结合生物信息学及生物学实验筛选并鉴定前列腺癌转移抑制基因的研究
摘要
背景与目的：
在美国,前列腺癌是最常见的非皮肤恶性肿瘤,占所有恶性肿瘤的29%,且是肿瘤导致死亡的第二位。2012年,大约有241,740男性诊断为前列腺癌,28,170男性死于前列腺癌。多数肿瘤相关的死亡和几乎所有的前列腺癌引起的死亡均与转移而非原位肿瘤负荷有关。因此,减少前列腺癌的病死率依赖于揭示肿瘤转移的生物学机制如发现参与肿瘤转移过程的基因等,从而制定相应的临床预防策略。有大量的研究表明存在着一批可以抑制或促进肿瘤转移的基因,被称为肿瘤转移调节基因。它们可以大体分为转移促进基因和转移抑制基因。转移促进基因促进肿瘤细胞从无转移性到具有转移性的转变。转移抑制基因可以单纯抑制肿瘤的转移而不影响原位肿瘤的生长。
要发现候选前列腺癌转移调节基因最直接的方法是在对应着不良预后的前列腺癌样本中,通过对转录信息的分析找到一组差异表达基因(基因标记)。但是单个研究常常缺乏统计学信度、信息不全、低质量等缺点。这些缺陷可以通过综合相关的不同的独立研究进行荟萃分析以增加样本,减少错误得以克服。目前,用来行荟萃分析的已公开发表的具有临床生存率数据的前列腺癌基因表达信息尚有限。因此,我们课题组转而利用已公开发表的丰富的乳腺癌基因表达及临床资料信息进行了荟萃分析。
该分析利用一个新的以数据相似性基础的方法对223个研究数据集,包含10,581名乳腺癌患者的数据进行了相似性整合。即将每个单个研究的数据集根据数据相似性分类后,整合成为大的具有可重复性、同一性的数据,从而发现新的更为准确的基因标记。然后利用21个新的包含6,011名乳腺癌患者及1,110名肺癌、前列腺癌等其它恶性肿瘤患者的研究数据集,对我们所发现的新的基因标记进行验证。验证标准为该新的基因标记对癌症患者生存率的预测准确性。在该荟萃分析中,根据数据相似性,633个肿瘤标记被整合成了121个肿瘤标记。从该121个肿瘤标记中,我们发现了11个代表了高度恶性肿瘤行为的标记,并从中筛选了50个相关基因,命名为BRmet50。经过验证,BRmet50是一个良好的肿瘤基因标记,能够较以往的肿瘤基因标记更为准确的预测乳腺癌患者的预后,且与肿瘤患者的常用的临床和病理参数相独立。另外,该基因标记不仅仅局限于对乳腺癌患者预后的准确预测性,对前列腺癌、肺癌患者的预后亦能准确预测。BRmet50中含有11个候选肿瘤转移抑制基因,39个候选肿瘤转移促进基因,本研究拟利用生物信息学方法对其中的11个候选肿瘤转移抑制基因进行筛选,并结合生物学实验对目标候选基因在前列腺癌中的生物学行为进行鉴定,以期发现新的前列腺癌转移抑制基因。
材料和方法：
1.候选前列腺癌转移抑制基因的筛选
1.1验证BRMet50这个新的基因标记对前列腺癌预后的预测准确性
我们选取已发表的3个数据集,共有957例前列腺癌患者,这些患者具有几种不同的前列腺癌预后转归结果(复发,远处转移或死亡),这三个预后结果被分别用来作为临床终点进行生存分析。分析的结果用来验证BRMet50这个新的基因标记预测前列腺癌患者预后的准确性；
1.2筛选最具肿瘤转移抑制基因特点的候选基因
在BRMet50中含有50个基因。其中有11个基因表达下调,这11个基因是候选肿瘤转移抑制基因。我们选取了10个已发表的关于正常或患病前列腺组织的基因表达数据进行研究。在每个研究数据中,我们对11个候选基因在前列腺癌患者实验组和对照组之间的差异表达进行了分析(增高或下降)。然后选取在这些数据中差异表达情况最为一致的基因。
1.3选取1.2中差异表达情况最为一致的的候选基因,对其在前列腺癌正常组织、前列腺癌组织及前列腺癌各细胞系中的表达情况进行了观察,以初步验证其表达谱是否符合前列腺癌转移抑制基因特征,如符合则对其进一步重点研究,以期鉴定其为前列腺癌转移抑制基因。
2.候选前列腺癌转移抑制基因的鉴定
2.1选取合适的带有生物荧光标记的前列腺癌细胞系；
2.2确定候选基因过表达载体,建立稳定的过度表达候选基因的前列腺癌细胞系；我们选取逆转录病毒载体,该载体能携带目的基因与宿主细胞基因组重组,从而达到稳定表达的目的。
2.3标准体外实验研究候选基因表达对前列腺癌细胞系PC3及ARCaPM的细胞增殖、迁移及侵袭性的影响(每种实验至少重复3次)：
2.3.1细胞增殖实验
2.3.2软琼脂集落形成实验
2.3.3细胞伤口愈合实验
2.3.4Transwell小室迁移实验
2.3.5Transwell侵袭实验
2.4动物模型体内实验研究候选基因对前列腺癌细胞系PC3在实验动物体内生长、转移的影响(每个转移模型实验至少重复2次)：
重度免疫缺陷小鼠(SCID小鼠)随机分为两组,分别注射两种细胞PC3-luc/EV(空对照)和PC3-luc/候选基因(候选基因过表达细胞系)。所注射PC3细胞系中含有萤火虫荧光素酶(Luciferase)标记。然后应用活体成像系统(IVIS-200)定期对小鼠体内肿瘤生长情况进行测定,并应用软件对每只小鼠全身荷瘤量进行计算。小鼠接近死亡时,处理小鼠,对各解剖器官(软组织器官和骨等)进行荧光检测,统计转移率,并对两组小鼠的生存曲线进行分析。
2.4.1原位异种移植小鼠前列腺癌原位转移模型(Orthotopic,OX模型)
10周龄SCID小鼠随机分为两组(5只实验组小鼠,5只对照组小鼠)：PC3-luc/EV注射组和PC3-luc/候选基因注射组。通过一个下腹正中手术切口,显微镜下将PC3-luc/EV或PC3-luc/候选基因细胞(3x105,30ul)混合胶原凝胶种植于前列腺前叶。其中PC3细胞的悬液随着胶原蛋白的凝固而成为了半固体,可以大大减少腹腔种植几率。然后,我们将前列腺前叶的切口关闭,让固体凝胶块留在前叶里面的管腔内。
2.4.2心脏注射小鼠前列腺癌全身转移模型(Intra-Cardiac,IC模型)
将6-8周龄SCID雄性小鼠随机分为两组(5只实验组小鼠,5只对照组小鼠)。将PC3-luc/EV或PC3-luc/候选基因细胞(5×105),重新悬浮于100ul PBS中,并缓慢注入小鼠心脏左心室内。
结果：
1.前列腺癌转移抑制候选基因筛选结果：
1.1基因标记BRmet50准确的预测了被检测的3个前列腺癌数据集中前列腺癌患者的预后结果(P<0.001)。
1.2基因SPARC like1(SPARCL1)在10个数据集实验组和对照组中的表达显示了最为一致的表现。SPARCL1被发现在正常前列腺组织或良性的前列组织中上调表达,而在前列腺癌组织,高级别前列腺癌(T3B),高Gleason评分(GS>7)前列腺癌肿瘤,雄激素非依赖性(AI)状态或转移性前列腺癌中下调表达。
1.3蛋白SPARCL1表达水平在前列腺癌组织中对比良性前列腺组织明显下调。在代表前列腺癌的恶性细胞系如LNCaP、ARCaPM、PC3中的表达检测不到。与此相反,在代表正常的良性前列腺组织的细胞系中(NHPrE1)高表达。
2.前列腺癌转移候选基因鉴定结果：
实验细胞系准备及候选基因过表达结果：
2.1由美国密歇根大学医学院K. Pienta博士所赠的PC3-Luc细胞带有萤火虫荧光素酶(Luciferase)标记,能够与底物luciferin相互作用发出生物荧光被探测到。
2.2我们应用pBMN-I-GFP逆转录病毒转染载体,成功构建pBMN-I-SPARCL1-GFP载体,并成功将SPARCL1基因开放读码框片段与宿主细胞PC3-Luc、ARCaPM等重组整合,成为PC3-Luc/SPARCL1ARCaPM/SPARCL1细胞等实验组细胞系及PC3-Luc/EV、ARCaPM/EV等对照组细胞系,前者能稳定过表达SPARCL1蛋白。
体外实验结果：
