Identification of primary tumors of brain metastases by SIMCA classification of IR spectroscopic images

Brain metastases are secondary intracranial lesions which occur more frequently than primary brain tumors. The four most abundant types of brain metastasis originate from primary tumors of lung cancer, colorectal cancer, breast cancer and renal cell carcinoma. As metastatic cells contain the molecular information of the primary tissue cells and IR spectroscopy probes the molecular fingerprint of cells, IR spectroscopy based methods constitute a new approach to determine the origin of brain metastases. IR spectroscopic images of 4 by 4 mm2 tissue areas were recorded in transmission mode by a FTIR imaging spectrometer coupled to a focal plane array detector. Unsupervised cluster analysis revealed variances within each cryosection. Selected clusters of five IR images with known diagnoses trained a supervised classification model based on the algorithm soft independent modeling of class analogies (SIMCA). This model was applied to distinguish normal brain tissue from brain metastases and to identify the primary tumor of brain metastases in 15 independent IR images. All specimens were assigned to the correct tissue class. This proof-of-concept study demonstrates that IR spectroscopy can complement established methods such as histopathology or immunohistochemistry for diagnosis.     

Postsynthetic Modification of Oligonucleotides with Imidazophenazine Dye and its Effect on Duplex Stability

Carboxyalkyl derivative of the intercalating agent imidazo[4,5-b]phenazine was used for the postsynthetic oligonucleotide modification. Model pentadecathymidylate-imidazophenazine conjugate was prepared from 5′-aminoalkyl-modified (dT)₁₅ by using phosphonium coupling reagent BOP in the presence of 1-hydroxybenzotriazole. Spectral-fluorescent properties of the conjugate were studied. The attachment of the dye was found to increase the thermal stability of (dT)₁₅ duplex with poly(dA) by more than 4°C, probably by the intercalation mechanism.     

Near-infrared, dual-ratiometric fluorescent label for measurement of pH

We describe the spectral properties of an amine-reactive, pH-sensitive, long-wavelength ratiometric fluorescent label having a pK_a in the physiological pH range. The label exhibits its main absorption and emission in the near-infrared (NIR) region. On deprotonation, a blue shift of the excitation maximum is observed. Importantly, both the protonated and deprotonated forms of the label are fluorescent, with the deprotonated form having an extremely large Stokes shift of more than 100 nm. The spectral and photophysical properties of this pH label are compared with the properties of the protein-conjugated forms. Due to the observed pK_a shift to the acidic pH range upon conjugation to proteins, such labels are ideal for studying phagocytic events and their regulation by drugs and/or environmental factors.     

A framework for prospective,adaptive meta-analysis (FAME) of aggregate data from randomised trials

BackgroundThe vast majority of systematic reviews are planned retrospectively, once most eligible trials have completed and reported, and are based on aggregate data that can be extracted from publications. Prior knowledge of trial results can introduce bias into both review and meta-analysis methods, and the omission of unpublished data can lead to reporting biases. We present a collaborative framework for prospective, adaptive meta-analysis (FAME) of aggregate data to provide results that are less prone to bias. Also, with FAME, we monitor how evidence from trials is accumulating, to anticipate the earliest opportunity for a potentially definitive meta-analysis.MethodologyWe developed and piloted FAME alongside 4 systematic reviews in prostate cancer, which allowed us to refine the key principles. These are to: (1) start the systematic review process early, while trials are ongoing or yet to report; (2) liaise with trial investigators to develop a detailed picture of all eligible trials; (3) prospectively assess the earliest possible timing for reliable meta-analysis based on the accumulating aggregate data; (4) develop and register (or publish) the systematic review protocol before trials produce results and seek appropriate aggregate data; (5) interpret meta-analysis results taking account of both available and unavailable data; and (6) assess the value of updating the systematic review and meta-analysis. These principles are illustrated via a hypothetical review and their application to 3 published systematic reviews.ConclusionsFAME can reduce the potential for bias, and produce more timely, thorough and reliable systematic reviews of aggregate data.

Jayne Tierney and coauthors discuss FAME, an approach for adaptive meta-analysis of data from randomised trials.