A new computational framework has revealed key differences between four rheumatoid arthritis medications and their impact on biological pathways in mice. Niki Karagianni of Biomedcode Hellas SA, Greece, and colleagues present their new approach and findings in PLOS Computational Biology. People with rheumatoid arthritis often receive medications that target and inhibit Tumor-Necrosis Factor (TNF), a protein involved in the painful and damaging inflammation characteristic of the disease. While several anti-TNF drugs are used widely with comparable clinical success, the details of their different molecular effects on biological processes have been unclear. To fill this gap, Karagianni and colleagues employed a mouse model of chronic inflammatory polyarthritis—mice that express the human TNF and develop symptoms and signatures that closely mirror the human form of the disease. The diseased mice received treatment with one of four anti-TNF drugs (Remicade, Cimzia, Humira, or Enbrel), or for comparison, none of the drugs. The researchers then compared them to healthy mice. After treatment, the researchers collected joint tissue from all the mice and analyzed their transcriptomes—the complete set of messenger RNA molecules in the tissues, which indicates which genes are turned on or off. Then, they applied a series of computational steps to the transcriptome data in order to compare the effects of the four different drugs. The analysis revealed previously unknown differences in the way the four drugs affect gene expression in diseased mice. Some of these differences were found for genes directly involved in arthritis, but many were found in non-arthritis-related genes, such as genes involved in cardiovascular disease and other conditions that may occur alongside arthritis. "Perhaps the most important result to come out of our study is the large number of down-regulated genes in the diseased animals, which are associated with functions and pathways that were until recently largely overlooked," says study co-author Christoforos Nikolaou. "These could provide additional insight into arthritis pathology mechanisms." The new computational framework developed for this study could be repurposed for detailed comparisons of other drugs in other diseases. To help facilitate this, the researchers are working to organize the system into an automated, standalone package.详情>>

2019-05-13 00:00:00


Rheumatic diseases have complex aetiologies that are not fully understood, which makes the study of pathogenic mechanisms in these diseases a challenge for researchers. Next-generation sequencing (NGS) and related omics technologies, such as transcriptomics, epigenomics and genomics, provide an unprecedented genome-wide view of gene expression, environmentally responsive epigenetic changes and genetic variation. The integrated application of NGS technologies to samples from carefully phenotyped clinical cohorts of patients has the potential to solve remaining mysteries in the pathogenesis of several rheumatic diseases, to identify new therapeutic targets and to underpin a precision medicine approach to the diagnosis and treatment of rheumatic diseases. This Review provides an overview of the NGS technologies available, showcases important advances in rheumatic disease research already powered by these technologies and highlights NGS approaches that hold particular promise for generating new insights and advancing the field.展开>><<收起

Nature Reviews Rheumatology,Published: 18 April 2019  0


Background Localized Scleroderma (LoS) encompasses a group of idiopathic skin conditions characterized by (sub)cutaneous inflammation and subsequent development of fibrosis. Currently, lack of accurate tools enabling disease activity assessment leads to suboptimal treatment approaches. Objective To investigate serum concentrations of cytokines and chemokines implicated in inflammation and angiogenesis in LoS and explore their potential to be utilized as biomarker of disease activity. Additionally, to investigate the implication of potential biomarkers in disease pathogenesis. Methods A 39-plex Luminex immuno-assay was performed in serum samples of 74 LoS and 22 Healthy Controls. The relation between a validated clinical measure of disease activity (mLoSSI) and serum analytes was investigated. Additionally, gene and protein expression were investigated in circulating cells and skin biopsies. Results From the total of 39, 10 analytes (CCL18, CXCL9, CXCL10, CXCL13, TNFRII, Galectin-9, TIE-1, sVCAM, IL-18, CCL19) were elevated in LoS serum. Cluster analysis of serum samples revealed CCL18 as most important analyte to discriminate between active and inactive disease. At individual patient level, CCL18 serum levels correlated strongest with mLoSSI-scores (rs = 0.4604, P < 0.0001) and in longitudinal measures CCL18 concentrations normalised with declining disease activity upon treatment initiation. Additionally, CCL18 was elevated in LoS serum, and not in (juvenile) dermatomyositis or spinal muscular atrophy. Importantly, CCL18 gene and protein expression was increased at the inflammatory border of cutaneous LoS lesions, with normal expression in unaffected skin and circulating immune cells. Conclusion CCL18 is specific for disease activity in LoS thereby providing relevance as a biomarker for this debilitating disease.展开>><<收起

