High-Throughput 3D Screening Reveals Differences in Drug Sensitivities between Culture Models of JIMT1 Breast Cancer Cells

The traditional method for studying cancer in vitro is to grow immortalized cancer cells in two-dimensional monolayers on plastic. However, many cellular features are impaired in these artificial conditions, and large changes in gene expression compared to tumors have been reported. Three-dimensional cell culture models have become increasingly popular and are suggested to be better models than two-dimensional monolayers due to improved cell-to-cell contact and structures that resemble in vivo architecture. The aim of this study was to develop a simple high-throughput three-dimensional drug screening method and to compare drug responses in JIMT1 breast cancer cells when grown in two dimensions, in poly(2-hydroxyethyl methacrylate) induced anchorage-independent three-dimensional models, and in Matrigel three-dimensional cell culture models. We screened 102 compounds with multiple concentrations and biological replicates for their effects on cell proliferation. The cells were either treated immediately upon plating, or they were allowed to grow in three-dimensional cultures for 4 days before the drug treatment. Large variations in drug responses were observed between the models indicating that comparisons of culture model-influenced drug sensitivities cannot be made based on the effects of a single drug. However, we show with the 63 most prominent drugs that, in general, JIMT1 cells grown on Matrigel were significantly more sensitive to drugs than cells grown in two-dimensional cultures, while the responses of cells grown in poly(2-hydroxyethyl methacrylate) resembled those of the two-dimensional cultures. Furthermore, comparing the gene expression profiles of the cell culture models to xenograft tumors indicated that cells cultured in Matrigel and as xenografts most closely resembled each other. In this study, we also suggest that three-dimensional cultures can provide a platform for systematic experimentation of larger compound collections in a high-throughput mode and be used as alternatives to traditional two-dimensional screens for better comparability to the in vivo state.     

Loss of annexin A1 expression in human breast cancer detected by multiple high-throughput analyses

To test the efficacy of combined high-throughput analyses (HTA) in target gene identification, screening criteria were set using >fivefold difference by microarray and statistically significant changes (p < 0.01) in SAGE and EST. Microarray analysis of two normal and seven breast cancer samples found 129 genes with >fivefold changes. Further SAGE and EST analyses of these genes identified four qualified genes, ERBB2, GATA3, AGR2, and ANXA1. Their expression pattern was validated by RT-PCR in both breast cell lines and tissue samples. Loss of ANXA1 in breast cancer was further confirmed at mRNA level by Human Breast Cancer Tissue Profiling Array and at protein level by immunohistochemical staining. This study demonstrated that combined HTA effectively narrowed the number of genes for further study, while retaining the sensitivity in identifying biologically important genes such as ERBB2 and ANXA1. A distinctive loss of ANXA1 in breast cancer suggests its involvement in maintaining normal breast biology.     

抑制小鼠乳腺肿瘤转移 microRNA 的筛选

目的：鉴定25种microRNA的功能及其在乳腺癌中发挥的作用,以筛选新的抑制乳腺癌转移的microRNA分子。方法利用脂质体2000将25种鼠源microRNA表达载体转染至4TO7细胞,经G418筛选结合流式细胞仪分选获绿色荧光细胞得稳定表达鼠源microRNA 的细胞株。将细胞2＆#215;105个/只尾静脉注射接种于BALB/C小鼠,14 d后解剖分离肺组织,统计小鼠肺组织结节数目。结果和接种阴性对照细胞小鼠相比,接种mir-449a稳转细胞的小鼠肿瘤肺转移减少。而接种 mir-1935稳转细胞的小鼠肿瘤肺转移增多。其它23种microRNA稳转细胞接种小鼠肿瘤肺转移既不增加也不减少。结论从25种鼠源microRNA中筛选到2种与乳腺癌肿瘤转移相关的microRNA：mir-449a抑制乳腺癌细胞肺转移,mir-1935则促进癌细胞肺转移。     

Network controllability-based algorithm to target personalized driver genes for discovering combinatorial drugs of individual patients

