RESUMO
Phylogenetic reconstruction based on morphometric data is hampered by homoplasies. For example, many similarities in cranial form between primate taxa more strongly reflect ecological similarities rather than phylogenetic relatedness. However, the way in which the different cranial bones constitute cranial form is, if at all, of less functional relevance and thus largely hidden from selection. We propose that these "constructional details" are better indicators of phylogenetic history than any large-scale shape feature or raw form variable. Within a geometric morphometric context, we show how to analyze the relative extent of bones independently of differences in overall shape. We also show how to decompose total shape variation into small-scale and large-scale shape variation. We apply both methods to the midsagittal cranial morphology of papionin monkeys, which are well known for the discrepancy between morphological similarities and phylogenetic relationships. We study phylogenetic signal and functional adaptation using a molecular phylogeny and contextual data on feeding ecology and locomotor behavior. As expected, total cranial shape, bone outline shape, and large-scale shape features were only weakly associated with phylogenetic distance. But the relative bone contributions and small-scale shape features were both highly correlated with phylogenetic distances. By contrast, the association with ecological and behavioral variables was strongest for the outline shape and large-scale shape features. Studies of morphological adaptation and phylogenetic history thus profit from a decomposition of shape variation into different spatial scales. [Adaptation; canalization; cranial shape; geometric morphometrics; papionini; partial warps; phylogeny.].
Assuntos
Evolução Biológica , Crânio , Animais , FilogeniaRESUMO
Tumor neoangiogenesis is an important hallmark of cancer progression, triggered by alternating selective pressures from the hypoxic tumor microenvironment. Non-invasive, non-contrast-enhanced multiparametric MRI combining blood-oxygen-level-dependent (BOLD) MRI, which depicts blood oxygen saturation, and intravoxel-incoherent-motion (IVIM) MRI, which captures intravascular and extravascular diffusion, can provide insights into tumor oxygenation and neovascularization simultaneously. Our objective was to identify imaging markers that can predict hypoxia-induced angiogenesis and to validate our findings using multiplexed immunohistochemical analyses. We present an in vivo study involving 36 female athymic nude mice inoculated with luminal A, Her2+, and triple-negative breast cancer cells. We used a high-field 9.4-tesla MRI system for imaging and subsequently analyzed the tumors using multiplex immunohistochemistry for CD-31, PDGFR-ß, and Hif1-α. We found that the hyperoxic-BOLD-MRI-derived parameter ΔR2* discriminated luminal A from Her2+ and triple-negative breast cancers, while the IVIM-derived parameter fIVIM discriminated luminal A and Her2+ from triple-negative breast cancers. A comprehensive analysis using principal-component analysis of both multiparametric MRI- and mpIHC-derived data highlighted the differences between triple-negative and luminal A breast cancers. We conclude that multiparametric MRI combining hyperoxic BOLD MRI and IVIM MRI, without the need for contrast agents, offers promising non-invasive markers for evaluating hypoxia-induced angiogenesis.
RESUMO
Hyperoxic BOLD-MRI targeting tumor hypoxia may provide imaging biomarkers that represent breast cancer molecular subtypes without the use of injected contrast agents. However, the diagnostic performance of hyperoxic BOLD-MRI using different levels of oxygen remains unclear. We hypothesized that molecular subtype characterization with hyperoxic BOLD-MRI is feasible independently of the amount of oxygen. Twenty-three nude mice that were inoculated into the flank with luminal A (n = 9), Her2+ (n = 5), and triple-negative (n = 9) human breast cancer cells were imaged using a 9.4 T Bruker BioSpin system. During BOLD-MRI, anesthesia was supplemented with four different levels of oxygen (normoxic: 21%; hyperoxic: 41%, 71%, 100%). The change in the spin-spin relaxation rate in relation to the normoxic state, ΔR2*, dependent on the amount of erythrocyte-bound oxygen, was calculated using in-house MATLAB code. ΔR2* was significantly different between luminal A and Her2+ as well as between luminal A and triple-negative breast cancer, reflective of the less aggressive luminal A breast cancer's ability to better deliver oxygen-rich hemoglobin to its tissue. Differences in ΔR2* between subtypes were independent of the amount of oxygen, with robust distinction already achieved with 41% oxygen. In conclusion, hyperoxic BOLD-MRI may be used as a biomarker for luminal A breast cancer identification without the use of exogenous contrast agents.