The pH Low Insertion Peptide pHLIP Variant 3 as a Novel Marker of Acidic Malignant Lesions

Current strategies for early detection of breast and other cancers are limited in part because some lesions identified as potentially malignant do not develop into aggressive tumors. Acid pH has been suggested as a key characteristic of aggressive tumors that might distinguish aggressive lesions from more indolent pathology. We therefore investigated the novel class of molecules, pH low insertion peptides (pHLIPs), as markers of low pH in tumor allografts and of malignant lesions in a mouse model of spontaneous breast cancer, BALB/neu-T. pHLIP Variant 3 (Var3) conjugated with fluorescent Alexa546 was shown to insert into tumor spheroids in a sequence-specific manner. Its signal reflected pH in murine tumors. It was induced by carbonic anhydrase IX (CAIX) overexpression and inhibited by acetazolamide (AZA) administration. By using 31P magnetic resonance spectroscopy (MRS), we demonstrated that pHLIP Var3 was retained in tumors of pH equal to or less than 6.7 but not in tissues of higher pH. In BALB/neu-T mice at different stages of the disease, the fluorescent signal from pHLIP Var3 marked cancerous lesions with a very low false-positive rate. However, only ∼60% of the smallest lesions retained a pHLIP Var3 signal, suggesting heterogeneity in pH. Taken together, these results show that pHLIP can identify regions of lower pH, allowing for its development as a theranostic tool for clinical applications

Gemcitabine-induced TIMP1 attenuates therapy response and promotes tumor growth and liver metastasis in pancreatic cancer

Gemcitabine constitutes one of the backbones for chemotherapy treatment in pancreatic ductal adenocarcinoma (PDAC), but patients often respond poorly to this agent. Molecular markers downstream of gemcitabine treatment in preclinical models may provide an insight into resistance mechanisms. Using cytokine arrays, we identified potential secretory biomarkers of gemcitabine resistance (response) in the transgenic KRasG12D; Trp53R172H; Pdx-1 Cre (KPC) mouse model of PDAC. We verified the oncogenic role of the cytokine tissue inhibitor of matrix metalloproteinases 1 (TIMP1) in primary pancreatic tumors and metastases using both in vitro techniques and animal models. We identified potential pathways affected downstream of TIMP1 using the Illumina Human H12 array. Our findings were validated in both primary and metastatic models of pancreatic cancer. Gemcitabine increased inflammatory cytokines including TIMP1 in the KPC mouse model. TIMP1 was upregulated in patients with pancreatic intraepithelial neoplasias grade 3 and PDAC lesions relative to matched normal pancreatic tissue. In addition, TIMP1 played a role in tumor clonogenic survival and vascular density, while TIMP1 inhibition resensitized tumors to gemcitabine and radiotherapy. We observed a linear relationship between TIMP-1 expression, liver metastatic burden, and infiltration by CD11b+Gr1+ myeloid cells and CD4+CD25+FOXP3+ Tregs, whereas the presence of tumor cells was required for immune cell infiltration. Overall, our results identify TIMP1 upregulation as a resistance mechanism to gemcitabine and provide a rationale for combining chemo/radiotherapy with TIMP1 inhibitors in PDAC

Tumor pH and Protein Concentration Contribute to the Signal of Amide Proton Transfer Magnetic Resonance Imaging

Abnormal pH is a common feature of malignant tumors and has been associated clinically with suboptimal outcomes. Amide proton transfer magnetic resonance imaging (APT MRI) holds promise as a means to noninvasively measure tumor pH, yet multiple factors collectively make quantification of tumor pH from APT MRI data challenging. The purpose of this study was to improve our understanding of the biophysical sources of altered APT MRI signals in tumors. Combining in vivo APT MRI measurements with ex vivo histological measurements of protein concentration in a rat model of brain metastasis, we determined that the proportion of APT MRI signal originating from changes in protein concentration was approximately 66%, with the remaining 34% originating from changes in tumor pH. In a mouse model of hypopharyngeal squamous cell carcinoma (FaDu), APT MRI showed that a reduction in tumor hypoxia was associated with a shift in tumor pH. The results of this study extend our understanding of APT MRI data and may enable the use of APT MRI to infer the pH of individual patients' tumors as either a biomarker for therapy stratification or as a measure of therapeutic response in clinical settings.Significance: These findings advance our understanding of amide proton transfer magnetic resonance imaging (APT MRI) of tumors and may improve the interpretation of APT MRI in clinical settings