Multiple driver genes in individual patient samples may cause resistance to individual drugs in precision medicine. However, current computational methods have not studied how to fill the gap between personalized driver gene identification and combinatorial drug discovery for individual patients. Here, we developed a novel structural network controllability-based personalized driver genes and combinatorial drug identification algorithm (CPGD), aiming to identify combinatorial drugs for an individual patient by targeting personalized driver genes from network controllability perspective. On two benchmark disease datasets (i.e. breast cancer and lung cancer datasets), performance of CPGD is superior to that of other state-of-the-art driver gene-focus methods in terms of discovery rate among prior-known clinical efficacious combinatorial drugs. Especially on breast cancer dataset, CPGD evaluated synergistic effect of pairwise drug combinations by measuring synergistic effect of their corresponding personalized driver gene modules, which are affected by a given targeting personalized driver gene set of drugs. The results showed that CPGD performs better than existing synergistic combinatorial strategies in identifying clinical efficacious paired combinatorial drugs. Furthermore, CPGD enhanced cancer subtyping by computationally providing personalized side effect signatures for individual patients. In addition, CPGD identified 90 drug combinations candidates from SARS-COV2 dataset as potential drug repurposing candidates for recently spreading COVID-19.     

KIAA1429 regulates cell proliferation by targeting c-Jun messenger RNA directly in gastric cancer

N6-methyladenosine (m6A) modification regulatory proteins are involved in the development of many types of cancer. KIAA1429 serves as a scaffold in bridging the catalytic core components of the m6A methyltransferase complex. The role of KIAA1429 in gastric cancer and its related mechanism has not been reported upon. The expression of KIAA1429 was detected in human gastric cancer tissues and cell lines by quantitative real-time polymerase chain reaction and western blot. The effects of KIAA1429 on gastric cancer proliferation were evaluated by cell counting kit assays, colony formation assays, flow cytometry assay, and in vivo experiments with nude mice. And messenger RNA (mRNA) high-throughput sequencing, RNA immunoprecipitation assay (RIP), luciferase assay, and a rescue experiment were used to identify the relationship between KIAA1429 and its specific targeted gene, c-Jun. We found that KIAA1429 was upregulated in gastric cancer tissues, and expressed lower in adjacent tissues. The upregulated KIAA1429 promoted proliferation and downregulated KIAA1429 was proved to inhibit proliferation of gastric cancer in vitro and in vivo. Then, we identified the potential KIAA1429 regulating gene as c-Jun by mRNAs high-throughput sequencing and RIP assay. By luciferase assay, we verified that KIAA1429 regulated the expression of c-Jun in an m6A-independent manner. Finally, the overexpression of c-Jun rescued the inhibition of proliferation caused by KIAA1429 knockdown in gastric cancer cells. KIAA1429 could act as an oncogene in gastric cancer by stabilizing c-Jun mRNA in an m6A-independent manner. This highlights the functional role for KIAA1429 as a potential prognostic biomarker and therapeutic target in gastric cancer.     

High-throughput screen identifies disulfiram as a potential therapeutic for triple-negative breast cancer cells: Interaction with IQ motif-containing factors

Triple-negative breast cancer (TNBC) represents an aggressive subtype, for which radiation and chemotherapy are the only options. Here we describe the identification of disulfiram, an FDA-approved drug used to treat alcoholism, as well as the related compound thiram, as the most potent growth inhibitors following high-throughput screens of 3185 compounds against multiple TNBC cell lines. The average IC₅₀ for disulfiram was ~300 nM. Drug affinity responsive target stability (DARTS) analysis identified IQ motif-containing factors IQGAP1 and MYH9 as direct binding targets of disulfiram. Indeed, knockdown of these factors reduced, though did not completely abolish, cell growth. Combination treatment with 4 different drugs commonly used to treat TNBC revealed that disulfiram synergizes most effectively with doxorubicin to inhibit cell growth of TNBC cells. Disulfiram and doxorubicin cooperated to induce cell death as well as cellular senescence, and targeted the ESA⁺/CD24^-/low/CD44⁺ cancer stem cell population. Our results suggest that disulfiram may be repurposed to treat TNBC in combination with doxorubicin.     

