Expression profiling of primary and metastatic oral squamous cell carcinoma identifies progression-associated transcriptome changes and therapeutic vulnerabilities

IF 20.1 1区 医学 Q1 ONCOLOGY
Jonas Pyko, Markus Glaß, Julia Rosemann, Matthias Kappler, Jana Macho, Sarah Qasem, Stefan Hüttelmaier, Alexander W. Eckert, Monika Haemmerle, Tony Gutschner
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Hence, a better understanding of the molecular mechanisms underlying oral cancer metastasis and the identification of therapeutic vulnerabilities are needed to prevent and treat metastatic disease.</p><p>We collected 87 primary tumors and 21 lymph node metastasis (LNM) from 72 OSCC patients to conduct comprehensive transcriptome-wide expression and correlation analyses (Figure 1A). First, we performed expression-based clustering with all primary tumors and observed the best subdivision with <i>k</i> = 3 using protein-coding and non-coding genes (Figure 1B). Of note, we observed transcriptional heterogeneity among multiregional tumor samples in about 30% of the cases, leading to the assignment of these patients and their respective tumors to different clusters. Intriguingly, Kaplan-Meier analysis of patients whose tumors were unambiguously assigned to only one cluster revealed that cluster 3 (C3) had the worst outcome, with a median survival of 15.6 months compared to 28.57 and 36.53 months for clusters 1 (C1) and 2 (C2), respectively (Figure 1C). Importantly, prognostic factors known to negatively affect survival, such as high T, N, and G status, were not enriched in C3 tumors (Supplementary Figure S1A-C). However, gene expression analysis identified 244 genes that were significantly changed in C3 compared to C1/2 tumors (Supplementary Figure S1D, Supplementary Table S1). Of note, cell cycle-related gene sets, including Early region 2 binding factor (<i>E2F</i>) and Myelocytomatosis oncogene (<i>MYC</i>) target genes, along with other oncogenic signaling pathways, showed a positive normalized enrichment score (NES), potentially explaining the poor outcomes of C3 tumors (Supplementary Figure S1E).</p><p>Next, we performed a gene expression-based overall survival (OS) analysis and identified two significant genes, namely Zinc Finger Protein 443 (<i>ZNF443</i>) and Serine Hydroxymethyltransferase 2 (<i>SHMT2</i>) (Figure 1D, Supplementary Table S2). Specifically, <i>ZNF443</i> expression was associated with a reduced risk (Hazard ratio [HR] = 0.238), whereas expression of <i>SHMT2</i> (HR = 4.028) suggested a higher risk of mortality. Thus, we further tested their prognostic relevance for OS and recurrence/disease-free survival (RFS/DFS) in our patient cohort (Figure 1E, Supplementary Figure S2A-C) as well as in The Cancer Genome Atlas (TCGA) HNSCC dataset (Supplementary Figure S2D-E) [<span>4</span>]. These analyses indicated that <i>SHMT2</i>, but not <i>ZNF443</i>, might serve as an OSCC-specific biomarker for OS. In line with this, <i>SHMT2</i> expression was higher in HNSCC tissues compared to normal tissues, as well as in T4 versus T1 tumors of the OSCC subtype, and its expression level increased with higher tumor grade (Supplementary Figure S3). Furthermore, univariate Cox regression analysis demonstrated a significant association of age, T-stage, N-stage, and <i>SHMT2</i> expression (Relative Risk [RR] = 1.548, <i>P</i> = 0.049; 95% confidence interval [CI] = 1.000-2.396]) with OS in OSCC patients. Multivariate analysis further confirmed the association of <i>SHMT2</i> (RR = 1.616, <i>P</i> = 0.041; 95% CI = 1.020-2.559]) (Supplementary Table S3). Intriguingly, downregulating <i>SHMT2</i> in SAS, Cal33, and XF354 cells or blocking its activity using an inhibitor [<span>5</span>] reduced proliferation and viability while inducing apoptosis (Figure 1F, Supplementary Figure S4). These data confirmed previous studies and underscored the therapeutic potential of <i>SHMT2</i> in OSCC [<span>6</span>, <span>7</span>].</p><p>Next, we aimed to characterize the metastasis-associated transcriptome in our OSCC cohort. First, we compared the transcriptome of primary tumors and matched LNM from each patient. This analysis identified 1,710 deregulated protein-coding and 990 long non-coding RNA (lncRNA) genes (false discovery rate [FDR] ≤ 0.05; | log2(Fold change) | ≥ 1). Subsequent gene set enrichment analysis revealed 32 gene sets, including Kirsten Rat Sarcoma Viral Oncogene Homology (<i>KRAS</i>) signaling and epithelial-to-mesenchymal transition (EMT)-promoting gene sets, among others, which showed positive enrichment in metastasis (Supplementary Figure S5A-C, Supplementary Tables S4-S5). In order to narrow down the list of putative metastasis-associated genes, we compared gene expression patterns between primary tumors with (<i>n</i> = 43) and without (<i>n</i> = 24) LNM. This complementary approach uncovered 482 deregulated protein-coding and 190 lncRNA