2.3.1细胞增殖实验PC3-Luc/SPARCL1细胞与PC3-Luc/EV细胞两组细胞系在24小时和48小时等时间点增值率均无统计学差异；
2.3.2软琼脂集落形成实验结果显示PC3-Luc/SPARCL1细胞与PC3-Luc-EV细胞两组形成的集落数目、大小无明显设统计学差异。
2.3.3细胞伤口愈合实验显示实验组PC3-luc/SPARCL1的细胞(伤口愈合封闭百分比,15%,相比对照组(PC3-luc/EV,33%)有着显著下降(P=3.2×10-7)。
2.3.4PC3-Luc/SPARCL1较PC3-Luc/EV细胞在transwell小室迁移实验中抑制率为64%,ARCaPM/SPARCL1细胞较ARCaPM/EV细胞在transwell小室迁移实验中的抑制率为67%。
2.3.5实验48小时后,在transwell小室侵袭实验中PC3-Luc/SPARCL1对比PC3-Luc/EV细胞的侵袭性显著降低(P=0.008)；ARCaPM/SPARCLl对比ARCaP/EV的侵袭性也显著降低(P=0.022)
动物实验结果：
2.4.1全身荷瘤及局部器官侵袭程度：
在OX(8只实验组小鼠,10只对照组小鼠)和IC(8只实验组小鼠,10只对照组小鼠)两个模型小鼠中,植入PC3-luc/SPARCLl细胞的实验组小鼠显示了较小的原发肿瘤区域和转移肿瘤区域,相比较而言,空载体对照小鼠(PC3-Iuc/EV),具有较强烈的荧光素酶活性(全身或各解剖器官包括肝、肾上腺、胰腺、脾脏、骨等)。其中转移性溶骨性病变,均经X射线图像证实。
2.4.2原位及转移瘤肿瘤细胞的确认
我们应用GFP(PC3-LUC细胞标记)免疫组化染色证实了原位肿瘤及转移瘤细胞均起源于PC3细胞(PC3-luc/EV和PC3-luc/SPARCLl),并发现他们具有一个类似的侵袭性肿瘤细胞生长模式。
2.4.3SPARCLl对原位肿瘤体积大小的影响
为确定SPARCLl是否抑制原位肿瘤的生长,我们对PC3-luc/EV和PC3-luc/SPARCLl两组小鼠的最终原位肿瘤体积进行了测量和比较。数据显示出两组具有类似的肿瘤体积(P>0.05)
2.4.4实验组与对照组全身荷瘤量的对比
我们利用标准化方法,计算了各小鼠每周的全身荧光强度(反映肿瘤总负担)。结果表明,在OX模型小鼠中,从第2-6周,PC3-luc/SPARCL组的平均全身荧光强度较PC3-luc／EV组低约4-7倍(P<0.001)。与此一致的是,在IC模型中,肿瘤细胞注射后第5周的全身局部骨转移数量对比中PC3-luc/SPARCL1组较PC3-luc/EV组也明显为少(P=0.04)
2.4.5SPARCL1蛋白对小鼠生存时间的影响
我们利用Kaplan-Meier生存曲线,以评估OX模型实验组和对照组的整体的生存情况。结果表明,PC3-luc/SPARCL1组小鼠和PC3-luc/EV组小鼠在总生存期存在着显著差异(P<0.0001)。总体而言,接种PC3-luc/SPARCL1细胞的小鼠存活多两个星期左右的时间,在60天时,PC3一luc/SPARCLl组小鼠表现出100%的存活率,而对照组小鼠(PC3-luc/EV)的则为0%。
2.4.6SPARCL1蛋白的表达抑制前列腺癌肿瘤转移
为进一步观察SPARCL1对肿瘤发展及转移中的影响,我们对OX和IC两个模型中,PC3-luc/EV组和PC3-luc/SPARCL1组小鼠的转移率及在各器官中的分布进行了统计。在这两种模型中，PC3-luc/EV和PC3-luc/SPARCL1细胞均能够发生内脏转移,在各种不同的软组织部位如肝脏、肺脏、肾上腺、胰腺、脾等。另外在IC模型中,PC3-luc/EV PC3-luc/SPARCL1都可能蔓延到骨,并形成溶骨。处死小鼠后,对两个模型中由PC3-luc/EV和PC3-luc/SPARCL1细胞导致的转移点的探测表明,PC3-luc/SPARCL1组小鼠,无论是软组织还是骨骼转移的频率均低于PC3-LUC/EV组小鼠。两组相比,PC3-luc/SPARCL1明显降低最终内脏转移总数,更具体地说,在OX模型(P=0.01)低27%在IC模型中(P<0.001)低45%。在IC模型中,两组主要长骨中的转移数目具有统计学差异,PC3-luc/SPARCL1组较PC3-luc/EV明显降低骨转移数目(P=0.04)
结论：
1.利用生物信息学方法,发现SPARCL1非常符合前列腺癌转移抑制基因特征；
2.SPARCL1蛋白不能抑制体外前列腺癌细胞系增殖、锚定生长,不能抑制前列腺癌在小鼠体内的原位生长；
3.SPARCL1蛋白能够抑制体外前列腺癌细胞系的迁移、侵袭,能够抑制前列腺癌细胞系在小鼠体内的转移,延长带瘤小鼠存活时间等；
综合先前的基因表达荟萃分析结果及临床资料和传统的体内、体外实验方法,我们发现SPARCL1符合肿瘤转移抑制基因的特性,初步鉴定其为前列腺癌转移抑制基因,具体机制尚需进一步研究。
Backgrounds and purpose:
In men, cancer of the prostate gland is the most commonly diagnosed non-cutaneous malignancy, accounting for29%of all cancer cases and the second most common cause of death by cancer in the USA. In2012, an estimated241,740men were diagnosed with prostate cancer and28,170men died of prostate cancer. The majority of cancer-associated deaths and essentially all prostate cancer deaths are due to metastases rather than primary tumor burden. Thus, decreasing mortality of prostate cancer depends on understanding the biology that underlies metastasis such as identification of genes involved in cancer metastasis that would benefit the design of more effective clinical intervention strategies. There is a wealth of evidence indicating that the acquisition of malignant progression and aggressive traits of cancer can be promoted or inhibited by a set of functional genes known as metastasis-regulatory genes in various cancers. These can be broadly categorized as pro-metastasis or metastasis-suppressor genes. Pro-metastasis genes drive conversion from non-metastatic to metastatic cells. Metastasis-suppressor genes can suppress metastases without affecting primary tumor growth.
