Adaptive Global Innovative Learning Environment for Glioblastoma: GBM AGILE

Alexander, Brian M.; Ba, Sujuan; Berger, Mitchel S.; Berry, Donald A.; Cavenee, Webster K.; Chang, Susan M.; Cloughesy, Timothy F.; Jiang, Tao; Khasraw, Mustafa; Li, Wenbin; Mittman, Robert; Poste, George; Wen, Patrick Y.; Yung, W. K. Alfred; Barker, Anna D.

doi:10.1158/1078-0432.ccr-17-0764

Cited by 163 publications

(121 citation statements)

References 23 publications

Supporting

Mentioning

121

Contrasting

Order By: Relevance

“…Grade IV glioma comprises the primary GBM and the secondary glioblastoma from lower grade glioma [37]. GBM, characterized by rapid cell proliferation, is a deadly disease [38,39]. Fortunately, with the development of bioinformatics analysis and medical technology, increasing lncRNAs are detected in GBM and used for the GBM treatment.…”

Section: Discussionmentioning

confidence: 99%

SP1–DLEU1–miR-4429 feedback loop promotes cell proliferative and anti-apoptotic abilities in human glioblastoma

Chen

Liu

2019

Bioscience Reports

View full text Add to dashboard Cite

Mounting studies have revealed that long non-coding RNA (lncRNA) deleted in lymphocytic leukemia 1 (DLEU1) positively regulated the initiation and development of various human malignant tumors. Nevertheless, the function and mechanism of DLEU1 in human glioblastoma multiforme (GBM) remain elusive and ill-defined. The current study was designed to highlight the functional role and disclose the underlying molecular mechanism by which DLEU1 regulated GBM development. We found that DLEU1 was up-regulated in GBM and DLEU1 knockdown significantly inhibited GBM cell proliferation and induced apoptosis. As predicted by bioinformatics analysis and validated in mechanistic assays, SP1 could bind to the promoter region of DLEU1 to activate DLEU1 transcription. Additionally, miR-4429 was verified as a target gene of DLEU1 and negatively modulated by DLEU1. More importantly, miR-4429 overexpression repressed the mRNA and protein levels of SP1 via binding to the 3′UTR of SP1. Overexpression of SP1 or miR-4429 inhibitor could partly abolish the effect of DLEU1 knockdown on cell viability and apoptosis in GBM. Accordingly, our experimental data revealed that SP1–DLEU1–miR-4429 formed a feedback loop to promote GBM development, providing a new evidence for the role of DLEU1 in GBM.

show abstract

Section: Discussionmentioning

confidence: 99%

SP1–DLEU1–miR-4429 feedback loop promotes cell proliferative and anti-apoptotic abilities in human glioblastoma

Chen

Liu

2019

Bioscience Reports

View full text Add to dashboard Cite

show abstract

“…This was followed by the platform trial STAMPEDE, that was first proposed in 2005 [8,9,[18][19][20][21][22][23][24][25][26][27][28]. We identified 68 ongoing master protocols (39 basket trials, 17 umbrella trials, and 12 platform trials) recruiting patients; of these, 11 basket trials [29][30][31][32][33][34][35][36][37][38], eight umbrella trials [39][40][41][42][43][44][45][46], and four platform trials [24,[47][48][49][50] have published results (Appendix Table 10).…”

Section: Trends Of Master Protocolsmentioning

confidence: 99%

“…Two upper-middle-income countries, Brazil and Mexico, were involved in the DIAN-TU platform trial (NCT01760005), but these countries only accounted for three of 36 study sites [48]. China, an upper-middle income country, has centres participating in FUTURE (NCT03805399), GBM AGILE [47,53,54], TRUMP (NCT03574402), and VE-BASKET (NCT01524978) [55,56] trials, but it should be noted that in China only accounts for a minority of study sites in GBM AGILE and VE-BASKET.…”

Section: Geographic Representation Of Master Protocolsmentioning

confidence: 99%

Systematic review of basket trials, umbrella trials, and platform trials: A landscape analysis of master protocols

