FGFR3/IGH融合基因t（4;14）探针
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FGFR3/IGH融合基因t（4;14）探针 本试剂盒主要用于FGFR3/IGH融合基因t（4;14）的检测，里面包括即用型杂交液和DAPI复染剂。 本试剂盒仅供科研使用。
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FGFR3/IGH融合基因t(4;14)探针
广州健仑生物科技有限公司
本司长期供应尼古丁（可替宁）检测试剂盒，其主要品牌包括美国NovaBios、广州健仑、广州创仑等进口产品，国产产品，试剂盒的实验方法是胶体金方法。
我司还有很多荧光原位杂交系列检测试剂盒以及各种FISH基因探针和染色体探针等，。
FGFR3/IGH融合基因t(4;14)探针
本试剂盒主要用于AML1/ETO融合基因t(8;21)的检测，里面包括即用型杂交液和DAPI复染剂。
本试剂盒仅供科研使用。
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以下是我司出售的部分FISH产品：
| 6号染色体计数探针（绿色） |
| 8号/20q探针 |
| D13S25（13q14）探针（红色） |
| JAK2（9p24）基因断裂探针 |
| FRS2（12q15）基因探针 |
| p53/RB1/ATM/CSP12/D13S25/6/6q21/IGH基因探针(七探针 ) |
| MYC（8q24），BCL6（3q37），BCL2（18q21）探针 |
| API2/MALT1融合基因t(11;18)探针 |
| MALT1/IGH融合基因t(14;18)探针 |
| IGH融合基因（CCND1,MAF,MAFB,FGFR3）探针 |
| ALK、MET、ROS1基因探针 |
| FGFR1,PDGFRA,PDGFRB基因探针 |
| 7号/8号染色体探针 |
| 8号/17号染色体探针 |
| 8号染色体计数探针（红色） |
| D7S522（7q31）基因探针 |
| RB1(13q14)/ATM(11q22)基因探针 |
FGFR3/IGH融合基因t(4;14)探针
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【公司名称】 广州健仑生物科技有限公司
【】 杨永汉
【】
【腾讯 】
【公司地址】 广州清华科技园创新基地番禺石楼镇创启路63号二期2幢101-3室
【企业文化宣传】FGFR3/IGH融合基因t(4;14)探针
如今在整个生物领域中正被用来研究一个共同的问题：如何研究异质细胞群体中的细胞多样性。这种多样性能够对细胞存活和增殖、对药物疗法和干预作出的反应以及很多其他的生物过程产生深刻影响。大规模单细胞转录组测序可用来研究黑色素瘤组织多样性的复杂细胞微环境。
2研究方法
➀ 通过流式分选了来自于19个患者的4,645细胞进行单细胞转录组测序；每个细胞15万Reads数。
➁ 荧光免疫组化分析。
3研究结果
➀ 单细胞转录谱区分恶性细胞和非恶性细胞的状态
通过CNV分析确定为恶性的细胞，然后根据其基因表达情况进行了TSNE降维分析，恶性细胞分为6个亚型（图1），表明了肿瘤的异质性。而非恶性细胞则相反，主要是通过细胞类型进行了区分，比如T细胞、B细胞、巨噬细胞、内皮细胞、癌相关成纤维细胞（CAFs）和NK细胞。
➁ 恶性细胞的分析揭示了细胞周期的异质性
我们使用G1或S／M期的标志性基因来分析恶性细胞的不同亚群，该分析揭示了在肿瘤组织中，循环的细胞所占的比例平均为13.5%；也区分低循环状态的细胞和高循环状态的细胞，比如Mel79处于低循环、而Mel78则处于高循环状态的肿瘤。KDM5B基因的表达与非循环状态的肿瘤有高度相关性，它在小鼠模型中编码H3K4组蛋白去甲基酶，这个酶与低循环相关，同时也有类似于黑色素瘤干细胞的耐药性的特征。
➂ 非恶性细胞以及他们在黑色素瘤微环境中的相互作用
各种各样的非恶性细胞组成了肿瘤的微环境，微环境的组成对肿瘤的发生和调节有重要影响。通过单细胞测序的数据区分了微环境中不同细胞的类型（图4），包括了T细胞、B细胞、巨噬细胞、内皮细胞和肿瘤相关的成纤维细胞（CAFs），并通过特征标签揭示了这些细胞在微环境中的相对丰富程度。
接下来我们分析细胞在肿瘤微环境中的作用关系，有很多新的发现，比如一群在CAF细胞中特征表达的基因与T细胞的浸润有高度相关性。
大量黑色素瘤细胞之间的数据拆分解揭示了细胞与细胞间的相互作用
➃ 肿瘤浸润性T淋巴细胞的多样性及其功能状态
肿瘤浸润淋巴细胞（TILs），尤其是CD8 + T细胞是免疫监视的主要决定因素。单细胞测序分析来推断各种类型T细胞的功能，从而有助于研究对免疫检查抑制剂的肿瘤反应和抵抗：
通过特征性标记定义了T细胞的主要亚群，比如CD4+,Tregs，CD8+等。然后通过耗竭基因分析了细胞的耗竭状态，并通过免疫组化验证（图5B和5C）。
zui后分析了细胞毒T细胞中耗竭T细胞的特征表达状态，以及高耗竭和低耗竭细胞的基因表达情况，并进行了TCR分析
It is now being used in the whole biological field to study a common problem: how to study the cell diversity in the heterogeneous cell population. This diversity can have a profound impact on cell survival and proliferation, response to drug therapy and intervention, and many other biological processes. The sequencing of a large single cell transcriptome can be used to study the complex cell microenvironment of the diversity of melanoma tissue.
2 research methods
By FACS from single cell transcriptome sequencing in 4645 cells in 19 patients; 150 thousand Reads per cell number.
Analysis of fluorescence immunohistochemistry.
3 research results