To identify candidate metastasis-regulatory genes in prostate cancer, a common and straightforward method is to elucidate a differential gene list (signature) derived from analysis of a transcriptional study on prostate cancer samples with groups correlated with poor prognosis. However, the single study-based signature is often underpowered, truncated, and low quality. These limitations can be overcome by combining related independent studies into a meta-analysis for larger sample size and smaller false discovery. There are a limited number of published prostate cancer gene-expression studies having clinical survival outcome data for meta-analysis. Sowe implemented and performed a large meta-analysis of breast cancer gene expression profiles from223datasets containing10,581human breast cancer samples using a novel data similarity-based approach (iterative EXALT). Cancer gene expression signatures extracted from individual datasets were clustered by data similarity and consolidated into a meta-signature with a recurrent and concordant gene expression pattern. A retrospective survival analysis was performed to evaluate the predictive power of a novel meta-signature deduced from transcriptional profiling studies of human breast cancer. Validation cohorts consisting of6,011breast cancer patients from21different breast cancer datasets and1,110patients with other malignancies (lung and prostate cancer) were used to test the robustness of our findings.
The certification standard is the predictive accuracy for patients' survival of the new gene signature. In this meta-analysis, based on data similarity,633tumor markers were integrated into121tumor markers. From these tumor markers, we found11of them represent the behavior of a highly malignant tumor. Then we identified50genes from them, named BRmet50. BRmet50was proved to be a better tumor gene signature than the ones in the past with a more accurate prediction of prognosis of breast cancer patients and this prediction result is independent with commonly used clinical and pathological parameters. In addition, the gene signature is not only limited to the predictability accuracy for breast cancer prognosis, and prostate cancer, lung cancer prognosis also accurately predicted. BRmet50contains11candidate tumor metastasis suppressor genes and39candidate tumor metastasis promoting genes.
This study intends to use bioinformatics methods to screen the11candidate tumor metastasis suppressor genes, and then to identify the biological behavior of the target candidate genes in prostate cancer in order to discover new prostate cancer metastasis suppressor gene.
Materials and methods:
1. The screening of the candidate prostate cancer metastasis suppressor gene
1.1To determine the association between a recently defined50-gene expression signature and prostate cancer.
We first examined whether the signature could be applied to predict prognosis in published prostate cancer datasets. Various prostate cancer outcomes (relapse, distant metastasis, or death) from957prostate cancer patients were used as clinical end points in the survival analyses.
1.2To screen the best candidate prostate cancer metastasis suppressor gene.
Eleven of50genes were downregulated in aggressive tumors. We used a bioinformatic approach to determine if any of the11suppressor candidate genes exhibited downregulation in human prostate cancer. We surveyed gene expression of the11candidates among data from10published transcriptional profiling studies performed on normal or diseased prostate tissues. Differential gene expression (up or down) was determined by a comparison between an experimental group and a control group within each dataset.Then we will take the best candidate gene to do further researchs.
1.3To choose the best candidate prostate cancer metastasis suppressor gene in1.2step and then determine whether its protein expression is lost in prostate cancer samples, we evaluated the candidate gene levels by Western blot in protein lysates from prostate cancer samples, non-malignant tissue and prostate cancer cells to identify it preplemently as a metastasis suppressor.
2. The identifying of the candidate prostate cancer metastasis suppressor gene
2.1Choose the proper prostate cancer cell lines with bioluminescence marker.
2.2Identifying over expression vector for candidate gene and then to establish a system for stable candidate gene overexpression in prostate cancer cell lines; we used retroviral vector, which can carry the purpose gene to recombinant with host cell genome, so as to achieve the purpose of stable expression.
2.3Standard in vitro studies to research the effect of the candidate gene's over-expression in prostate cancer cell lines PC3and ARCaPM on proliferation, migration and invasiveness (each experiment was repeated at least three times)
2.3.1Cell proliferation assay
2.3.2Soft agar colony formation assay
2.3.3Wound healing assay
2.3.4Transwell chamber migration assay
2.3.5Transwell chamber invasion assay
2.4Animal models in vivo studies to research the effect of the candidate gene's over-expression in PC3cell lines on the grown and metastasis in vivo in experimental animals (Any animal metastasis model experiment was repeated at least twice):
Severe combined immunodeficient (SCID) male mice were randomized into two groups:PC3-luc/EV and PC3-luc/Candidate gene. After PC3xenografting, mice were imaged biweekly for bioluminescence using an in vivo Imaging System (MS) to monitor tumor growth. Upon sacrifice, the prostate and other organs were removed for imaging and histological examination. Survival data were plotted on a Kaplan-Meier curve, and two different groups were compared using the Log-rank (Mantel-Cox) test.
For orthotopic xenografting (OX) experiments,10-week-old SCID mice were randomized into two groups:PC3-luc/EV and PC3-luc/candidate gene. PC3-luc/EV or PC3-luc/candidate cells (3x105in30u.1) mixing with neutralized collagen gel were implanted into the mouse anterior prostate (AP) lobe through a lower midline laparotomy incision. The liquid collagen gel containing PC3cells became solid in vivo. We then closed the incision of AP to let the solid gel piece stay inside of the lumen of the AP lobe. There was no cell suspension left in the space surrounding space of the prostatic ducts.
For Intracardiac (IC) injections, in brief,6-8-week-old SCID male mice were randomized into two groups. PC3-luc/EV or PC3-luc/candidate gene cells (5×105) were re-suspended in100μl PBS and slowly injected into the left ventricle of the mice. IVIS and radiographs (Faxitron) were used to confirm successful injections into the mouse body and to monitor metastasis formation.