Mills

Park

Siden

et al. 2019

Preprint

View full text Add to dashboard Cite

Background: Master protocols, classified as basket trials, umbrella trials, and platform trials, are novel designs that investigate multiple hypotheses through concurrent sub-studies (e.g. multiple treatments or populations, or that allow adding/removing arms during the trial), offering enhanced efficiency and a more ethical approach to trial evaluation. Despite the many advantages of these designs, they are infrequently used. Methods: We conducted a landscape analysis of published master protocols using a systematic literature search to determine what trials have been conducted, with an overall goal of improving literacy in this emerging concept. On July 8th, 2019 English-language studies identified from MEDLINE, EMBASE, and CENTRAL databases and hand-searches of published reviews and registries. Results: We identified 83 master protocols (49 basket, 18 umbrella, 16 platform trials). The number of master protocols has increased rapidly over the last five years. Most have been conducted in the US (n=44/83) and investigated experimental drugs (n=82/83), in the field of oncology (n=76/83). The majority of basket trials were exploratory (i.e. phase I/II; n=47/49) and not randomized (n=44/49), with almost half (n=28/48) only investigating a single intervention. The median sample size of basket trials was 205 participants (Interquartile range, Q3-Q1 [IQR]: 500-90=410), with a median study duration of 22.3 (IQR: 74.1-42.9=31.1) months. Similar to basket trials, most umbrella trials were exploratory (n=16/18), but use of randomization was more common (n=8/18). The median sample size of umbrella trials was 346 participants (IQR: 565-252=313), with a median study duration of 60.9 (IQR: 81.3-46.9=34.4) months. The median number of interventions investigated in umbrella trials was 5 (IQR: 6-4=2). In platform trials, randomization (n=15/16) and phase III investigation (n=7/15; one did not report information on phase), with four of them using seamless II/III design, were more common. The median sample size was 892 (IQR: 1835-255=1580), with median study duration of 58.9 (IQR: 101.3-36.9=64.4) months. Conclusions: We anticipate that the number of master protocols will continue to increase at a rapid pace over the upcoming decades. More efforts to improve awareness and training are needed to apply these innovative trial design methods to fields outside of oncology.

show abstract

“…Examples of on-going trials that consider the feature of adding new treatment arm(s) include STAMPEDE, 1 I-spy 2, 2 and Glioblastoma (GBM) AGILE. 3 To date, limited statistical literature on methodology for adding arms is available. Cohen et al 4 provided a review of papers discussing methodology and practical considerations for adding arms to an on-going clinical trial.…”

Section: Introductionmentioning

confidence: 99%

To add or not to add a new treatment arm to a multiarm study: A decision‐theoretic framework

Lee

Wason

Stallard

2019

Statistics in Medicine

View full text Add to dashboard Cite

Multiarm clinical trials, which compare several experimental treatments against control, are frequently recommended due to their efficiency gain. In practise, all potential treatments may not be ready to be tested in a phase II/III trial at the same time. It has become appealing to allow new treatment arms to be added into on‐going clinical trials using a “platform” trial approach. To the best of our knowledge, many aspects of when to add arms to an existing trial have not been explored in the literature. Most works on adding arm(s) assume that a new arm is opened whenever a new treatment becomes available. This strategy may prolong the overall duration of a study or cause reduction in marginal power for each hypothesis if the adaptation is not well accommodated. Within a two‐stage trial setting, we propose a decision‐theoretic framework to investigate when to add or not to add a new treatment arm based on the observed stage one treatment responses. To account for different prospect of multiarm studies, we define utility in two different ways; one for a trial that aims to maximise the number of rejected hypotheses; the other for a trial that would declare a success when at least one hypothesis is rejected from the study. Our framework shows that it is not always optimal to add a new treatment arm to an existing trial. We illustrate a case study by considering a completed trial on knee osteoarthritis.

show abstract

Adaptive Global Innovative Learning Environment for Glioblastoma: GBM AGILE

Cited by 163 publications

References 23 publications

SP1–DLEU1–miR-4429 feedback loop promotes cell proliferative and anti-apoptotic abilities in human glioblastoma

SP1–DLEU1–miR-4429 feedback loop promotes cell proliferative and anti-apoptotic abilities in human glioblastoma

Systematic review of basket trials, umbrella trials, and platform trials: A landscape analysis of master protocols

To add or not to add a new treatment arm to a multiarm study: A decision‐theoretic framework

Contact Info

Product

Resources

About