MicroRNAs (miRNAs) have been implicated to play key roles in normal physiological functions, and altered expression of specific miRNAs has been associated with a number of diseases. It is of great interest to understand their roles and a prerequisite for such study is the ability to comprehensively and accurately assess the levels of the entire repertoire of miRNAs in a given sample. It has been shown that some miRNAs frequently have sequence variations termed isomirs. To better understand the extent of miRNA sequence heterogeneity and its potential implications for miRNA function and measurement, we conducted a comprehensive survey of miRNA sequence variations from human and mouse samples using next generation sequencing platforms. Our results suggest that the process of generating this isomir spectrum might not be random and that heterogeneity at the ends of miRNA affects the consistency and accuracy of miRNA level measurement. In addition, we have constructed a database from our sequencing data that catalogs the entire repertoire of miRNA sequences (http://galas.systemsbiology. net/cgi-bin/isomir/find.pl). This enables users to determine the most abundant sequence and the degree of heterogeneity for each individual miRNA species. This information will be useful both to better understand the functions of isomirs and to improve probe or primer design for miRNA detection and measurement.
Each year millions of pulmonary nodules are discovered by computed tomography and subsequently biopsied. As the majority of these nodules are benign, many patients undergo unnecessary and costly invasive procedures. We present a 13-protein blood-based classifier that differentiates malignant and benign nodules with high confidence, thereby providing a diagnostic tool to avoid invasive biopsy on benign nodules. Using a systems biology strategy, 371 protein candidates were identified and a multiple reaction monitoring (MRM) assay was developed for each. The MRM assays were applied in a three-site discovery study (n = 143) on plasma samples from patients with benign and Stage IA cancer matched on nodule size, age, gender and clinical site, producing a 13-protein classifier. The classifier was validated on an independent set of plasma samples (n = 104), exhibiting a high negative predictive value (NPV) of 90%. Validation performance on samples from a non-discovery clinical site showed NPV of 94%, indicating the general effectiveness of the classifier. A pathway analysis demonstrated that the classifier proteins are likely modulated by a few transcription regulators (NF2L2, AHR, MYC, FOS) that are associated with lung cancer, lung inflammation and oxidative stress networks. The classifier score was independent of patient nodule size, smoking history and age, which are risk factors used for clinical management of pulmonary nodules. Thus this molecular test can provide a powerful complementary tool for physicians in lung cancer diagnosis.
PURPOSE Although the majority of patients with relapsed or refractory large B-cell lymphoma respond to axicabtagene ciloleucel (axi-cel), only a minority of patients have durable remissions. This prospective multicenter study explored the prognostic value of circulating tumor DNA (ctDNA) before and after standard-of-care axi-cel for predicting patient outcomes. METHODS Lymphoma-specific variable, diversity, and joining gene segments (VDJ) clonotype ctDNA sequences were frequently monitored via next-generation sequencing from the time of starting lymphodepleting chemotherapy until progression or 1 year after axi-cel infusion. We assessed the prognostic value of ctDNA to predict outcomes and axi-cel–related toxicity. RESULTS A tumor clonotype was successfully detected in 69 of 72 (96%) enrolled patients. Higher pretreatment ctDNA concentrations were associated with progression after axi-cel infusion and developing cytokine release syndrome and/or immune effector cell–associated neurotoxicity syndrome. Twenty-three of 33 (70%) durably responding patients versus 4 of 31 (13%) progressing patients demonstrated nondetectable ctDNA 1 week after axi-cel infusion ( P < .0001). At day 28, patients with detectable ctDNA compared with those with undetectable ctDNA had a median progression-free survival and OS of 3 months versus not reached ( P < .0001) and 19 months versus not reached ( P = .0080), respectively. In patients with a radiographic partial response or stable disease on day 28, 1 of 10 patients with concurrently undetectable ctDNA relapsed; by contrast, 15 of 17 patients with concurrently detectable ctDNA relapsed ( P = .0001). ctDNA was detected at or before radiographic relapse in 29 of 30 (94%) patients. All durably responding patients had undetectable ctDNA at or before 3 months after axi-cel infusion. CONCLUSION Noninvasive ctDNA assessments can risk stratify and predict outcomes of patients undergoing axi-cel for the treatment of large B-cell lymphoma. These results provide a rationale for designing ctDNA-based risk-adaptive chimeric antigen receptor T-cell clinical trials.
A detailed analysis of Monte Carlo data on the two-dimensional Ising spin glass with bimodal interactions shows that the free energy of the model has a nontrivial scaling. In particular, we show by studying the correlation length that much larger system sizes and lower temperatures are required to see the true critical behavior of the model in the thermodynamic limit. Our results agree with data by Lukic et al. in that the degenerate ground state is separated from the first excited state by an energy gap of 2J.
Multiple reaction monitoring (MRM) is a highly sensitive method of targeted mass spectrometry (MS) that can be used to selectively detect and quantify peptides based on the screening of specified precursor peptide-to-fragment ion transitions. MRM-MS sensitivity depends critically on the tuning of instrument parameters, such as collision energy and cone voltage, for the generation of maximal product ion signal. Although generalized equations and values exist for such instrument parameters, there is no clear indication that optimal signal can be reliably produced for all types of MRM transitions using such an algorithmic approach. To address this issue, we have devised a workflow functional on both Waters Quattro Premier and ABI 4000 QTRAP triple quadrupole instruments that allows rapid determination of the optimal value of any programmable instrument parameter for each MRM transition. Here, we demonstrate the strategy for the optimizations of collision energy and cone voltage, but the method could be applied to other instrument parameters, such as declustering potential, as well. The workflow makes use of the incremental adjustment of the precursor and product m/z values at the hundredth decimal place to create a series of MRM targets at different collision energies that can be cycled through in rapid succession within a single run, avoiding any run-to-run variability in execution or comparison. Results are easily visualized and quantified using the MRM software package Mr. M to determine the optimal instrument parameters for each transition.
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