Results:
1. Discovery of candidate metastasis suppressor gene
1.1Our results demonstrated that the50-gene signature successfully predicted clinical outcomes in all three prostate cancer datasets (p<0.001)
1.2Out of the11candidate genes. SPARC-like1(SPARCL1) displayed the most consistent profile among the10datasets. Upregulation of SPARCL1was found in nonmalignant (benign) and normal prostate tissues. Downregulation of SPARCL1was observed in prostate cancer samples, tumors with high grade (T3B), high Gleason scores (GS>7), androgen independent (AI) status, or metastatic prostate tumors.
1.3Protein SPARCL1levels were downregulated in prostate cancer samples in comparison to the non-malignant sample. SPARCL1expression is undetectable in LNCaP, ARCaPM, and PC3cancer cells. In contrast, high expression of SPARCL1was observed in benign human prostate tissue and benign prostate cell lines (NHPrE1).
2. Identifying of the candidate metastasis suppressor gene
The preparation of the cell lines for the experiment and the establishment of the candidate gene over-expression:
2.1The bioluminescent human prostate carcinoma cell line (PC3-Luc) from Dr. K. Pienta (University of Michigan Medical Center)) has bioluminent marker that has Luciferase can effect with luciferin and can be detected by IVIS.
2.2pBMN-l-GFP retroviral transfection vector was applied to construct pBMN-I-SPARCL1-GFP vector and SPARCL1gene open reading frame fragment was successfully restructured and integrated with the host cells, such as PC3-Luc, ARCaPM. So they became PC3-LUC/SPARCL1, ARCaPM/SPARCL1cells and PC3-Luc/EV, ARCaPM/EV cell lines were the control cells. PC3-Luc/SPARCL1and ARCaPM/SPARCL1cells can over-express protein SPARCL1stably.
Resuls of in vitro studies:
2.3.1Proliferation rates of the PC3-luc/EV and PC3-luc/SPARCL1cells were similar in24-and48-hour measurements;
2.3.2There were similar numbers of PC3-luc/EV and PC3-luc/SPARCL1colonies after3weeks culture.
2.3.3At12hours, PC3-luc/SPARCL1cells showed significantly less motility and migration (wound-healing closure percentage,15%) compared to the control (PC3-luc/EV,33%)(P=3.2×10-7);
2.3.4Recombinant SPARCL1significantly inhibited both PC3and ARCaPM cells across a membrane in a transwell migration assay (inhibition rates,64%and67%, respectively)
2.3.5In a48-hour invasion assay, more PC3-luc/EV cells invaded through the basement membrane compared to PC3-luc/SPARCL1cells. In comparison to the empty vector control (PC3-luc/EV) cells, SPARCL1significantly decreased the invasiveness of PC3cells by2.7-fold in a transwell Matrigel invasion assay (P=0.008). We found that recombinant SPARCL1could also reduce invasiveness of ARCaPM cells (P=0.022).
Results of in vivo studies:
2.4.1Total body tumor buden and the invasiveness of organs:
In both OX (8mice in experimental group and10mice in control group) and IC models (8mice in experimental group and10mice in control group), mice implanted with PC3-luc/SPARCLl cells displayed smaller areas and less intense luciferase activities in either the whole body or the dissected organs compared to the empty vector control mice (PC3-luc/EV)
2.4.2Confirmation of the OX tumor and metastasis sites.
To confirm this PC3cell identity in xenografted tumors, IHC staining of GFP (PC3-luc cell marker, was earned out to show that these tumors originated from xenografted PC3cells (PC3-luc/EV and PC3-luc/SPARCL1). Histological analysis of orthotopically xenografted PC3-luc/EV and PC3-luc/SPARCLl tumors indicated that they had a similar pattern of invasive tumor cell growth in the prostate and other metastatic sites.
2.4.3The effect of protein SPARCL1on the size of OX tumor
To determine whether SPARCL1had an effect on suppressing orthotopic tumor growth, final orthotopic tumor volumes from PC3-luc/EV and PC3-luc/SPARCL1mice were measured and compared. Data revealed similar tumor volumes in EV and SPARCL1groups (p>0.05)
2.4.4The comparation of the total body tumor burden between the experimental group and control group
We computed the whole body luminescence index from normalized whole-body photon emission rates (reflective of total tumor burden). The whole body luminescence indexes from PC3-luc/SPARCL1group were consistently lower by approximately4-to7-fold than those from PC3-luc/EV group (P<0.001). Consistent with the whole body tumor burden, the total bone luminescence indexes in the PC3-luc/SPARCL1group at week5post-injection were also significantly lower than PC3-luc/EV group (P=0.04)
2.4.5The effect of protein SPARCL1on the survive time of the mice
Kaplan-Meier curves were generated to evaluate overall survival for control mice (PC3-luc/EV) and mice xenografted with SPARCL1overexpression cells (PC3-luc/SPARCL1). The results indicated a significant difference in overall survival between the mice inoculated with PC3-luc/SPARCL1and mice inoculated with PC3-luc/EV (P<0.0001). Overall, mice inoculated with PC3-luc/SPARCL1cells survived about two weeks longer. Mice bearing PC3-luc/SPARCL1tumors had a better prognosis, as demonstrated by100%survival at60days compared to0%for mice harboring control cells.
2.4.6SPARCL1expression suppresses metastasis
To gain insight into whether SPARCL1had an effect on the development and tropism of metastases, we evaluated the incidences of metastasis and tissue distribution of metastatic lesions in PC3-luc/EV and PC3-luc/SPARCL1groups using both OX and IC models. The numbers of metastatic sites were determined via bioluminescence imaging of anesthetized mice, bioluminescence ex vivo of isolated organs and X-ray imaging of the mouse skeletal system. When compared to PC3-luc-EV group, the total numbers of final visceral metastasis for the PC3-luc/SPARCL1group were statistically significantly lower in both in vivo models, more specifically,27%lower in the OX model (P=0.01) and45%lower in the IC model (P<0.001). In the IC model, metastatic lesions among main long bone skeletal sites decreased in PC3-luc/SPARCL1group significantly between PC3-luc/EV and PC3-luc/SPARCL1(P=0.04).
Conclusions:
1. We have screened SPARCL1gene as the candidate prostate cancer metastasis suppressor gene by bioinformatics method;
2. SPARCL1protein had no effect on cell proliferation or anchorage independent growth of prostate cancer cell lines in vitro and had no significant effect on the growth of primary orthotopic tumors in vivo animal studies.
3. SPARCL1could suppress motility and invasion of prostate cancer cell lines in vitro and could suppress the metastasis of prostate cancer in vivo animal studies as well as prolong the survive time of the animals with tumor.
In conclusion, we have provided evidence that SPARCL1is a new metastasis-suppressor gene in prostate cancer. This study sets the stage for further investigations of the basic mechanisms that underlie cancer metastasis. Additional studies on SPARCL1will be valuable for determining its mechanisms of metastasis suppression in cancer.