Journal of Autoimmunity,Available online 18 April 2019  0
精准抗癌疗法递交IPO申请 拟助推新药进入2期临床

新闻精准抗癌疗法递交IPO申请 拟助推新药进入2期临床

继2018年10月完成8000万美元的夹层融资(mezzanine financing)之后,Turning Point Therapeutics日前申请纳斯达克上市,拟募集1亿美元的资金。该公司表示,将利用IPO资金推进其主打候选药物repotrectinib进入2期临床,并推进另外两款候选药物进入早期临床。 Turning Point Therapeutics于2013年10月创立,专注于精准抗癌疗法的研发,正在开发新一代激酶抑制剂,用于治疗对现有的激酶抑制剂产生抗药性的肿瘤。截至目前,该公司已融资近1.48亿美元。这家公司的科学创始人(scientific founder)崔景荣博士(J. Jean Cui)是两款精准抗肿瘤药物克唑替尼(crizotinib)与lorlatinib的主要发明人。前者已于2011年获美国FDA批准上市,治疗带有ALK突变的非小细胞肺癌。后者于2018年11月获FDA批准上市,用于治疗ALK阳性转移性非小细胞肺癌。 公司科学创始人(scientific founder)崔景荣博士(J. Jean Cui)(图片来源:Turning Point Therapeutics官网) 该公司的在研产品repotrectinib是一款充满潜力的药物。这是一款ROS1/TRKs/ALK抑制剂,有潜力治疗ROS1阳性的非小细胞肺癌,以及NTRK阳性的实体瘤。这款新药已于2017年获得了美国FDA颁发的孤儿药资格。据该公司的研究计划,2期临床将招募已接受酪氨酸激酶抑制剂(TKI)却出现耐药,或是难治的癌症患者。此外,该研究也计划招募没有接受过TKI治疗的患者。如果研究结果顺利,对于这些患者而言将是一大利好。 该公司表示,IPO资金还将用于推进临床前项目TPX-0046(一种RET抑制剂)和TPX-0022(一种双重CSF1R / MET抑制剂)的开发,这两款药物都将在今年下半年进入临床。该公司尚未披露这两款药物所针对的癌种。另外,IPO资金还将用于支持ALK抑制剂的开发,该公司目前正在选择递交IND申请的ALK候选产品。 Turning Point Therapeutics研发管线(图片来源:Turning Point Therapeutics官网) 我们祝愿Turning Point Therapeutics上市顺利,也期待其临床研发之旅在资本的助力下一切顺利,早日为全球患者带来更多精准抗癌新药! 参考资料: [1] Turning Point Therapeutics Files Registration Statement for Proposed Initial Public Offering Retrieved on March 25 2019 from https://www.businesswire.com/news/home/20190321005775/en/Turning-Point-Therapeutics-Files-Registration-Statement-Proposed [2] 祝贺!8000万美元助推精准抗癌疗法,TP Therapeutics完成融资 Retrieved on March 25 2019 from 创鉴汇详情>>

