Noninvasive photoacoustic computed tomography/ultrasound imaging to identify high-risk atherosclerotic plaques.

PURPOSE: Noninvasive detection of high-risk plaques is still challenging. In this study, we aimed to noninvasively assess αvß3-integrin expression using a customed photoacoustic (PA) computed tomography (PACT)/ultrasound (US) system in atherosclerotic lesions of varying degrees of severity and to explore its potential value for detecting high-risk plaques. METHODS: We constructed αvß3-integrin-targeted ultrasmall gold nanorods (AuNRs) with cyclo Arg-Gly-Asp (cRGD) and tested their properties. Employing C57BL/6 J (wild-type, WT) mice and apolipoprotein E gene knockout (ApoE-/-) mice fed either a chow diet or a high-fat/high-cholesterol diet (HFHCD), we established varying degrees of lesion severity. In vivo PACT/US imaging was performed to assess αvß3-integrin expression in the 4 groups by cRGD-AuNRs. Further histopathologic examination was conducted to evaluate the plaque vulnerability indicators. RESULTS: The data showed that cRGD-AuNRs exhibited excellent photothermal conversion capacity, stability, targeting ability, and biocompatibility. The immunohistochemical results indicated that αvß3-integrin was upregulated with increasing aggravation of the lesions. In vivo PACT/US imaging showed good consistency with αvß3-integrin expression. Notably, ApoE-/- mice fed a HFHCD showed an abrupt PA intensity increase compared with the other groups. The histopathologic examination verified that the atherosclerotic plaques of ApoE-/- mice fed the HFHCD developed unstable phenotypes. Correlation analysis showed that PA intensity was mainly related to inflammation and angiogenesis among all of the indicators. CONCLUSION: Our data indicated that αvß3-integrin is an effective indicator of plaque instability, and noninvasive PACT/US molecular imaging assessment of αvß3-integrin holds promise in detecting high-risk plaques.

Global computational alignment of tumor and cell line transcriptional profiles.

Cell lines are key tools for preclinical cancer research, but it remains unclear how well they represent patient tumor samples. Direct comparisons of tumor and cell line transcriptional profiles are complicated by several factors, including the variable presence of normal cells in tumor samples. We thus develop an unsupervised alignment method (Celligner) and apply it to integrate several large-scale cell line and tumor RNA-Seq datasets. Although our method aligns the majority of cell lines with tumor samples of the same cancer type, it also reveals large differences in tumor similarity across cell lines. Using this approach, we identify several hundred cell lines from diverse lineages that present a more mesenchymal and undifferentiated transcriptional state and that exhibit distinct chemical and genetic dependencies. Celligner could be used to guide the selection of cell lines that more closely resemble patient tumors and improve the clinical translation of insights gained from cell lines.

Identification of Transcriptional Variation in Aortic Remodeling Using a Murine Transverse Aortic Constriction (TAC) Model.

Arterial remodeling is a major pathological consequence of hypertension, which is recognized as the most common chronic non-communicable disease. However, the detailed mechanism of how arterial remodeling is induced by hypertension has not yet been fully elucidated. Evaluating the transcriptional changes in arterial tissue in response to elevated blood pressure at an early stage may provide new insights and identify novel therapeutic candidates in preventing arterial remodeling. Here, we used the ascending aorta of the transverse aortic constriction (TAC) model to induce arterial remodeling in C57BL/6 male mice. Age-matched mice were subjected to sham surgery as controls. The TAC model was only considered successful if the mice conformed to the criteria (RC/LC blood flow velocity with 5-10-fold change) 1 week after the surgery. Two weeks after surgery, the ascending aorta developed severe remodeling in TAC mice as compared to the sham group. High throughput sequencing was then applied to identify differentially expressed (DE) transcripts. In silicon analysis were then performed to systematically network transcriptional changes. A total of 1,019 mRNAs were significantly changed between TAC and the sham group at the transcriptional level. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis revealed that stress/stimulus/immune-related biological processes played a crucial role during arterial remodeling. Our data provide a comprehensive understanding of global gene expression changes in the TAC model, which suggests that targeting inflammation and vascular smooth cell transformation are potential therapeutic strategies to interfere with the aortic remodeling at an early stage in the development of hypertension.

Discovering the anti-cancer potential of non-oncology drugs by systematic viability profiling.

Anti-cancer uses of non-oncology drugs have occasionally been found, but such discoveries have been serendipitous. We sought to create a public resource containing the growth inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. We used PRISM, a molecular barcoding method, to screen drugs against cell lines in pools. An unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines in a manner predictable from the cell lines' molecular features. Our findings include compounds that killed by inducing PDE3A-SLFN12 complex formation; vanadium-containing compounds whose killing depended on the sulfate transporter SLC26A2; the alcohol dependence drug disulfiram, which killed cells with low expression of metallothioneins; and the anti-inflammatory drug tepoxalin, which killed via the multi-drug resistance protein ABCB1. The PRISM drug repurposing resource (https://depmap.org/repurposing) is a starting point to develop new oncology therapeutics, and more rarely, for potential direct clinical translation.