在美国,前列腺癌是最常见的非皮肤恶性肿瘤,占所有恶性肿瘤的29%,且是肿瘤导致死亡的第二位。2012年,大约有241,740男性诊断为前列腺癌,28,170男性死于前列腺癌。多数肿瘤相关的死亡和几乎所有的前列腺癌引起的死亡均与转移而非原位肿瘤负荷有关。因此,减少前列腺癌的病死率依赖于揭示肿瘤转移的生物学机制如发现参与肿瘤转移过程的基因等,从而制定相应的临床预防策略。有大量的研究表明存在着一批可以抑制或促进肿瘤转移的基因,被称为肿瘤转移调节基因。它们可以大体分为转移促进基因和转移抑制基因。转移促进基因促进肿瘤细胞从无转移性到具有转移性的转变。转移抑制基因可以单纯抑制肿瘤的转移而不影响原位肿瘤的生长。
要发现候选前列腺癌转移调节基因最直接的方法是在对应着不良预后的前列腺癌样本中,通过对转录信息的分析找到一组差异表达基因(基因标记)。但是单个研究常常缺乏统计学信度、信息不全、低质量等缺点。这些缺陷可以通过综合相关的不同的独立研究进行荟萃分析以增加样本,减少错误得以克服。目前,用来行荟萃分析的已公开发表的具有临床生存率数据的前列腺癌基因表达信息尚有限。因此,我们课题组转而利用已公开发表的丰富的乳腺癌基因表达及临床资料信息进行了荟萃分析。
该分析利用一个新的以数据相似性基础的方法对223个研究数据集,包含10,581名乳腺癌患者的数据进行了相似性整合。即将每个单个研究的数据集根据数据相似性分类后,整合成为大的具有可重复性、同一性的数据,从而发现新的更为准确的基因标记。然后利用21个新的包含6,011名乳腺癌患者及1,110名肺癌、前列腺癌等其它恶性肿瘤患者的研究数据集,对我们所发现的新的基因标记进行验证。验证标准为该新的基因标记对癌症患者生存率的预测准确性。在该荟萃分析中,根据数据相似性,633个肿瘤标记被整合成了121个肿瘤标记。从该121个肿瘤标记中,我们发现了11个代表了高度恶性肿瘤行为的标记,并从中筛选了50个相关基因,命名为BRmet50。经过验证,BRmet50是一个良好的肿瘤基因标记,能够较以往的肿瘤基因标记更为准确的预测乳腺癌患者的预后,且与肿瘤患者的常用的临床和病理参数相独立。另外,该基因标记不仅仅局限于对乳腺癌患者预后的准确预测性,对前列腺癌、肺癌患者的预后亦能准确预测。BRmet50中含有11个候选肿瘤转移抑制基因,39个候选肿瘤转移促进基因,本研究拟利用生物信息学方法对其中的11个候选肿瘤转移抑制基因进行筛选,并结合生物学实验对目标候选基因在前列腺癌中的生物学行为进行鉴定,以期发现新的前列腺癌转移抑制基因。
材料和方法：
1.候选前列腺癌转移抑制基因的筛选
1.1验证BRMet50这个新的基因标记对前列腺癌预后的预测准确性
我们选取已发表的3个数据集,共有957例前列腺癌患者,这些患者具有几种不同的前列腺癌预后转归结果(复发,远处转移或死亡),这三个预后结果被分别用来作为临床终点进行生存分析。分析的结果用来验证BRMet50这个新的基因标记预测前列腺癌患者预后的准确性；
1.2筛选最具肿瘤转移抑制基因特点的候选基因
在BRMet50中含有50个基因。其中有11个基因表达下调,这11个基因是候选肿瘤转移抑制基因。我们选取了10个已发表的关于正常或患病前列腺组织的基因表达数据进行研究。在每个研究数据中,我们对11个候选基因在前列腺癌患者实验组和对照组之间的差异表达进行了分析(增高或下降)。然后选取在这些数据中差异表达情况最为一致的基因。
1.3选取1.2中差异表达情况最为一致的的候选基因,对其在前列腺癌正常组织、前列腺癌组织及前列腺癌各细胞系中的表达情况进行了观察,以初步验证其表达谱是否符合前列腺癌转移抑制基因特征,如符合则对其进一步重点研究,以期鉴定其为前列腺癌转移抑制基因。
2.候选前列腺癌转移抑制基因的鉴定
2.1选取合适的带有生物荧光标记的前列腺癌细胞系；
2.2确定候选基因过表达载体,建立稳定的过度表达候选基因的前列腺癌细胞系；我们选取逆转录病毒载体,该载体能携带目的基因与宿主细胞基因组重组,从而达到稳定表达的目的。
2.3标准体外实验研究候选基因表达对前列腺癌细胞系PC3及ARCaPM的细胞增殖、迁移及侵袭性的影响(每种实验至少重复3次)：
2.3.1细胞增殖实验
2.3.2软琼脂集落形成实验
2.3.3细胞伤口愈合实验
2.3.4Transwell小室迁移实验
2.3.5Transwell侵袭实验
2.4动物模型体内实验研究候选基因对前列腺癌细胞系PC3在实验动物体内生长、转移的影响(每个转移模型实验至少重复2次)：
重度免疫缺陷小鼠(SCID小鼠)随机分为两组,分别注射两种细胞PC3-luc/EV(空对照)和PC3-luc/候选基因(候选基因过表达细胞系)。所注射PC3细胞系中含有萤火虫荧光素酶(Luciferase)标记。然后应用活体成像系统(IVIS-200)定期对小鼠体内肿瘤生长情况进行测定,并应用软件对每只小鼠全身荷瘤量进行计算。小鼠接近死亡时,处理小鼠,对各解剖器官(软组织器官和骨等)进行荧光检测,统计转移率,并对两组小鼠的生存曲线进行分析。
2.4.1原位异种移植小鼠前列腺癌原位转移模型(Orthotopic,OX模型)
10周龄SCID小鼠随机分为两组(5只实验组小鼠,5只对照组小鼠)：PC3-luc/EV注射组和PC3-luc/候选基因注射组。通过一个下腹正中手术切口,显微镜下将PC3-luc/EV或PC3-luc/候选基因细胞(3x105,30ul)混合胶原凝胶种植于前列腺前叶。其中PC3细胞的悬液随着胶原蛋白的凝固而成为了半固体,可以大大减少腹腔种植几率。然后,我们将前列腺前叶的切口关闭,让固体凝胶块留在前叶里面的管腔内。
2.4.2心脏注射小鼠前列腺癌全身转移模型(Intra-Cardiac,IC模型)
将6-8周龄SCID雄性小鼠随机分为两组(5只实验组小鼠,5只对照组小鼠)。将PC3-luc/EV或PC3-luc/候选基因细胞(5×105),重新悬浮于100ul PBS中,并缓慢注入小鼠心脏左心室内。
结果：
1.前列腺癌转移抑制候选基因筛选结果：
1.1基因标记BRmet50准确的预测了被检测的3个前列腺癌数据集中前列腺癌患者的预后结果(P<0.001)。
1.2基因SPARC like1(SPARCL1)在10个数据集实验组和对照组中的表达显示了最为一致的表现。SPARCL1被发现在正常前列腺组织或良性的前列组织中上调表达,而在前列腺癌组织,高级别前列腺癌(T3B),高Gleason评分(GS>7)前列腺癌肿瘤,雄激素非依赖性(AI)状态或转移性前列腺癌中下调表达。
1.3蛋白SPARCL1表达水平在前列腺癌组织中对比良性前列腺组织明显下调。在代表前列腺癌的恶性细胞系如LNCaP、ARCaPM、PC3中的表达检测不到。与此相反,在代表正常的良性前列腺组织的细胞系中(NHPrE1)高表达。
2.前列腺癌转移候选基因鉴定结果：
实验细胞系准备及候选基因过表达结果：
2.1由美国密歇根大学医学院K. Pienta博士所赠的PC3-Luc细胞带有萤火虫荧光素酶(Luciferase)标记,能够与底物luciferin相互作用发出生物荧光被探测到。
2.2我们应用pBMN-I-GFP逆转录病毒转染载体,成功构建pBMN-I-SPARCL1-GFP载体,并成功将SPARCL1基因开放读码框片段与宿主细胞PC3-Luc、ARCaPM等重组整合,成为PC3-Luc/SPARCL1ARCaPM/SPARCL1细胞等实验组细胞系及PC3-Luc/EV、ARCaPM/EV等对照组细胞系,前者能稳定过表达SPARCL1蛋白。
体外实验结果：
2.3.1细胞增殖实验PC3-Luc/SPARCL1细胞与PC3-Luc/EV细胞两组细胞系在24小时和48小时等时间点增值率均无统计学差异；