人胰腺α-淀粉酶抑制剂高通量筛选模型的建立及其应用

【目的】针对人胰腺α-淀粉酶这个糖代谢途径中重要的靶蛋白,建立α-淀粉酶抑制剂高通量筛选模型。【方法】采用毕赤酵母表达系统克隆和表达人胰腺α-淀粉酶;利用酶的催化特性建立α-淀粉酶抑制剂筛选模型;应用该模型对放线菌发酵液冻干物进行高通量筛选;通过构建16S rRNA系统发育树分析阳性菌株的分类地位。【结果】成功克隆、表达了具催化活性的人胰腺α-淀粉酶;建立了α-淀粉酶抑制剂的筛选模型;对近2000株放线菌的发酵液冻干物进行高通量筛选,最终得到14株α-淀粉酶抑制剂产生菌株,且在分类学上具有丰富的菌种多样性。【结论】本研究建立的α-淀粉酶抑制剂高通量筛选模型具有很强的实用价值,可用于新型淀粉酶抑制剂类降糖药物的开发。     

Letrozole-, anastrozole-, and tamoxifen-responsive genes in MCF-7aro cells: a microarray approach

Antiestrogens and aromatase inhibitors are important drugs in the treatment of estrogen-dependent breast cancer. To investigate the effects of these drugs on gene expression in breast cancer cells, we treated estrogen receptor-positive MCF-7 cells stably transfected with the aromatase gene (known as MCF-7aro cells) with testosterone, 17 beta-estradiol, two aromatase inhibitors (letrozole and anastrozole), and an antiestrogen (tamoxifen). We found that testosterone or 17 beta-estradiol induced the proliferation of MCF-7aro cells at a rate six times faster than the untreated cells. In addition, the testosterone-induced proliferation of MCF-7aro cells was effectively suppressed by letrozole, anastrozole, or tamoxifen. Microarray analyses on Affymetrix Human Genome U133A GeneChips (Affymetrix, Santa Clara, CA) were carried out using total RNA isolated from the control and treated cells. At the false discovery rate of 0.05 and a minimum fold-change criteria of 1.5, 104 genes were identified that were up-regulated and 109 genes were identified that were down-regulated by both androgen and estrogen. More than 50% of these hormone-regulated genes were counter-regulated by all three inhibitors and >90% were counter-regulated by at least one of the inhibitors. Comparing the effect of each inhibitor on gene expression, we observed that letrozole and anastrozole are more similar in terms of the genes they affect compared with treatment with tamoxifen. To validate the gene expression profiles identified from microarray analyses, the expression patterns of 13 representative genes were examined by Northern analysis. Finally, the genes identified as statistically significant were classified based on their expression patterns and biological function/pathways. The results of this study provide us with a better understanding of the actions of both aromatase inhibitors and antiestrogens at the molecular level. We believe that the results of this study serve as the first step in identifying unique expression patterns following drug treatment, and that this will ultimately be useful in customizing patient treatment strategies for hormone-dependent breast cancer.     