2019-03-26 00:00:00


【新闻事件】:今天Sarepta公布了其2E亚型肢带型肌营养不良症(LGMD2E)基因疗法MYO-101的第一批三位患者的生物标记数据。输入5x1013vg/kg的MYO-101后60天三位患者该基因表达蛋白 beta sarcoglycan在42-63%的肌纤维中表达、平均为51%,而20%即认为临床有意义。用蛋白免疫印迹测量该蛋白水平为正常值的36%,一个肌肉损伤标记肌酸激酶的水平则下降了90%。据估计详细结果将在四月举行的MDA 会议上公布。受此消息影响今天SRPT上扬8%。 【药源解析】:LGMD和DMD类似都是单基因肌肉损伤疾病,与DMD不同的是男孩女孩都可能得LGMD、而DMD只有男孩会有症状。估计现在全球有20-30万LGMD患者,共有5个亚型。LGMD2E是比较严重的一种,除了肌肉、心血管和呼吸系统也受到影响,患者平均寿命为30岁左右。这个数据是一个一二期临床的一个人群,整个试验共有9位4-15岁患者。今天这个结果虽然令人兴奋,但现在只是短期数据,而基因疗法的持久性是一个关键不确定性。这个蛋白表达是否能够转化为功能改善也还有待研究。另外两位患者出现转氨酶上升,但是可逆的。对于只需一针的基因疗法来说这个副作用可能不足为惧。 这个产品是SRPT去年从Myonexus以6000万收购而来,这个小公司还有其它几个亚型LGMD的基因疗法。今天的数据公布前一个小时SRPT也宣布将以1.65亿收购Myonexus,而这个公司2017年成立时只有250万的启动基金。这个公司的技术平台来自俄亥俄的一个儿童医院,发明人Louise Rodino-Klapac也是SRPT去年引起轰动的DMD基因疗法发明人之一,这两个疗法所用的病毒载体(AAVrh74)和启动子(MHCK7)都一样。使用这个系统的DMD基因疗法去年令三位6岁以下DMD儿童患者肌营养蛋白水平达到正常水平的38%(用另一种定量方法测为正常值的53%),这远超投资者预期的5-10%正常值水平、更是比SRPT上市的反译核酸药物Exondys 51的不到1%蛋白水平高很多。这个DMD药物令血液肌酸酐激酶水平比用药前下降87%。 SRPT最早的技术平台是反译核酸,主打产品Exondys 51虽然只产生正常水平0.3%左右的肌营养蛋白,但在患者家属声泪俱下和当时FDA新药部主任Woodcock的铁腕支持下成功上市,令SRPT获得了进入基因疗法的宝贵资本和时间。当时Woodcock支持的一个理由是如果不批准,Sarepta可能会破产,DMD新药会更加遥遥无期。现在SRPT市值已经达到100亿美元,AAVrh74.MHCK7系统看来对肌肉疾病治疗非常有效,SRPT有望成为这个市场的霸主,Woodcock当时颇有争议的决策现在看有点高瞻远瞩的味道。而昨天提到的KPTI则没有这样运气、或者没有这样高水平的执行,主打产品上市被推迟、生存都成为问题。新药赛场不只是技术一个人在战斗。 基因疗法现在快速成熟,很多大公司已经开始涉足这个新技术。诺华、罗氏先后以87、48亿收购了Avexis和Spark,其它大药厂也以合作形式进入这个领域。基因疗法在最根源解决蛋白的生产问题、可以把不存在的正常蛋白在细胞中合成,这与传统药物只改变已有蛋白活性(主要是降低活性)的技术有本质区分。虽然酶替代疗法可以达到类似效果,但很多疾病酶替代疗法不适用、使用也不方便。基因疗法虽然也有一些不确定性,但这个技术带来的希望已经触手可及。基因疗法令失明的孩子看见星空和彩虹,令注定要瘫痪的SMA患者可以做俯卧撑,Exondys 51听证会上患者母亲“approve this drug so he can hug me”的绝望请求也有望被基因疗法真正实现。科学技术不愧是第一生产力。详情>>

