Establishing a model composed of immune-related gene-modules to predict tumor immunotherapy response.

At present, tumor immunotherapy has been widely applied to treat various cancers. However, the accuracy of predicting treatment efficacy has not yet achieved a significant breakthrough. This study aimed to construct a prediction model based on the modified WGCNA algorithm to precisely judge the anti-tumor immune response. First, we used a murine colon cancer model to screen corresponding DEGs according to different groups. GSEA was used to analyze the potential mechanisms of the immune-related DEGs (irDEGs) in each group. Subsequently, the intersection of the irDEGs in every group was acquired, and 7 gene-modules were mapped. Finally, 4 gene-modules including cogenes, antiPD-1 immu-genes, chemo immu-genes and comb immu-genes, were selected for subsequent study. Furthermore, a clinical dataset of gastric cancer patients receiving immunotherapy was enrolled, and the irDEGs were identified. A total of 34 vital irDEGs were obtained from the intersections of the vital irDEGs and the four gene-modules. Next, the vital irDEGs were analyzed by the modified WGCNA algorithm, and the correlation coefficients between the 4 gene-modules and the response status to immunotherapy were calculated. Thus, a prediction model based on correlation coefficients was built, and the corresponding model scores were acquired. The AUC calculated according to the model score was 0.727, which was non-inferior to that of the ESTIMATE score and the TIDE score. Meanwhile, the AUC calculated according to the classification of the model scores was 0.705, which was non-inferior to that of the ESTIMATE classification and the TIDE classification. The prediction accuracy of the model was validated in clinical datasets of other cancers.

The miR-146b-3p/TNFAIP2 axis regulates cell differentiation in acute myeloid leukaemia.

Our purpose is to verify that miR-146b-3p targets the downstream transcript TNFAIP2 in order to reveal the machinery underlying the miR-146b-3p/TNFAIP2 axis regulating acute myeloid leukaemia (AML) differentiation. Bioinformatics analyses were performed using multiple databases and R packages. The CD11b+ and CD14+ cell frequencies were detected using flow cytometry and immunofluorescence staining. The TNFAIP2 protein expression was evaluated using western blotting, immunocytochemistry and immunofluorescence staining. The qRT-PCR was conducted to detect the expression of TNFAIP2 and miR-146b-3p. TNFAIP2 and its correlated genes were enriched in multiple cell differentiation pathways. TNFAIP2 was upregulated upon leukaemic cell differentiation. miR-146b-3p directly targeted TNFAIP2, resulting in a decrease in TNFAIP2 expression. Forced expression of TNFAIP2 or knockdown of miR-146b-3p significantly induced the differentiation of MOLM-13 cells. In this study, we demonstrated that TNFAIP2 is a critical driver in inducing differentiation and that the miR-146b-3p/TNFAIP2 axis involves in regulating cell differentiation in AML.

Mechanism of PD-L1 and Siglec-15 in regulating malignant biological behavior of ovarian cancer cells and its clinical significance / 中国肿瘤生物治疗杂志

@#[摘 要] 目的：探讨卵巢癌组织中PD-L1与唾液酸结合性免疫球蛋白样凝集素15（Siglec-15）的关系及其临床意义以及两者对卵巢癌SKOV3细胞增殖、迁移及侵袭的影响。方法：收集2017年1月至2019年12月福建医科大学附属第二医院妇科50例手术切除的卵巢癌组织和配对输卵管组织的石蜡包埋标本，采用免疫组化染色Envision法检测癌组织和输卵管组织中PD-L1和Siglec-15的表达水平，Kaplan-Meier生存曲线和Logistic回归分析PD-L1和Siglec-15表达与患者预后的关系。利用瞬时转染技术在卵巢癌细胞SKOV3中分别转染si-PD-L1和si-NC，用qPCR和WB法检测SKOV3细胞中PD-L1的表达对Siglec-15的影响，用CCK-8及Transwell法验证PD-L1及Siglec-15表达对SKOV3细胞增殖、迁移及侵袭的影响。结果：50例卵巢癌组织中，PD-L1与Siglec-15均呈高表达（50.00%与42.00%）。PD-L1表达与肿瘤病理类型、有无腹水、淋巴结转移、FIGO分期及卵巢癌复发与否具有关联（均P<0.05）；Siglec-15表达与卵巢癌患者淋巴结转移及FIGO分期具有关联（均P<0.05）。成功构建PD-L1低表达SKOV3细胞株，降低PD-L1表达可使Siglec-15表达升高。结论：PD-L1和Siglec-15在卵巢癌组织中均有较高的阳性表达率，PD-L1是卵巢癌复发的独立风险因素。PD-L1和Siglec-15两者的表达呈负相关，降低PD-L1表达可使Siglec-15表达水平升高而抑制SKOV3细胞增殖、迁移和侵袭的能力。

Determination of a DNA repair-related gene signature with potential implications for prognosis and therapeutic response in pancreatic adenocarcinoma.

