FGFR3/IGH融合基因t(4;14)探針
【簡單介紹】
品牌 | 其他品牌 | 供貨周期 | 現貨 |
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本試劑盒主要用于FGFR3/IGH融合基因t(4;14)的檢測,里面包括即用型雜交液和DAPI復染劑。
本試劑盒僅供科研使用。
【詳細說明】
FGFR3/IGH融合基因t(4;14)探針
廣州健侖生物科技?有限公司
本司長期供應尼古?。商鎸帲z測試劑盒,其主要品牌包括美國NovaBios、廣州健侖、廣州創(chuàng)侖等進口產品,國產產品,試劑盒的實驗方法是膠體金方法。
我司還有很多熒光原位雜交系列檢測試劑盒以及各種FISH基因探針和染色體探針等,。
FGFR3/IGH融合基因t(4;14)探針
本試劑盒主要用于AML1/ETO融合基因t(8;21)的檢測,里面包括即用型雜交液和DAPI復染劑。
本試劑盒僅供科研使用。
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以下是我司出售的部分FISH產品:
6號染色體計數探針(綠色) |
8號/20q探針 |
D13S25(13q14)探針(紅色) |
JAK2(9p24)基因斷裂探針 |
FRS2(12q15)基因探針 |
p53/RB1/ATM/CSP12/D13S25/6/6q21/IGH基因探針(七探針 ) |
MYC(8q24),BCL6(3q37),BCL2(18q21)探針 |
API2/MALT1融合基因t(11;18)探針 |
MALT1/IGH融合基因t(14;18)探針 |
IGH融合基因(CCND1,MAF,MAFB,FGFR3)探針 |
ALK、MET、ROS1基因探針 |
FGFR1,PDGFRA,PDGFRB基因探針 |
7號/8號染色體探針 |
8號/17號染色體探針 |
8號染色體計數探針(紅色) |
D7S522(7q31)基因探針 |
RB1(13q14)/ATM(11q22)基因探針 |
FGFR3/IGH融合基因t(4;14)探針
二維碼掃一掃
【公司名稱】 廣州健侖生物科技有限公司
【】 楊永漢
【】
【騰訊 】
【公司地址】 廣州清華科技園創(chuàng)新基地番禺石樓鎮(zhèn)創(chuàng)啟路63號二期2幢101-3室
【企業(yè)文化宣傳】FGFR3/IGH融合基因t(4;14)探針
如今在整個生物領域中正被用來研究一個共同的問題:如何研究異質細胞群體中的細胞多樣性。這種多樣性能夠對細胞存活和增殖、對藥物療法和干預作出的反應以及很多其他的生物過程產生深刻影響。大規(guī)模單細胞轉錄組測序可用來研究黑色素瘤組織多樣性的復雜細胞微環(huán)境。
2研究方法
? 通過流式分選了來自于19個患者的4,645細胞進行單細胞轉錄組測序;每個細胞15萬Reads數。
? 熒光免疫組化分析。
3研究結果
? 單細胞轉錄譜區(qū)分惡性細胞和非惡性細胞的狀態(tài)
通過CNV分析確定為惡性的細胞,然后根據其基因表達情況進行了TSNE降維分析,惡性細胞分為6個亞型(圖1),表明了腫瘤的異質性。而非惡性細胞則相反,主要是通過細胞類型進行了區(qū)分,比如T細胞、B細胞、巨噬細胞、內皮細胞、癌相關成纖維細胞(CAFs)和NK細胞。
? 惡性細胞的分析揭示了細胞周期的異質性
我們使用G1或S/M期的標志性基因來分析惡性細胞的不同亞群,該分析揭示了在腫瘤組織中,循環(huán)的細胞所占的比例平均為13.5%;也區(qū)分低循環(huán)狀態(tài)的細胞和高循環(huán)狀態(tài)的細胞,比如Mel79處于低循環(huán)、而Mel78則處于高循環(huán)狀態(tài)的腫瘤。KDM5B基因的表達與非循環(huán)狀態(tài)的腫瘤有高度相關性,它在小鼠模型中編碼H3K4組蛋白去甲基酶,這個酶與低循環(huán)相關,同時也有類似于黑色素瘤干細胞的耐藥性的特征。
? 非惡性細胞以及他們在黑色素瘤微環(huán)境中的相互作用
各種各樣的非惡性細胞組成了腫瘤的微環(huán)境,微環(huán)境的組成對腫瘤的發(fā)生和調節(jié)有重要影響。通過單細胞測序的數據區(qū)分了微環(huán)境中不同細胞的類型(圖4),包括了T細胞、B細胞、巨噬細胞、內皮細胞和腫瘤相關的成纖維細胞(CAFs),并通過特征標簽揭示了這些細胞在微環(huán)境中的相對豐富程度。
接下來我們分析細胞在腫瘤微環(huán)境中的作用關系,有很多新的發(fā)現,比如一群在CAF細胞中特征表達的基因與T細胞的浸潤有高度相關性。
大量黑色素瘤細胞之間的數據拆分解揭示了細胞與細胞間的相互作用
? 腫瘤浸潤性T淋巴細胞的多樣性及其功能狀態(tài)
腫瘤浸潤淋巴細胞(TILs),尤其是CD8 + T細胞是免疫監(jiān)視的主要決定因素。單細胞測序分析來推斷各種類型T細胞的功能,從而有助于研究對免疫檢查抑制劑的腫瘤反應和抵抗:
通過特征性標記定義了T細胞的主要亞群,比如CD4+,Tregs,CD8+等。然后通過耗竭基因分析了細胞的耗竭狀態(tài),并通過免疫組化驗證(圖5B和5C)。
zui后分析了細胞毒T細胞中耗竭T細胞的特征表達狀態(tài),以及高耗竭和低耗竭細胞的基因表達情況,并進行了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.
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