genes (Supplementary Figure S5D-E, Supplementary Tables S6-S7). Intriguingly, a total of 31 gene sets were significantly enriched in LNM-positive (LNM<sup>pos</sup>) tumors, but only EMT-promoting genes showed consistent positive enrichment in both differential gene expression analysis (Supplementary Figure S5F). To identify individual genes driving and maintaining metastases, we intersected the lists of differentially expressed genes from both analyses (Supplementary Table S8). This revealed a common set of 41 upregulated and 40 downregulated genes. Gene ontology analysis suggested that differentiation-associated processes were impaired in both LNM and LNM-positive tumors (Figure 1G). Importantly, a database search using the canSAR knowledgebase [<span>8</span>] identified four consistently upregulated genes that are targetable with approved clinical drugs. However, their cellular and molecular functions as well as their contribution to OSCC metastasis needs to be established using appropriate in vitro and in vivo models.</p><p>Finally, we extended our gene-level expression analysis and characterized gene isoform usage in primary tumors and their matched metastasis. We identified hundreds of alternative transcription events that were either enriched or diminished in metastasis (Supplementary Figure S6A). At the individual gene level, this analysis yielded a list of 114 genes with significant isoform switches (Figure 1H, Supplementary Table S9). The most significant isoform switches were observed for Wnt Family Member 5A (<i>WNT5A</i>) and Myosin Light Chain 6 (<i>MYL6</i>), whereas SH3 And Cysteine Rich Domain 3 (<i>STAC3</i>), and RAR Related Orphan Receptor C (<i>RORC</i>) showed the highest combined differences in isoform fraction (dIF) values (Figure 1H). We decided to investigate the isoform switch in <i>WNT5A</i> in greater detail. In metastases, the canonical isoform (<i>WNT5-201</i>) was more abundant, while the fractions of <i>WNT5A-202</i> (encoding the same WNT5A protein) and <i>WNT5-203</i> (encoding a shorter protein variant) were significantly reduced (Supplementary Figure S6B). We generated overexpression constructs, transduced SAS cells with these variants, and successfully detected all WNT5A proteins at their expected size (Figure 1I). Intriguingly, overexpression of the canonical WNT5A protein only slightly enhanced spheroid growth in SAS cells but strongly increased their invasive capacity (Supplementary Figure S6C-D). Moreover, comparison of the different WNT5A isoforms revealed no significant differences in growth (Figure 1J). However, cells overexpressing the <i>WNT5A-203</i> (BC construct) isoform exhibited markedly reduced invasive potential in Matrigel compared to cells expressing other WNT5A protein variants (Figure 1K). These findings suggest that inhibiting the canonical <i>WNT5A</i> isoform may represent a therapeutic strategy to prevent metastasis in OSCC, consistent with previous reports [<span>9</span>].</p><p>In summary, our study contributes to OSCC profiling and target identification efforts [<span>4</span>, <span>10</span>] in a unique manner. Our carefully selected sample collection included LNM-negative and LNM<sup>pos</sup> primary tumors as well as their matched metastases. Furthermore, RNA isolated in this study was subjected to total RNA sequencing upon ribosomal RNA depletion, providing a more unbiased view of the primary and metastatic oral cancer transcriptome. This approach enabled the identification of coding and non-coding genes, as well as isoforms, associated with OSCC metastasis. However, additional studies are needed (see Supplementary Discussion) to confirm the described associations and validate the clinical relevance of individual candidates in vitro and in vivo.</p><p>The study was conceptualized by Jonas Pyko, Markus Glaß, and Tony Gutschner with input from Monika Hämmerle and Stefan Hüttelmaier. Experiments were performed by Jonas Pyko, Julia Rosemann, Jana Macho, and Sarah Qasem. Patient tumor samples were collected by Matthias Kappler and Alexander W. Eckert. Pathological sample evaluation was performed by Monika Hämmerle. Computational analysis was performed by Markus Glaß and Stefan Hüttelmaier. Analysis of experimental data was done by Jonas Pyko, Markus Glaß, and Tony Gutschner. The manuscript was written by Jonas Pyko, Markus Glaß, and Tony Gutschner with input from all authors. Figures were prepared by Jonas Pyko, Markus Glaß, and Tony Gutschner. All authors have read and agreed to the final version of the manuscript.</p><p>The authors declare that they have no competing interests.</p><p>This study was supported by intramural funding from the Medical Faculty (Wilhelm-Roux program, FKZ32/19).</p><p>Ethical registry 210/19.08.09/10 was obtained from the Ethics Committee of the Medical Faculty of the University Halle. 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引用次数: 0

