positive to strongly positive, AE1/3 expression (epithelial marker) changed from negative to positive, and CD34, CD4, CD43, and CD56 expression (common in naive hematopoietic cell-derived tumors) was greatly attenuated. Exome sequencing revealed missense mutations in FLT3 and PTPRB, which are associated with myeloid sarcoma, and in TP53, CD44, CD19, LTK, NOTCH2, and CNTN2, which are associated with lymphohematopoietic tumors and poorly differentiated cancers. Conclusion: We diagnosed myeloid sarcoma with monocytic differentiation after excluding poorly differentiated adenocarcinoma, common lymphohematopoietic-system tumors, epithelioid sarcoma, and malignant melanoma. We identified that the immunophenotypic of patient had alterations after chemotherapy, and FLT3 gene mutations. We hope that the above results will improve our understanding of this rare tumor. Highlights: 1. We used exome sequencing to detect and report the genetic changes in a case of extramedullary gastric primary myeloid sarcom with monocytic differentiationa. 2. Immunophenotypic alteration of tumor cells occurred after chemotherapy, suggesting that chemotherapy drugs induced tumor differentiation. [ABSTRACT FROM AUTHOR]

Reference 1 Li X, Zhang H, Cui Y. Exome sequencing analysis of gastric primary myeloid sarcoma with monocytic differentiation with altered immunophenotype after chemotherapy: case report. Xiang Li, Hongxia Zhang and Yong Cui contributed equally to this work and should be considered co-first authors. [Extracted from the article]

Aim: To explore the association between the determinant factors including HLA-DQB1*03, DRB1-*07, -*13 and high-risk HPV infection, the cervical squamous cell carcinoma (CSCC) pathogenesis among Chinese Uighur and Han population.Materials& Methods: HLA alleles were genotyped by PCR sequence-specific primers.Results: HPV16 infection rate was significantly higher among the Uighurs and Hans with CSCC as compared with healthy controls, respectively. HLA-DQB1*03 significantly increased among Uighurs with CSCC, while HLA-DRB1*07 significantly increased among Hans with CSCC. Similar tendencies were observed for DQB1*03 with HPV16-positive Uighurs CSCC and DRB1*07 with HPV16-positive Hans CSCC.Conclusion: This study suggests that HLA-DQB1*03 and DRB1*07 alleles may influence the immune response to HPV16 infection and increase the risk of CSCC among the Uighurs and Hans in China. [ABSTRACT FROM AUTHOR]

Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine learning method for predicting protein functional families from protein sequences irrespective of similarity, which complemented those similarity-based and other methods in predicting diverse classes of proteins including the distantly-related proteins and homologous proteins of different functions. Since its publication in 2003, we made major improvements to SVM-Prot with (1) expanded coverage from 54 to 192 functional families, (2) more diverse protein descriptors protein representation, (3) improved predictive performances due to the use of more enriched training datasets and more variety of protein descriptors, (4) newly integrated BLAST analysis option for assessing proteins in the SVM-Prot predicted functional families that were similar in sequence to a query protein, and (5) newly added batch submission option for supporting the classification of multiple proteins. Moreover, 2 more machine learning approaches, K nearest neighbor and probabilistic neural networks, were added for facilitating collective assessment of protein functions by multiple methods. SVM-Prot can be accessed at . [ABSTRACT FROM AUTHOR]