免疫浸润:生信论文42乳腺癌引文写作

原创
2020/08/21 06:00
阅读数 50

生信论文的套路

  1. ONCOMINE从全景、亚型两个维度做表达差异分析;

  2. 临床标本从蛋白水平确认(或HPA数据库),很重要;

  3. Kaplan-Meier Plotter从临床意义的角度阐明其重要性;

  4. cBio-portal数据库做基因组学的分析(机制一);

  5. STRING互作和GO/KEGG分析探讨可能的信号通路(机制二);

  6. TISIDB/TIMER分析肿瘤免疫特征(机制三)。


引文的基本内容:介绍背景(一段或两段)、提出问题(一段),解决问题(一段或2段)。一般引文介绍3~5段。


  1. 疾病或基因的背景介绍;

  2. 前人研究的成果、现实情况,存在的问题;

  3. 阐明研究原因或意义。介绍研究的性质、范畴及其重要性,突出研究目的和待解决的科学问题;

  4. 研究方法,新发现和意义。


跟生信论文40中乳腺癌引文写作对比,该论文的引文写作更详细,对于初次生信阅读和写作有很大的帮助,很友好。但是该论文背景介绍显得过多,而分析又比较少,给人头重脚轻的感觉。因此,引文要做到明了,简要。


生信论文41--乳腺癌--引文写作


第一段详细介绍乳腺癌的流行病学,预后现状和治疗情况,引出诊断和治疗的重要性。


Breast cancer (BRCA) and the most frequent cause of cancer death in  women is a highly prevalent disease worldwide (Miller et al., 2016; Nagini, 2017). Survival rates of this disease largely depend on what stage the patients are diagnosed. Patients who are detected at an early stage have more superior survival rates. BRCA is regarded as a complex heterogeneous disease, which displays significant diversity based on histopathological features and therapeutic responses. The molecular classification of BRCA is classified into different subtypes based on the hormone receptor status and human epithelial growth factor receptor-2 (HER2) expression, namely luminal A, luminal B, HER2 enriched, and basal-like/triple negative breast cancer. Thus, the diagnostic approach and targeted therapy to breast cancer should be subtype oriented to achieve the optimal therapeutic efficiency.


第二段具体介绍传统检测手段(X线透视)的局限性,并用except for引出现代技术--DNA微阵列技术的介绍。


Traditional diagnostic methods, such as mammography, although very effective, are limited for the fact that locoregional or distant metastasis may have already taken place before breast cancer diagnosis (O’Donoghue et al., 2014; Jafari t al., 2018). To achieve much ideal diagnostic efficiency, research groups have focused on biomarkers based on blood and saliva, which will facilitate detection of BRCA in its infancy before it has spread beyond the primary site (Duffy et al., 2015). Except for the traditional laboratory techniques, the DNA microarray technology has also been widely used to analyze gene expression among breast cancer patients.


第三段介绍机器学习技术在诊断乳腺癌中的应用,引出生信技术在肿瘤诊断中的价值。通过该引文,我们还可以加深对临床的认识,结合临床实践中的病例、检查检验技术,对生信也能更好地掌握。


Currently, the machine learning approaches have been utilized to help identify the genomic profiles among different breast cancer survivors who undergo varying treatment types (Cardoso et al., 2016; Tabl et al., 2018, 2019; Zeng et al., 2018). For example, Tabl et al. (2018) adopted improved learning approaches for breast cancer analysis. An unsupervised learning approach was implemented to find the separation between the treatment-survival groups of classes. And a newly hierarchical machine learning system was introduced to help predict the 5-year survivability of the patients undergoing although specific type of therapy (Tabl et al., 2019). Analyzing the genomic profiles of breast cancers contributes to a better understanding of the disease’s progression and the body response to the treatment. Therefore, the bioinformatic analysis could provide clues to find biomarkers in breast cancer and help personalize the treatment based on the patients’ gene expression. 


第四段介绍LCN家族基因的生理功能及其在肿瘤中的作用,最后引出LCN1在肿瘤中的作用研究较少,提出科学问题。


Lipocalins (LCNs) are a family of proteins that are involved in the transport of steroids and lipids into cells. LCN2 is thought to be involved in multiple cellular processes, including maintenance of skin homeostasis, and suppression of invasiveness and metastasis (Lee et al., 2008; Venge et al., 2015; Xiao et al., 2017). Upregulation of LCN2 had been observed in multiple cancers, including breast cancer, cholangiocarcinoma, lung cancer, esophageal cancer, pancreatic
cancer, prostate cancer, and some other cancers (Leng et al., 2011; Song et al., 2015; Chiang et al., 2016; Ding et al., 2016; Gomez-Chou et al., 2017; Meng et al., 2017; Celestino t al., 2018). Studies have indicated that LCN2 can be an important regulator of tumorigenesis and metastasis and regarded as a newly identified biomarker and a potential therapeutic target for BRCA (Leng et al., 2011; Oren et al., 2016).
However, studies on function of LCN1, another member of the LCN superfamily, are relative less. 


第五段介绍LCN1基因的功能,探讨其在肿瘤中的相关研究,进一步引出其肿瘤中研究较少的主题。


Researchers have suggested that LCN1 is produced exclusively by a number of exocrine glands and tissues, including lachrymal and lingual glands, prostate, secretory glands of the tracheobronchial tract, sweat gland, and pituitary gland (Holzfeind et al., 1997; Wojnar et al., 2002). Thus, LCN1 can be expressed in tears, lingual sweat, and lower airway glands, and it can be detected in bronchoalveolar lavage fluid and saliva. Taking these facts together, LCN1 might be a potential biomarker to indicate physiological or pathological disturbance. Some studies have proved that LCN1 can function as a physiological scavenger of potentially harmful lipophilic molecules, act as a cysteine proteinase inhibitor, and play antimicrobial activities (Redl et al., 1998; Redl, 2000; Lechner et al., 2001; Wojnar et al., 2002). However, researches on LCN1 were relatively rare, and the precise biological function of LCN1 has not been fully characterized.

第六段解决问题,差异分析、组学改变、相关性分析和生存分析,非常调理。遗憾的是,作者没有进行免疫浸润分析。


Currently, the relevance of LCN1 function with the tumorigenesis is still unknown. In our previous study on biomarker screening, we found that LCN1 level was abnormally downregulated in salivary sample of subjects with breast cancer compared with the healthy controls through isobaric tags for relative and absolute quantitation. To further address the correlation of LCN1 with BRCA, bioinformatic analysis was performed in this study. LCN1 expression in BRCA was assessed through TIMER and UALCAN databases. Meanwhile, genetic alterations of LCN1 were analyzed by cBioPortal database, and the correlation between somatic copy number alterations (SCNAs) of LCN1 and immune cell enrichments in BRCA was also analyzed by GISTIC 2.0. In addition, affection of LCN1 expression on the survival for breast cancer patients was also predicted by Kaplan–Meier plotter. Thus, the purpose of this study was to evaluate the potential role of LCN1 to be a biomarker for BRCA diagnosis.




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