Abstract

Oral squamous cell carcinoma (OSCC), a major subgroup of head and neck squamous cell carcinoma (HNSCC), is an aggressive disease that preferentially spreads to cervical lymph nodes. Positive lymph node status is an important predictor of survival in OSCC [1-3]. Hence, a better understanding of the molecular mechanisms underlying oral cancer metastasis and the identification of therapeutic vulnerabilities are needed to prevent and treat metastatic disease.

We collected 87 primary tumors and 21 lymph node metastasis (LNM) from 72 OSCC patients to conduct comprehensive transcriptome-wide expression and correlation analyses (Figure 1A). First, we performed expression-based clustering with all primary tumors and observed the best subdivision with k = 3 using protein-coding and non-coding genes (Figure 1B). Of note, we observed transcriptional heterogeneity among multiregional tumor samples in about 30% of the cases, leading to the assignment of these patients and their respective tumors to different clusters. Intriguingly, Kaplan-Meier analysis of patients whose tumors were unambiguously assigned to only one cluster revealed that cluster 3 (C3) had the worst outcome, with a median survival of 15.6 months compared to 28.57 and 36.53 months for clusters 1 (C1) and 2 (C2), respectively (Figure 1C). Importantly, prognostic factors known to negatively affect survival, such as high T, N, and G status, were not enriched in C3 tumors (Supplementary Figure S1A-C). However, gene expression analysis identified 244 genes that were significantly changed in C3 compared to C1/2 tumors (Supplementary Figure S1D, Supplementary Table S1). Of note, cell cycle-related gene sets, including Early region 2 binding factor (E2F) and Myelocytomatosis oncogene (MYC) target genes, along with other oncogenic signaling pathways, showed a positive normalized enrichment score (NES), potentially explaining the poor outcomes of C3 tumors (Supplementary Figure S1E).