Background: Pancreatic adenocarcinoma (PAAD) is one of the leading causes of cancer death worldwide. Alterations in DNA repair-related genes (DRGs) are observed in a variety of cancers and have been shown to affect the development and treatment of cancers. The aim of this study was to develop a DRG-related signature for predicting prognosis and therapeutic response in PAAD. Methods: We constructed a DRG signature using least absolute shrinkage and selection operator (LASSO) Cox regression analysis in the TCGA training set. GEO datasets were used as the validation set. A predictive nomogram was constructed based on multivariate Cox regression. Calibration curve and decision curve analysis (DCA) were applied to validate the performance of the nomogram. The CIBERSORT and ssGSEA algorithms were utilized to explore the relationship between the prognostic signature and immune cell infiltration. The pRRophetic algorithm was used to estimate sensitivity to chemotherapeutic agents. The CellMiner database and PAAD cell lines were used to investigate the relationship between DRG expression and therapeutic response. Results: We developed a DRG signature consisting of three DRGs (RECQL, POLQ, and RAD17) that can predict prognosis in PAAD patients. A prognostic nomogram combining the risk score and clinical factors was developed for prognostic prediction. The DCA curve and the calibration curve demonstrated that the nomogram has a higher net benefit than the risk score and TNM staging system. Immune infiltration analysis demonstrated that the risk score was positively correlated with the proportions of activated NK cells and monocytes. Drug sensitivity analysis indicated that the signature has potential predictive value for chemotherapy. Analyses utilizing the CellMiner database showed that RAD17 expression is correlated with oxaliplatin. The dynamic changes in three DRGs in response to oxaliplatin were examined by RT-qPCR, and the results show that RAD17 is upregulated in response to oxaliplatin in PAAD cell lines. Conclusion: We constructed and validated a novel DRG signature for prediction of the prognosis and drug sensitivity of patients with PAAD. Our study provides a theoretical basis for further unraveling the molecular pathogenesis of PAAD and helps clinicians tailor systemic therapies within the framework of individualized treatment.

Evaluating the tumor immune profile based on a three-gene prognostic risk model in HER2 positive breast cancer.

To date, there have not been great breakthroughs in immunotherapy for HER2 positive breast cancer (HPBC). This study aimed to build a risk model that might contribute to predicting prognosis and discriminating the immune landscape in patients with HPBC. We analyzed the tumor immune profile of HPBC patients from the TCGA using the ESTIMATE algorithm. Thirty survival-related differentially expressed genes were selected according to the ImmuneScore and StromalScore. A prognostic risk model consisting of PTGDR, PNOC and CCL23 was established by LASSO analysis, and all patients were classified into the high- and low-risk score groups according to the risk scores. Subsequently, the risk model was proven to be efficient and reliable. Immune related pathways were the dominantly enriched category. ssGSEA showed stronger immune infiltration in the low-risk score group, including the infiltration of TILs, CD8 T cells, NK cells, DCs, and so on. Moreover, we found that the expression of immune checkpoint genes, including PD-L1, CTLA-4, TIGIT, TIM-3 and LAG-3, was significantly upregulated in the low-risk score group. All the results were validated with corresponding data from the GEO database. In summary, our investigation indicated that the risk model composed of PTGDR, PNOC and CCL23 has potential to predict prognosis and evaluate the tumor immune microenvironment in HPBC patients. More importantly, HPBC patients with a low-risk scores are likely to benefit from immune treatment.

Levels of PD‑L1 and CD8+ TIL in TNBC tissues and their clinical significance / 中国肿瘤生物治疗杂志

@#[摘 要] 目的： 探讨程序性死亡蛋白-配体1（programmed death ligand-1，PD-L1）和肿瘤浸润淋巴细胞（tumor-infiltrating lymphocyte, TIL）在三阴性乳腺癌（triple-negative breast cancer，TNBC）组织中的水平及其临床意义。方法：收集2015年1月至2019年1月福建医科大学附属第二医院手术切除的61例TNBC患者的癌及癌旁组织石蜡标本，用免疫组化法检测癌组织中PD-L1表达和CD8+ TIL的水平，用卡方检测方法分析TNBC组织中PD-L1和CD8+ TIL水平与患者临床病理特征及预后的关系。结果： PD-L1和CD8+ TIL在TNBC组织中的阳性率分别为63.9%（39/61）和32.8%（20/61）。PD-L1表达与TNBC患者的肿瘤大小、淋巴结转移、病理分期、复发与否有明显关联（均P<0.05），与患者的年龄、肿瘤分化程度、脉管侵犯以及Ki67表达水平无明显关联（均P>0.05）；CD8+ TIL水平与TNBC患者的肿瘤大小、肿瘤分化程度、淋巴结转移、病理分期、复发与否有明显关联（均P<0.05），与患者的年龄、脉管侵犯以及Ki67表达水平无明显关联（均P>0.05）。PD-L1和CD8+ TIL水平与患者的无进展生存期（PFS）及总生存期（OS）具有显著相关性（均P<0.05），PD-L1+或者缺乏CD8+ TIL与患者更差的PFS及OS相关（均P<0.05）。结论：TNBC组织中存在较高水平的PD-L1和CD8+ TIL，PD-L1阳性表达或缺乏CD8+ TIL与肿瘤侵袭性增加相关，也与患者更差的PFS及OS相关。

YAP regulates ALDH1A1 expression and stem cell property of bladder cancer cells.

BACKGROUND: Yes-associated protein (YAP), a key player of the Hippo pathway, has been identified to have more and more important roles in tumorigenesis and may be an important biomarker for cancer therapy. YAP is important for bladder cancer cell migration, metastasis, and drug resistance; however, its function in bladder cancer stem cells remains unknown. PURPOSE: The aim of this work was to examine the expression and role of YAP in bladder cancer stem cells. MATERIALS AND METHODS: We identified that the expression level of YAP was significantly enriched in bladder cancer stem cells compared to noncancer stem cell population. Moreover, the effect of YAP on stem cell self-renewal was examined in bladder cancer cells by siRNA silencing approach. In addition, we showed that YAP is required for aldehyde dehydrogenase activity in bladder cancer cells. RESULTS: RNAseq analysis and quantitative real-time PCR results showed that silencing of YAP inhibited the expression of ALDH1A1 gene. CONCLUSION: Collectively, our findings for the first time elucidated that YAP serves as a cancer stem cell regulator in bladder cancer, which provided a promising therapy strategy for patients with bladder cancer.