2.3.2软琼脂集落形成实验结果显示PC3-Luc/SPARCL1细胞与PC3-Luc-EV细胞两组形成的集落数目、大小无明显设统计学差异。
2.3.3细胞伤口愈合实验显示实验组PC3-luc/SPARCL1的细胞(伤口愈合封闭百分比,15%,相比对照组(PC3-luc/EV,33%)有着显著下降(P=3.2×10-7)。
2.3.4PC3-Luc/SPARCL1较PC3-Luc/EV细胞在transwell小室迁移实验中抑制率为64%,ARCaPM/SPARCL1细胞较ARCaPM/EV细胞在transwell小室迁移实验中的抑制率为67%。
2.3.5实验48小时后,在transwell小室侵袭实验中PC3-Luc/SPARCL1对比PC3-Luc/EV细胞的侵袭性显著降低(P=0.008)；ARCaPM/SPARCLl对比ARCaP/EV的侵袭性也显著降低(P=0.022)
动物实验结果：
2.4.1全身荷瘤及局部器官侵袭程度：
在OX(8只实验组小鼠,10只对照组小鼠)和IC(8只实验组小鼠,10只对照组小鼠)两个模型小鼠中,植入PC3-luc/SPARCLl细胞的实验组小鼠显示了较小的原发肿瘤区域和转移肿瘤区域,相比较而言,空载体对照小鼠(PC3-Iuc/EV),具有较强烈的荧光素酶活性(全身或各解剖器官包括肝、肾上腺、胰腺、脾脏、骨等)。其中转移性溶骨性病变,均经X射线图像证实。
2.4.2原位及转移瘤肿瘤细胞的确认
我们应用GFP(PC3-LUC细胞标记)免疫组化染色证实了原位肿瘤及转移瘤细胞均起源于PC3细胞(PC3-luc/EV和PC3-luc/SPARCLl),并发现他们具有一个类似的侵袭性肿瘤细胞生长模式。
2.4.3SPARCLl对原位肿瘤体积大小的影响
为确定SPARCLl是否抑制原位肿瘤的生长,我们对PC3-luc/EV和PC3-luc/SPARCLl两组小鼠的最终原位肿瘤体积进行了测量和比较。数据显示出两组具有类似的肿瘤体积(P>0.05)
2.4.4实验组与对照组全身荷瘤量的对比
我们利用标准化方法,计算了各小鼠每周的全身荧光强度(反映肿瘤总负担)。结果表明,在OX模型小鼠中,从第2-6周,PC3-luc/SPARCL组的平均全身荧光强度较PC3-luc／EV组低约4-7倍(P<0.001)。与此一致的是,在IC模型中,肿瘤细胞注射后第5周的全身局部骨转移数量对比中PC3-luc/SPARCL1组较PC3-luc/EV组也明显为少(P=0.04)
2.4.5SPARCL1蛋白对小鼠生存时间的影响
我们利用Kaplan-Meier生存曲线,以评估OX模型实验组和对照组的整体的生存情况。结果表明,PC3-luc/SPARCL1组小鼠和PC3-luc/EV组小鼠在总生存期存在着显著差异(P<0.0001)。总体而言,接种PC3-luc/SPARCL1细胞的小鼠存活多两个星期左右的时间,在60天时,PC3一luc/SPARCLl组小鼠表现出100%的存活率,而对照组小鼠(PC3-luc/EV)的则为0%。
2.4.6SPARCL1蛋白的表达抑制前列腺癌肿瘤转移
为进一步观察SPARCL1对肿瘤发展及转移中的影响,我们对OX和IC两个模型中,PC3-luc/EV组和PC3-luc/SPARCL1组小鼠的转移率及在各器官中的分布进行了统计。在这两种模型中，PC3-luc/EV和PC3-luc/SPARCL1细胞均能够发生内脏转移,在各种不同的软组织部位如肝脏、肺脏、肾上腺、胰腺、脾等。另外在IC模型中,PC3-luc/EV PC3-luc/SPARCL1都可能蔓延到骨,并形成溶骨。处死小鼠后,对两个模型中由PC3-luc/EV和PC3-luc/SPARCL1细胞导致的转移点的探测表明,PC3-luc/SPARCL1组小鼠,无论是软组织还是骨骼转移的频率均低于PC3-LUC/EV组小鼠。两组相比,PC3-luc/SPARCL1明显降低最终内脏转移总数,更具体地说,在OX模型(P=0.01)低27%在IC模型中(P<0.001)低45%。在IC模型中,两组主要长骨中的转移数目具有统计学差异,PC3-luc/SPARCL1组较PC3-luc/EV明显降低骨转移数目(P=0.04)
结论：
1.利用生物信息学方法,发现SPARCL1非常符合前列腺癌转移抑制基因特征；
2.SPARCL1蛋白不能抑制体外前列腺癌细胞系增殖、锚定生长,不能抑制前列腺癌在小鼠体内的原位生长；
3.SPARCL1蛋白能够抑制体外前列腺癌细胞系的迁移、侵袭,能够抑制前列腺癌细胞系在小鼠体内的转移,延长带瘤小鼠存活时间等；
综合先前的基因表达荟萃分析结果及临床资料和传统的体内、体外实验方法,我们发现SPARCL1符合肿瘤转移抑制基因的特性,初步鉴定其为前列腺癌转移抑制基因,具体机制尚需进一步研究。
Backgrounds and purpose:
In men, cancer of the prostate gland is the most commonly diagnosed non-cutaneous malignancy, accounting for29%of all cancer cases and the second most common cause of death by cancer in the USA. In2012, an estimated241,740men were diagnosed with prostate cancer and28,170men died of prostate cancer. The majority of cancer-associated deaths and essentially all prostate cancer deaths are due to metastases rather than primary tumor burden. Thus, decreasing mortality of prostate cancer depends on understanding the biology that underlies metastasis such as identification of genes involved in cancer metastasis that would benefit the design of more effective clinical intervention strategies. There is a wealth of evidence indicating that the acquisition of malignant progression and aggressive traits of cancer can be promoted or inhibited by a set of functional genes known as metastasis-regulatory genes in various cancers. These can be broadly categorized as pro-metastasis or metastasis-suppressor genes. Pro-metastasis genes drive conversion from non-metastatic to metastatic cells. Metastasis-suppressor genes can suppress metastases without affecting primary tumor growth.