Next, we performed a gene expression-based overall survival (OS) analysis and identified two significant genes, namely Zinc Finger Protein 443 (ZNF443) and Serine Hydroxymethyltransferase 2 (SHMT2) (Figure 1D, Supplementary Table S2). Specifically, ZNF443 expression was associated with a reduced risk (Hazard ratio [HR] = 0.238), whereas expression of SHMT2 (HR = 4.028) suggested a higher risk of mortality. Thus, we further tested their prognostic relevance for OS and recurrence/disease-free survival (RFS/DFS) in our patient cohort (Figure 1E, Supplementary Figure S2A-C) as well as in The Cancer Genome Atlas (TCGA) HNSCC dataset (Supplementary Figure S2D-E) [4]. These analyses indicated that SHMT2, but not ZNF443, might serve as an OSCC-specific biomarker for OS. In line with this, SHMT2 expression was higher in HNSCC tissues compared to normal tissues, as well as in T4 versus T1 tumors of the OSCC subtype, and its expression level increased with higher tumor grade (Supplementary Figure S3). Furthermore, univariate Cox regression analysis demonstrated a significant association of age, T-stage, N-stage, and SHMT2 expression (Relative Risk [RR] = 1.548, P = 0.049; 95% confidence interval [CI] = 1.000-2.396]) with OS in OSCC patients. Multivariate analysis further confirmed the association of SHMT2 (RR = 1.616, P = 0.041; 95% CI = 1.020-2.559]) (Supplementary Table S3). Intriguingly, downregulating SHMT2 in SAS, Cal33, and XF354 cells or blocking its activity using an inhibitor [5] reduced proliferation and viability while inducing apoptosis (Figure 1F, Supplementary Figure S4). These data confirmed previous studies and underscored the therapeutic potential of SHMT2 in OSCC [6, 7].

Next, we aimed to characterize the metastasis-associated transcriptome in our OSCC cohort. First, we compared the transcriptome of primary tumors and matched LNM from each patient. This analysis identified 1,710 deregulated protein-coding and 990 long non-coding RNA (lncRNA) genes (false discovery rate [FDR] ≤ 0.05; | log2(Fold change) | ≥ 1). Subsequent gene set enrichment analysis revealed 32 gene sets, including Kirsten Rat Sarcoma Viral Oncogene Homology (KRAS) signaling and epithelial-to-mesenchymal transition (EMT)-promoting gene sets, among others, which showed positive enrichment in metastasis (Supplementary Figure S5A-C, Supplementary Tables S4-S5). In order to narrow down the list of putative metastasis-associated genes, we compared gene expression patterns between primary tumors with (n = 43) and without (n = 24) LNM. This complementary approach uncovered 482 deregulated protein-coding and 190 lncRNA genes (Supplementary Figure S5D-E, Supplementary Tables S6-S7). Intriguingly, a total of 31 gene sets were significantly enriched in LNM-positive (LNMpos) tumors, but only EMT-promoting genes showed consistent positive enrichment in both differential gene expression analysis (Supplementary Figure S5F). To identify individual genes driving and maintaining metastases, we intersected the lists of differentially expressed genes from both analyses (Supplementary Table S8). This revealed a common set of 41 upregulated and 40 downregulated genes. Gene ontology analysis suggested that differentiation-associated processes were impaired in both LNM and LNM-positive tumors (Figure 1G). Importantly, a database search using the canSAR knowledgebase [8] identified four consistently upregulated genes that are targetable with approved clinical drugs. However, their cellular and molecular functions as well as their contribution to OSCC metastasis needs to be established using appropriate in vitro and in vivo models.