2019-03-04 00:00:00


Researchers at Johns Hopkins Medicine say they have added to evidence that rapid resistance gene sequencing technology can accurately speed the identification of specific antibiotic-resistant bacteria strains that sicken and kill some patients. A report on a proof of concept study, published in the January 2019 issue of Antimicrobial Agents and Chemotherapy, suggests the technology has the potential to hasten the "personalized" choice of antibiotics critically ill patients need. "Delays in prescribing effective antibiotic therapy for drug-resistant infections increase the risk of poor outcomes," says Pranita Tamma, M.D., M.H.S., associate professor of pediatrics at Johns Hopkins Children's Center and one of the study authors. "The current standard process of identifying appropriate treatment options for highly drug-resistant bacteria can take up to 96 hours from the time the lab receives samples, but our findings suggest that with the use of a rapid whole genome sequencing method, we might reduce that time to about one day less," Tamma adds. Tamma notes that drug-resistant bacterial infections are rising dramatically, in great part due to the overuse of antibiotic drugs and in part to the ease with which bacteria can acquire new resistance genes from other bacterial strains or species, especially in hospital settings where different strains might intermingle. Efforts to develop new antibiotics are underway but are limited, Tamma says. The U.S. Centers for Disease Control and Prevention estimates that each year at least 2 million people develop an antibiotic-resistant infection, and at least 23,000 people die from them. Currently, typical laboratory tests to identify specific bacterial strains require 24 hours to grow the microbial culture sampled from patients, plus an additional 24 to 48 hours to determine which commonly used antibiotics would be effective against it. For bacteria resistant to multiple drugs, further tests may require an additional 24 to 48 hours more to determine what antibiotics of last resort can eradicate the infection. For years, scientists have been able to screen bacterial genomes for specific antibiotic-resistant genes, a laborious and protracted process until the recent advent of newer technologies able to sequence and analyze bacterial genomes within hours. These technologies also offer fast ways to identify exactly what type of resistant genes the pathogens contain. In their study designed to test the proof of concept of such methods, Tamma and Patricia J. Simner, Ph.D., D.(A.B.M.M.), the senior author of the study and an associate professor of pathology and medical microbiology at the John Hopkins University School of Medicine, used a nanopore DNA sequencer--a newer type of technology that gives results much faster than other DNA sequencing tools as it measures an electrical signal when a string of DNA moves through a tiny pore (i.e., nanopore). The electrical signal is monitored in real time, allowing for analysis of sequencing results within minutes. Other sequencers require a minimum of 24 hours before result analysis can take place. The researchers used the new sequencer to spot antibiotic resistance genes in several strains of Klebsiella pneumoniae, bacteria that may harmlessly dwell in the human intestinal tract, but can cause serious infections if they enter the bloodstream, the urinary tract or lungs. While all typical strains of K. pneumoniae can be treated with common antibiotics such as ceftriaxone, those with acquired antibiotic-resistant genes can turn dangerous and deadly. Those most at risk are hospitalized, have been exposed repeatedly to antibiotics, or are coming from parts of the world known for high antibiotic resistance rates. The team collected clinical samples that grew K. pneumoniae in culture from 40 adult patients hospitalized at The Johns Hopkins Hospital, extracted the bacterial DNA, and ran the DNA through the nanopore sequencer. The researchers used two different approaches to spotting the antibiotic resistance genes. A real-time analysis approach, which let researchers comb through the already sequenced genome parts while the rest of the DNA was still being read, revealed resistance genes within eight hours. An assembly-based approach took 14 hours, but proved to be more accurate and less prone to errors. The real-time approach correctly identified K. pneumoniae resistance genes and mutations in 77 percent of cases and the assembly-based one in 92 percent. "While we still need to wait 24 hours to get the culture to grow, we were able to cut time to identifying effective antibiotic therapy by at least 20 hours, compared to our current standard of care," says Simner. The team also believes that further automation of sample preparation could reduce the wait for optimal therapy. Tamma and Simner caution that their study does not mean the technology is ready for clinical use, or that it will prove to be less expensive or cost-effective. The study was limited by a small sample size and only one bacterial organism. Further studies are needed to test the new sequencer's value with other bacteria, and the methods applied still need refinements to make it easily useful in clinical settings. Tamma says their findings are a logical outgrowth of the commitment to precision, or personalized, medicine, which uses genetic specificity to guide treatment for patients with infections, cancer, heart disease and other disorders.详情>>

2019-01-22 00:00:00


最近发表在Nature Genetics上的最全面的全基因组关联研究(GWAS)结果发现了40种新的与结肠癌的风险增加有关的遗传变异。 由Fred Hutchinson癌症研究中心的一个研究小组领导的这项研究同时确定了第一种罕见的散发性结直肠癌保种。总之,这些发现对于创建个性化筛查策略和更好地为结直肠癌的药物开发提供了重要的信息。 这些研究结果也阐明了研究作者在药物开发中所谓的“错失机会”。作者认为,使用GWAS结果为癌症药物开发提供信息可以提高药物开发成功率,甚至可以为高风险人群提供化学预防药物。 “使用GWAS结果为抗癌药物的靶点发现提供了很大的潜力。对于2型糖尿病和心脏病等疾病,GWAS方法推动了新生物学和潜在药物靶点的发现,”该研究的作者,Jeroen Huyghe博士解释说:“迄今为止,对癌症治疗新目标的研究主要集中在癌症细胞的分子特征上。我们认为使用GWAS方法为结直肠癌的药物开发提供了一个巨大的机会。” Huyghe解释说:“大规模的全基因组测序研究已经发现了数百种尚未系统检查与疾病相关的遗传变异。我们的研究充分利用了Haplotype Reference Consortium面板的可用性,该面板是来自超过32,000个个体的序列数据的群体参考面板。通过将该策略与定制设计的基因分型芯片相结合,我们能够稳健地识别罕见的变异关联信号以及涉及低频变种的多个附加信号。“ 之前针对结直肠癌风险的GWAS仅考察了常见的遗传变异。相比之下,这项研究涉及超过2,000个人的全基因组测序,旨在检查罕见遗传变异对结直肠癌风险的贡献。 “通过这项研究,我们已经将已知数量的结直肠癌风险变种带到了近100个,”该研究的共同第一作者,Fred Hutch的遗传流行病学家Tabitha Harrison说。 “接下来,我们将研究人群扩大到包括来自不同种族背景的人。这将使我们更全面地了解整个人口的风险。” 资讯出处:Study discovers 40 new genetic variants associated with colorectal cancer risk 原始出处:Jeroen R. Huyghe et al, Discovery of common and rare genetic risk variants for colorectal cancer, Nature Genetics (2018). DOI: 10.1038/s41588-018-0286-6详情>>