To identify candidate metastasis-regulatory genes in prostate cancer, a common and straightforward method is to elucidate a differential gene list (signature) derived from analysis of a transcriptional study on prostate cancer samples with groups correlated with poor prognosis. However, the single study-based signature is often underpowered, truncated, and low quality. These limitations can be overcome by combining related independent studies into a meta-analysis for larger sample size and smaller false discovery. There are a limited number of published prostate cancer gene-expression studies having clinical survival outcome data for meta-analysis. Sowe implemented and performed a large meta-analysis of breast cancer gene expression profiles from223datasets containing10,581human breast cancer samples using a novel data similarity-based approach (iterative EXALT). Cancer gene expression signatures extracted from individual datasets were clustered by data similarity and consolidated into a meta-signature with a recurrent and concordant gene expression pattern. A retrospective survival analysis was performed to evaluate the predictive power of a novel meta-signature deduced from transcriptional profiling studies of human breast cancer. Validation cohorts consisting of6,011breast cancer patients from21different breast cancer datasets and1,110patients with other malignancies (lung and prostate cancer) were used to test the robustness of our findings.
The certification standard is the predictive accuracy for patients' survival of the new gene signature. In this meta-analysis, based on data similarity,633tumor markers were integrated into121tumor markers. From these tumor markers, we found11of them represent the behavior of a highly malignant tumor. Then we identified50genes from them, named BRmet50. BRmet50was proved to be a better tumor gene signature than the ones in the past with a more accurate prediction of prognosis of breast cancer patients and this prediction result is independent with commonly used clinical and pathological parameters. In addition, the gene signature is not only limited to the predictability accuracy for breast cancer prognosis, and prostate cancer, lung cancer prognosis also accurately predicted. BRmet50contains11candidate tumor metastasis suppressor genes and39candidate tumor metastasis promoting genes.
This study intends to use bioinformatics methods to screen the11candidate tumor metastasis suppressor genes, and then to identify the biological behavior of the target candidate genes in prostate cancer in order to discover new prostate cancer metastasis suppressor gene.
Materials and methods:
1. The screening of the candidate prostate cancer metastasis suppressor gene
1.1To determine the association between a recently defined50-gene expression signature and prostate cancer.
We first examined whether the signature could be applied to predict prognosis in published prostate cancer datasets. Various prostate cancer outcomes (relapse, distant metastasis, or death) from957prostate cancer patients were used as clinical end points in the survival analyses.
1.2To screen the best candidate prostate cancer metastasis suppressor gene.
Eleven of50genes were downregulated in aggressive tumors. We used a bioinformatic approach to determine if any of the11suppressor candidate genes exhibited downregulation in human prostate cancer. We surveyed gene expression of the11candidates among data from10published transcriptional profiling studies performed on normal or diseased prostate tissues. Differential gene expression (up or down) was determined by a comparison between an experimental group and a control group within each dataset.Then we will take the best candidate gene to do further researchs.
1.3To choose the best candidate prostate cancer metastasis suppressor gene in1.2step and then determine whether its protein expression is lost in prostate cancer samples, we evaluated the candidate gene levels by Western blot in protein lysates from prostate cancer samples, non-malignant tissue and prostate cancer cells to identify it preplemently as a metastasis suppressor.
2. The identifying of the candidate prostate cancer metastasis suppressor gene
2.1Choose the proper prostate cancer cell lines with bioluminescence marker.
2.2Identifying over expression vector for candidate gene and then to establish a system for stable candidate gene overexpression in prostate cancer cell lines; we used retroviral vector, which can carry the purpose gene to recombinant with host cell genome, so as to achieve the purpose of stable expression.
2.3Standard in vitro studies to research the effect of the candidate gene's over-expression in prostate cancer cell lines PC3and ARCaPM on proliferation, migration and invasiveness (each experiment was repeated at least three times)
2.3.1Cell proliferation assay
2.3.2Soft agar colony formation assay
2.3.3Wound healing assay
2.3.4Transwell chamber migration assay
2.3.5Transwell chamber invasion assay
2.4Animal models in vivo studies to research the effect of the candidate gene's over-expression in PC3cell lines on the grown and metastasis in vivo in experimental animals (Any animal metastasis model experiment was repeated at least twice):
Severe combined immunodeficient (SCID) male mice were randomized into two groups:PC3-luc/EV and PC3-luc/Candidate gene. After PC3xenografting, mice were imaged biweekly for bioluminescence using an in vivo Imaging System (MS) to monitor tumor growth. Upon sacrifice, the prostate and other organs were removed for imaging and histological examination. Survival data were plotted on a Kaplan-Meier curve, and two different groups were compared using the Log-rank (Mantel-Cox) test.
For orthotopic xenografting (OX) experiments,10-week-old SCID mice were randomized into two groups:PC3-luc/EV and PC3-luc/candidate gene. PC3-luc/EV or PC3-luc/candidate cells (3x105in30u.1) mixing with neutralized collagen gel were implanted into the mouse anterior prostate (AP) lobe through a lower midline laparotomy incision. The liquid collagen gel containing PC3cells became solid in vivo. We then closed the incision of AP to let the solid gel piece stay inside of the lumen of the AP lobe. There was no cell suspension left in the space surrounding space of the prostatic ducts.
For Intracardiac (IC) injections, in brief,6-8-week-old SCID male mice were randomized into two groups. PC3-luc/EV or PC3-luc/candidate gene cells (5×105) were re-suspended in100μl PBS and slowly injected into the left ventricle of the mice. IVIS and radiographs (Faxitron) were used to confirm successful injections into the mouse body and to monitor metastasis formation.