Finally, we extended our gene-level expression analysis and characterized gene isoform usage in primary tumors and their matched metastasis. We identified hundreds of alternative transcription events that were either enriched or diminished in metastasis (Supplementary Figure S6A). At the individual gene level, this analysis yielded a list of 114 genes with significant isoform switches (Figure 1H, Supplementary Table S9). The most significant isoform switches were observed for Wnt Family Member 5A (WNT5A) and Myosin Light Chain 6 (MYL6), whereas SH3 And Cysteine Rich Domain 3 (STAC3), and RAR Related Orphan Receptor C (RORC) showed the highest combined differences in isoform fraction (dIF) values (Figure 1H). We decided to investigate the isoform switch in WNT5A in greater detail. In metastases, the canonical isoform (WNT5-201) was more abundant, while the fractions of WNT5A-202 (encoding the same WNT5A protein) and WNT5-203 (encoding a shorter protein variant) were significantly reduced (Supplementary Figure S6B). We generated overexpression constructs, transduced SAS cells with these variants, and successfully detected all WNT5A proteins at their expected size (Figure 1I). Intriguingly, overexpression of the canonical WNT5A protein only slightly enhanced spheroid growth in SAS cells but strongly increased their invasive capacity (Supplementary Figure S6C-D). Moreover, comparison of the different WNT5A isoforms revealed no significant differences in growth (Figure 1J). However, cells overexpressing the WNT5A-203 (BC construct) isoform exhibited markedly reduced invasive potential in Matrigel compared to cells expressing other WNT5A protein variants (Figure 1K). These findings suggest that inhibiting the canonical WNT5A isoform may represent a therapeutic strategy to prevent metastasis in OSCC, consistent with previous reports [9].

In summary, our study contributes to OSCC profiling and target identification efforts [4, 10] in a unique manner. Our carefully selected sample collection included LNM-negative and LNMpos primary tumors as well as their matched metastases. Furthermore, RNA isolated in this study was subjected to total RNA sequencing upon ribosomal RNA depletion, providing a more unbiased view of the primary and metastatic oral cancer transcriptome. This approach enabled the identification of coding and non-coding genes, as well as isoforms, associated with OSCC metastasis. However, additional studies are needed (see Supplementary Discussion) to confirm the described associations and validate the clinical relevance of individual candidates in vitro and in vivo.

The study was conceptualized by Jonas Pyko, Markus Glaß, and Tony Gutschner with input from Monika Hämmerle and Stefan Hüttelmaier. Experiments were performed by Jonas Pyko, Julia Rosemann, Jana Macho, and Sarah Qasem. Patient tumor samples were collected by Matthias Kappler and Alexander W. Eckert. Pathological sample evaluation was performed by Monika Hämmerle. Computational analysis was performed by Markus Glaß and Stefan Hüttelmaier. Analysis of experimental data was done by Jonas Pyko, Markus Glaß, and Tony Gutschner. The manuscript was written by Jonas Pyko, Markus Glaß, and Tony Gutschner with input from all authors. Figures were prepared by Jonas Pyko, Markus Glaß, and Tony Gutschner. All authors have read and agreed to the final version of the manuscript.

The authors declare that they have no competing interests.

This study was supported by intramural funding from the Medical Faculty (Wilhelm-Roux program, FKZ32/19).

Ethical registry 210/19.08.09/10 was obtained from the Ethics Committee of the Medical Faculty of the University Halle. All patients gave written informed consent (Department of Oral and Maxillofacial Plastic Surgery, University of Halle-Wittenberg, Germany).