2018-12-07 00:00:00


BACKGROUND Many patients remain without a diagnosis despite extensive medical evaluation. The Undiagnosed Diseases Network (UDN) was established to apply a multidisciplinary model in the evaluation of the most challenging cases and to identify the biologic characteristics of newly discovered diseases. The UDN, which is funded by the National Institutes of Health, was formed in 2014 as a network of seven clinical sites, two sequencing cores, and a coordinating center. Later, a central biorepository, a metabolomics core, and a model organisms screening center were added. METHODS We evaluated patients who were referred to the UDN over a period of 20 months. The patients were required to have an undiagnosed condition despite thorough evaluation by a health care provider. We determined the rate of diagnosis among patients who subsequently had a complete evaluation, and we observed the effect of diagnosis on medical care. RESULTS A total of 1519 patients (53% female) were referred to the UDN, of whom 601 (40%) were accepted for evaluation. Of the accepted patients, 192 (32%) had previously undergone exome sequencing. Symptoms were neurologic in 40% of the applicants, musculoskeletal in 10%, immunologic in 7%, gastrointestinal in 7%, and rheumatologic in 6%. Of the 382 patients who had a complete evaluation, 132 received a diagnosis, yielding a rate of diagnosis of 35%. A total of 15 diagnoses (11%) were made by clinical review alone, and 98 (74%) were made by exome or genome sequencing. Of the diagnoses, 21% led to recommendations regarding changes in therapy, 37% led to changes in diagnostic testing, and 36% led to variant-specific genetic counseling. We defined 31 new syndromes. CONCLUSIONS The UDN established a diagnosis in 132 of the 382 patients who had a complete evaluation, yielding a rate of diagnosis of 35%. (Funded by the National Institutes of Health Common Fund.)展开>><<收起

N Engl J Med 2018; 379:2131-2139  0


Osteoarthritis has a highly negative impact on quality of life because of the associated pain and loss of joint function. Here we describe the largest meta-analysis so far of osteoarthritis of the hip and the knee in samples from Iceland and the UK Biobank (including 17,151 hip osteoarthritis patients, 23,877 knee osteoarthritis patients, and more than 562,000 controls). We found 23 independent associations at 22 loci in the additive meta-analyses, of which 16 of the loci were novel: 12 for hip and 4 for knee osteoarthritis. Two associations are between rare or low-frequency missense variants and hip osteoarthritis, affecting the genes SMO (rs143083812, frequency 0.11%, odds ratio (OR) = 2.8, P = 7.9 × 10−12, p.Arg173Cys) and IL11 (rs4252548, frequency 2.08%, OR = 1.30, P = 2.1 × 10−11, p.Arg112His). A common missense variant in the COL11A1 gene also associates with hip osteoarthritis (rs3753841, frequency 61%, P = 5.2 × 10–10, OR = 1.08, p.Pro1284Leu). In addition, using a recessive model, we confirm an association between hip osteoarthritis and a variant of CHADL1 (rs117018441, P = 1.8 × 10−25, OR = 5.9). Furthermore, we observe a complex relationship between height and risk of osteoarthritis.展开>><<收起

Nature Geneticsvolume 50, pages1681–1687 (2018)  0


Autoimmune rheumatic diseases are characterised by an abnormal immune system response, complement activation, cytokines dysregulation and inflammation. In last years, despite many progresses in managing these patients, it has been shown that clinical remission is reached in less than 50% of patients and a personalised and tailored therapeutic approach is still lacking resulting in a significant gap between guidelines and real-world practice. In this context, the need for biomarkers facilitating early diagnosis and profiling those individuals at the highest risk for a poor outcome has become of crucial interest. A biomarker generally refers to a measured characteristic which may be used as an indicator of some biological state or condition. Three different types of medical biomarkers has been suggested: i. mechanistic markers; ii. clinical disease markers; iii. therapeutic markers. A combination of biomarkers from these different groups could be used for an ideal more accurate diagnosis and treatment. However, although a growing body of evidence is focused on improving biomarkers, a significant amount of this information is not integrated on standard clinical care.展开>><<收起

Autoimmunity Reviews,Available online 5 November 2018  0