Results:
1. Discovery of candidate metastasis suppressor gene
1.1Our results demonstrated that the50-gene signature successfully predicted clinical outcomes in all three prostate cancer datasets (p<0.001)
1.2Out of the11candidate genes. SPARC-like1(SPARCL1) displayed the most consistent profile among the10datasets. Upregulation of SPARCL1was found in nonmalignant (benign) and normal prostate tissues. Downregulation of SPARCL1was observed in prostate cancer samples, tumors with high grade (T3B), high Gleason scores (GS>7), androgen independent (AI) status, or metastatic prostate tumors.
1.3Protein SPARCL1levels were downregulated in prostate cancer samples in comparison to the non-malignant sample. SPARCL1expression is undetectable in LNCaP, ARCaPM, and PC3cancer cells. In contrast, high expression of SPARCL1was observed in benign human prostate tissue and benign prostate cell lines (NHPrE1).
2. Identifying of the candidate metastasis suppressor gene
The preparation of the cell lines for the experiment and the establishment of the candidate gene over-expression:
2.1The bioluminescent human prostate carcinoma cell line (PC3-Luc) from Dr. K. Pienta (University of Michigan Medical Center)) has bioluminent marker that has Luciferase can effect with luciferin and can be detected by IVIS.
2.2pBMN-l-GFP retroviral transfection vector was applied to construct pBMN-I-SPARCL1-GFP vector and SPARCL1gene open reading frame fragment was successfully restructured and integrated with the host cells, such as PC3-Luc, ARCaPM. So they became PC3-LUC/SPARCL1, ARCaPM/SPARCL1cells and PC3-Luc/EV, ARCaPM/EV cell lines were the control cells. PC3-Luc/SPARCL1and ARCaPM/SPARCL1cells can over-express protein SPARCL1stably.
Resuls of in vitro studies:
2.3.1Proliferation rates of the PC3-luc/EV and PC3-luc/SPARCL1cells were similar in24-and48-hour measurements;
2.3.2There were similar numbers of PC3-luc/EV and PC3-luc/SPARCL1colonies after3weeks culture.
2.3.3At12hours, PC3-luc/SPARCL1cells showed significantly less motility and migration (wound-healing closure percentage,15%) compared to the control (PC3-luc/EV,33%)(P=3.2×10-7);
2.3.4Recombinant SPARCL1significantly inhibited both PC3and ARCaPM cells across a membrane in a transwell migration assay (inhibition rates,64%and67%, respectively)
2.3.5In a48-hour invasion assay, more PC3-luc/EV cells invaded through the basement membrane compared to PC3-luc/SPARCL1cells. In comparison to the empty vector control (PC3-luc/EV) cells, SPARCL1significantly decreased the invasiveness of PC3cells by2.7-fold in a transwell Matrigel invasion assay (P=0.008). We found that recombinant SPARCL1could also reduce invasiveness of ARCaPM cells (P=0.022).
Results of in vivo studies:
2.4.1Total body tumor buden and the invasiveness of organs:
In both OX (8mice in experimental group and10mice in control group) and IC models (8mice in experimental group and10mice in control group), mice implanted with PC3-luc/SPARCLl cells displayed smaller areas and less intense luciferase activities in either the whole body or the dissected organs compared to the empty vector control mice (PC3-luc/EV)
2.4.2Confirmation of the OX tumor and metastasis sites.
To confirm this PC3cell identity in xenografted tumors, IHC staining of GFP (PC3-luc cell marker, was earned out to show that these tumors originated from xenografted PC3cells (PC3-luc/EV and PC3-luc/SPARCL1). Histological analysis of orthotopically xenografted PC3-luc/EV and PC3-luc/SPARCLl tumors indicated that they had a similar pattern of invasive tumor cell growth in the prostate and other metastatic sites.
2.4.3The effect of protein SPARCL1on the size of OX tumor
To determine whether SPARCL1had an effect on suppressing orthotopic tumor growth, final orthotopic tumor volumes from PC3-luc/EV and PC3-luc/SPARCL1mice were measured and compared. Data revealed similar tumor volumes in EV and SPARCL1groups (p>0.05)
2.4.4The comparation of the total body tumor burden between the experimental group and control group
We computed the whole body luminescence index from normalized whole-body photon emission rates (reflective of total tumor burden). The whole body luminescence indexes from PC3-luc/SPARCL1group were consistently lower by approximately4-to7-fold than those from PC3-luc/EV group (P<0.001). Consistent with the whole body tumor burden, the total bone luminescence indexes in the PC3-luc/SPARCL1group at week5post-injection were also significantly lower than PC3-luc/EV group (P=0.04)
2.4.5The effect of protein SPARCL1on the survive time of the mice
Kaplan-Meier curves were generated to evaluate overall survival for control mice (PC3-luc/EV) and mice xenografted with SPARCL1overexpression cells (PC3-luc/SPARCL1). The results indicated a significant difference in overall survival between the mice inoculated with PC3-luc/SPARCL1and mice inoculated with PC3-luc/EV (P<0.0001). Overall, mice inoculated with PC3-luc/SPARCL1cells survived about two weeks longer. Mice bearing PC3-luc/SPARCL1tumors had a better prognosis, as demonstrated by100%survival at60days compared to0%for mice harboring control cells.
2.4.6SPARCL1expression suppresses metastasis
To gain insight into whether SPARCL1had an effect on the development and tropism of metastases, we evaluated the incidences of metastasis and tissue distribution of metastatic lesions in PC3-luc/EV and PC3-luc/SPARCL1groups using both OX and IC models. The numbers of metastatic sites were determined via bioluminescence imaging of anesthetized mice, bioluminescence ex vivo of isolated organs and X-ray imaging of the mouse skeletal system. When compared to PC3-luc-EV group, the total numbers of final visceral metastasis for the PC3-luc/SPARCL1group were statistically significantly lower in both in vivo models, more specifically,27%lower in the OX model (P=0.01) and45%lower in the IC model (P<0.001). In the IC model, metastatic lesions among main long bone skeletal sites decreased in PC3-luc/SPARCL1group significantly between PC3-luc/EV and PC3-luc/SPARCL1(P=0.04).
Conclusions:
1. We have screened SPARCL1gene as the candidate prostate cancer metastasis suppressor gene by bioinformatics method;
2. SPARCL1protein had no effect on cell proliferation or anchorage independent growth of prostate cancer cell lines in vitro and had no significant effect on the growth of primary orthotopic tumors in vivo animal studies.
3. SPARCL1could suppress motility and invasion of prostate cancer cell lines in vitro and could suppress the metastasis of prostate cancer in vivo animal studies as well as prolong the survive time of the animals with tumor.
In conclusion, we have provided evidence that SPARCL1is a new metastasis-suppressor gene in prostate cancer. This study sets the stage for further investigations of the basic mechanisms that underlie cancer metastasis. Additional studies on SPARCL1will be valuable for determining its mechanisms of metastasis suppression in cancer.
引文
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