Abstract Image

原发性和转移性口腔鳞状细胞癌的表达谱确定了进展相关的转录组变化和治疗脆弱性。
口腔鳞状细胞癌(OSCC)是头颈部鳞状细胞癌(HNSCC)的一个主要亚群,是一种侵袭性疾病,优先扩散到颈部淋巴结。淋巴结状态阳性是OSCC患者存活的重要预测指标[1-3]。因此,需要更好地了解口腔癌转移的分子机制和确定治疗脆弱性,以预防和治疗转移性疾病。我们从72例OSCC患者中收集了87例原发肿瘤和21例淋巴结转移(LNM),进行了全面的转录组表达和相关性分析(图1A)。首先,我们对所有原发肿瘤进行了基于表达的聚类,并观察了使用蛋白编码基因和非编码基因在k = 3时的最佳细分(图1B)。值得注意的是,我们在大约30%的病例中观察到多区域肿瘤样本的转录异质性,导致这些患者及其各自的肿瘤被分配到不同的聚类。有趣的是,Kaplan-Meier分析显示,肿瘤明确分配到一个组的患者中,3组(C3)的预后最差,中位生存期为15.6个月,而1组(C1)和2组(C2)的中位生存期分别为28.57个月和36.53个月(图1C)。重要的是,已知对生存有负面影响的预后因素,如高T、N和G状态,在C3肿瘤中并不富集(补充图S1A-C)。然而,基因表达分析发现,与C1/2肿瘤相比,C3中有244个基因发生了显著变化(Supplementary Figure S1D, Supplementary Table S1)。值得注意的是,细胞周期相关的基因集,包括早期2区结合因子(E2F)和髓细胞瘤癌基因(MYC)靶基因,以及其他致癌信号通路,显示了正的标准化富集评分(NES),这可能解释了C3肿瘤的不良预后(补充图S1E)。接下来,我们进行了基于基因表达的总生存期(OS)分析,并确定了两个重要基因,即锌指蛋白443 (ZNF443)和丝氨酸羟甲基转移酶2 (SHMT2)(图1D,补充表S2)。具体来说,表达ZNF443与死亡风险降低相关(风险比[HR] = 0.238),而表达SHMT2(风险比[HR] = 4.028)表明死亡风险较高。因此,我们在我们的患者队列(图1E,补充图S2A-C)以及癌症基因组图谱(TCGA) HNSCC数据集(补充图S2D-E)[4]中进一步测试了它们与OS和复发/无病生存(RFS/DFS)的预后相关性。这些分析表明SHMT2,而不是ZNF443,可能是oscc特异性的OS生物标志物。由此可见,SHMT2在HNSCC组织中的表达高于正常组织,在OSCC亚型的T4肿瘤中表达高于T1肿瘤,且其表达水平随肿瘤分级的升高而升高(补充图S3)。此外,单因素Cox回归分析显示,年龄、t分期、n分期与SHMT2表达显著相关(相对危险度[RR] = 1.548, P = 0.049;95%可信区间[CI] = 1.000-2.396])与OSCC患者的OS有关。多因素分析进一步证实了SHMT2的相关性(RR = 1.616, P = 0.041;95% CI = 1.020-2.559])(补充表S3)。有趣的是,下调SAS、Cal33和XF354细胞中的SHMT2或使用抑制剂[5]阻断其活性可降低增殖和活力,同时诱导凋亡(图1F,补充图S4)。这些数据证实了先前的研究,并强调了SHMT2在OSCC中的治疗潜力[6,7]。接下来,我们的目标是在我们的OSCC队列中表征转移相关的转录组。首先,我们比较了每位患者原发肿瘤和匹配LNM的转录组。该分析鉴定出1710个蛋白编码失调基因和990个长链非编码RNA (lncRNA)基因(错误发现率[FDR]≤0.05;随后的基因集富集分析显示32个基因集,包括Kirsten大鼠肉瘤病毒癌基因同源性(KRAS)信号和上皮-间质转化(EMT)促进基因集等,在转移中显示正富集(补充图S5A-C,补充表S4-S5)。为了缩小推定的转移相关基因列表,我们比较了原发性肿瘤(n = 43)和非(n = 24) LNM的基因表达模式。这种互补的方法发现了482个失调的蛋白质编码基因和190个lncRNA基因(补充图S5D-E,补充表S6-S7)。有趣的是,共有31组基因在lnm阳性(LNMpos)肿瘤中显著富集,但在两种差异基因表达分析中,只有emt促进基因呈现一致的阳性富集(Supplementary Figure S5F)。 为了确定驱动和维持转移的单个基因,我们交叉了两种分析中差异表达基因的列表(补充表S8)。这揭示了一组共有41个上调基因和40个下调基因。基因本体论分析表明,在LNM和LNM阳性肿瘤中,分化相关过程均受损(图1G)。重要的是,使用canSAR知识库的数据库搜索发现了四个持续上调的基因,这些基因可以被批准的临床药物靶向。