Single cell transcriptional profiling to distinguish between malignant and nonmalignant cells state
The malignant cells were identified by CNV analysis, and then TSNE dimension reduction analysis was performed according to their gene expression. The malignant cells were divided into 6 subtypes (Fig. 1), indicating the heterogeneity of tumors. Instead of malignant cells, they are mainly differentiated by cell types, such as T cells, B cells, macrophages, endothelial cells, cancer associated fibroblasts (CAFs) and NK cells.
Analysis of malignant cells revealed the heterogeneity of cell cycle
Marker genes, we use G1 or S / M phase analysis of malignant cells in different subgroup, the analysis revealed in tumor tissue, cell cycle accounted for the proportion of the average of 13.5%; also distinguish between low cycle state and high cell cycle state of cells, such as Mel79 in the low cycle, and Mel78 in the high cycle of tumor. The expression of KDM5B gene is highly correlated with the acyclic tumor. It encodes H3K4 histone demethylation enzyme in mouse model, which is related to low circulation and similar to the drug-resistance of melanoma stem cells.
Non malignant cells and their interactions in melanoma microenvironment.
Various non malignant cells constitute the microenvironment of the tumor, and the composition of the microenvironment has an important influence on the occurrence and regulation of the tumor. The single cell sequencing data to distinguish the different types of cells in the microenvironment (Figure 4), including T cells, B cells, macrophages, endothelial cells and tumor associated fibroblasts (CAFs), and reveals that these cells in the microenvironment of the relative abundance through the feature label.
Next, we analyze the role of cells in tumor microenvironment, and there are many new discoveries. For example, a group of genes expressed in CAF cells are highly correlated with the infiltration of T cells.
Figure 4 the disassembly of a large number of melanoma cells reveals the interaction between cells and cells
Of tumor infiltrating T lymphocytes in the diversity and function of state
Tumor infiltrating lymphocytes (TILs), especially CD8 + T cells, are the main determinants of immune surveillance. Single cell sequencing analysis is used to infer the functions of various types of T cells, thus helping to study the tumor response and resistance to immunoassay inhibitors:
The main subgroups of T cells, such as CD4+, Tregs, CD8+, are defined by characteristic markers. Then the depletion of the cells was analyzed by the exhaustion gene and verified by immunohistochemistry (FIGS. 5B and 5C).
Finally, we analyzed the characteristic expression state of depleted T cells in cytotoxic T cells, and the gene expression of high exhaustion and low depletion cells (map 5D, E, F), and carried out TCR analysis.