用传统分离培养法和高通量测序技术分析印度块菌子囊果内细菌的群落结构

块菌是重要的经济真菌, 在其生长发育过程中, 细菌扮演了重要角色。本文利用传统分离培养方法和高通量测序技术分析了印度块菌(Tuber indicum)子囊果内细菌的群落结构。共分离得到细菌532株, 根据物种累积曲线, 选取其中的112株细菌进行了16S rRNA基因序列分析, 共鉴定出4属40种, 其中假单胞菌属(Pseudomonas)菌株占所测菌株数的80%, 不动杆菌属(Acinetobacter)占12.5%, 链霉菌属(Streptomyces)占5%, 贪噬菌属(Variovorax)占2.5%。通过对印度块菌子囊果16S rRNA基因的V1-V3区高通量测序分析, 共获得细菌序列9,862条, 分属于7门43属220种, 其中变形菌门、拟杆菌门和放线菌门的物种占总物种数的99.7%, 是印度块菌子囊果内的优势细菌。黄杆菌属(Flavobacterium)、壤霉菌属(Agromyces)、微杆菌属(Microbacterium)、剑菌属(Ensifer)和寡养食单胞菌属(Stenotrophomonas)的物种数占总物种的86.3%, 是印度块菌子囊果内细菌的优势属。研究结果表明, 采用胰蛋白大豆培养基仅分离得到印度块菌子囊果内少数细菌物种, 而采用高通量测序技术分析发现, 印度块菌子囊果内细菌物种种类丰富, 群落结构复杂。     

Claudin-2 promotes breast cancer liver metastasis by facilitating tumor cell interactions with hepatocytes

We previously identified claudin-2 as a functional mediator of breast cancer liver metastasis. We now confirm that claudin-2 levels are elevated in liver metastases, but not in skin metastases, compared to levels in their matched primary tumors in patients with breast cancer. Moreover, claudin-2 is specifically expressed in liver-metastatic breast cancer cells compared to populations derived from bone or lung metastases. The increased liver tropism exhibited by claudin-2-expressing breast cancer cells requires claudin-2-mediated interactions between breast cancer cells and primary hepatocytes. Furthermore, the reduction of the claudin-2 expression level, either in cancer cells or in primary hepatocytes, diminishes these heterotypic cell-cell interactions. Finally, we demonstrate that the first claudin-2 extracellular loop is essential for mediating tumor cell-hepatocyte interactions and the ability of breast cancer cells to form liver metastases in vivo. Thus, during breast cancer liver metastasis, claudin-2 shifts from acting within tight-junctional complexes to functioning as an adhesion molecule between breast cancer cells and hepatocytes.     

Aromatase and cyclooxygenases: enzymes in breast cancer

Aromatase (estrogen synthase) is the cytochrome P450 enzyme complex that converts C₁₉ androgens to C₁₈ estrogens. Aromatase activity has been demonstrated in breast tissue in vitro, and expression of aromatase is highest in or near breast tumor sites. Thus, local regulation of aromatase by both endogenous factors as well as exogenous medicinal agents will influence the levels of estrogen available for breast cancer growth. The prostaglandin PGE₂ increases intracellular cAMP levels and stimulates estrogen biosynthesis, and previous studies in our laboratories have shown a strong linear association between aromatase (CYP19) expression and expression of the cyclooxygenases (COX-1 and COX-2) in breast cancer specimens. To further investigate the pathways regulating COX and CYP19 gene expression, studies were performed in normal breast stromal cells, in breast cancer cells from patients, and in breast cancer cell lines using selective pharmacological agents. Enhanced COX enzyme levels results in increased production of prostaglandins, such as PGE₂. This prostaglandin increased aromatase activity in breast stromal cells, and studies with selective agonists and antagonists showed that this regulation of signaling pathways occurs through the EP₁ and EP₂ receptor subtypes. COX-2 gene expression was enhanced in breast cancer cell lines by ligands for the various peroxisome proliferator-activated receptors (PPARs), and differential regulation was observed between hormone-dependent and -independent breast cancer cells. Thus, the regulation of both enzymes in breast cancer involves complex paracrine interactions, resulting in significant consequences on the pathogenesis of breast cancer.     

基于受体的药物高通量筛选研究进展

受体是药物筛选的重要靶标,基于受体的药物高通量筛选是药物筛选的主要类型之一。本文根据受体作用原理,按照检测对象的不同,从直接与间接检测的角度,将基于受体的药物高通量筛选进行了分类,总结了基于受体的几种不同的药物筛选模型,并简要介绍了高通量筛选技术在中药研究中的应用,对药物筛选的发展进行了展望。