然而,它们的细胞和分子功能以及它们对OSCC转移的贡献需要通过适当的体外和体内模型来建立。最后,我们扩展了我们的基因水平表达分析,并表征了基因异构体在原发性肿瘤及其匹配转移中的使用。我们发现了数百个在转移中富集或减少的转录事件(补充图S6A)。在单个基因水平上,该分析得出了114个具有显著异构体开关的基因列表(图1H,补充表S9)。在Wnt家族成员5A (WNT5A)和Myosin轻链6 (MYL6)中观察到最显著的异构体开关,而SH3和半胱氨酸富结构域3 (STAC3)以及RAR相关孤儿受体C (RORC)在异构体分数(dIF)值上的综合差异最大(图1H)。我们决定更详细地研究WNT5A的异构体开关。在转移瘤中,典型亚型(WNT5-201)更为丰富,而编码相同WNT5A蛋白的WNT5A-202和编码较短蛋白变体的WNT5-203的部分显著减少(补充图S6B)。我们构建了过表达构建体,用这些变异体转导SAS细胞,并成功检测到所有WNT5A蛋白的预期大小(图1I)。有趣的是,标准WNT5A蛋白的过表达仅轻微增强了SAS细胞的球形生长,但却强烈增加了其侵袭能力(补充图S6C-D)。此外,比较不同的WNT5A亚型,发现在生长方面没有显著差异(图1J)。然而,与表达其他WNT5A蛋白变体的细胞相比,过表达WNT5A-203 (BC构建体)亚型的细胞在Matrigel中表现出明显降低的侵袭潜力(图1K)。这些发现表明,抑制典型的WNT5A亚型可能是一种预防OSCC转移的治疗策略,这与先前的报道一致。总之,我们的研究以独特的方式为OSCC分析和目标识别工作做出了贡献[4,10]。我们精心挑选的样本收集包括lnm阴性和LNMpos原发肿瘤及其匹配的转移瘤。此外,本研究中分离的RNA在核糖体RNA缺失的情况下进行了总RNA测序,为原发性和转移性口腔癌转录组提供了更公正的观点。这种方法能够识别与OSCC转移相关的编码和非编码基因以及同种异构体。然而,需要更多的研究(见补充讨论)来证实所描述的关联,并验证个体候选药物在体外和体内的临床相关性。该研究由Jonas Pyko、Markus Glaß和Tony Gutschner构想,并得到Monika Hämmerle和Stefan h<e:2> ttelmaier的意见。实验由Jonas Pyko, Julia Rosemann, Jana Macho和Sarah Qasem进行。患者肿瘤样本由Matthias Kappler和Alexander W. Eckert收集。病理样本评估由Monika Hämmerle完成。计算分析由Markus Glaß和Stefan h<e:2> telmaier进行。实验数据的分析由Jonas Pyko, Markus Glaß和Tony Gutschner完成。手稿由Jonas Pyko, Markus Glaß和Tony Gutschner撰写,并得到了所有作者的意见。数据由Jonas Pyko, Markus Glaß和Tony Gutschner准备。所有作者都已阅读并同意稿件的最终版本。作者宣称他们没有竞争利益。本研究得到了医学院(Wilhelm-Roux program, FKZ32/19)的校内资助。从哈雷大学医学院伦理委员会获得了210/19.08.09/10伦理登记册。所有患者均给予书面知情同意书(德国Halle-Wittenberg大学口腔颌面整形外科)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cancer Communications
Cancer Communications Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
25.50
自引率
4.30%
发文量
153
审稿时长
4 weeks
期刊介绍: Cancer Communications is an open access, peer-reviewed online journal that encompasses basic, clinical, and translational cancer research. The journal welcomes submissions concerning clinical trials, epidemiology, molecular and cellular biology, and genetics.
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