Enhanced antitumor immunity through sequential targeting of PI3Kδ and LAG3

Background Despite striking successes, immunotherapies aimed at increasing cancer-specific T cell responses are unsuccessful in most patients with cancer. Inactivating regulatory T cells (Treg) by inhibiting the PI3Kδ signaling enzyme has shown promise in preclinical models of tumor immunity and is currently being tested in early phase clinical trials in solid tumors. Methods Mice bearing 4T1 mammary tumors were orally administered a PI3Kδ inhibitor (PI-3065) daily and tumor growth, survival and T cell infiltrate were analyzed in the tumor microenvironment. A second treatment schedule comprised PI3Kδ inhibitor with anti-LAG3 antibodies administered sequentially 10 days later. Results As observed in human immunotherapy trials with other agents, immunomodulation by PI3Kδ-blockade led to 4T1 tumor regressor and non-regressor mice. Tumor infiltrating T cells in regressors were metabolically fitter than those in non-regressors, with significant enrichments of antigen-specific CD8+ T cells, T cell factor 1 (TCF1)+ T cells and CD69− T cells, compatible with induction of a sustained tumor-specific T cell response. Treg numbers were significantly reduced in both regressor and non-regressor tumors compared with untreated tumors. The remaining Treg in non-regressor tumors were however significantly enriched with cells expressing the coinhibitory receptor LAG3, compared with Treg in regressor and untreated tumors. This striking difference prompted us to sequentially block PI3Kδ and LAG3. This combination enabled successful therapy of all mice, demonstrating the functional importance of LAG3 in non-regression of tumors on PI3Kδ inhibition therapy. Follow-up studies, performed using additional cancer cell lines, namely MC38 and CT26, indicated that a partial initial response to PI3Kδ inhibition is an essential prerequisite to a sequential therapeutic benefit of anti-LAG3 antibodies. Conclusions These data indicate that LAG3 is a key bottleneck to successful PI3Kδ-targeted immunotherapy and provide a rationale for combining PI3Kδ/LAG3 blockade in future clinical studies

Nonlinear least squares fitting for variable flip angle T1 estimation

The niiT1vfa program enables a fast nonlinear least squares fit for T1 estimation using a robust and efficient version of the Levenberg-Marquardt minimization algorithm provided by a derivative solver in the Gnu Scientific Library (GSL, http://www.gnu.org/software/gsl/). Input data are variable flip angle (VFA) '.nii' data and (optionally) a processed actual flip angle imaging (AFI) 'nii' data set containing the flip angle (FA) distribution resulting from the prescribed AFI flip angle. FA maps provide a voxel wise FA correction for the VFA FA prescription during fitting. Output data are a T1 estimate (T1_VFA.nii), a M0* = Mo.exp(-TE/T2*) estimate (M0_VFA.nii), and (optionally) the number of iterations (NIT_VFA.nii). The 'nii' data are in the NIfTI-1 format, http://nifti.nimh.nih.gov/ ImageJ is a suitable viewer, http://imagej.nih.gov/ij/ The niiT1vfa program was used to calculate the T1 maps from the VFA data and FA maps of four consecutively scanned mice that are publically available courtesy of the Bodleian Digital Library Systems and Services of the University of Oxford at http://dx.doi.org/10.5287/bodleian:a4awG5r7R. See Content.txt for further details

Prospective gating with automated reacquisition for efficient steady state MRI

The Radiobiology Research Institute (RRI) package contents provide prospective gating scan modes with automated reacquisition that have been developed for efficient steady state MRI on Bruker (ParaVision 6.0.1) and Varian (VnmrJ 4.2) platforms. The 3D methods are described in: Kinchesh P, Gilchrist S, Beech JS, Gomes AL, Kersemans V, Newman RG, Vojnovic B, Allen PD, Brady M, Muschel RJ, Smart SC. Prospective gating control for highly efficient cardio-respiratory synchronised short and constant TR MRI in the mouse. Magn Reson Imaging 2018;53:20-27. The SPLICER multi-slice methods are described in: Kinchesh P, Allen PD, Gilchrist S, Kersemans V, Lanfredini S, Thapa A, O’Neill E, Smart SC. Reduced respiratory motion artefact in constant TR multi-slice MRI of the mouse. Submitted to Magn Reson Imaging. Data showing the improved stability of the 3D methods with respect to ungated scanning can be found at http://dx.doi.org/10.5287/bodleian:a4awG5r7R. Data showing the improved stability of a SPLICER RARE scan with respect to an ungated RARE scan are available in this repository. RRI package scan modes include: ge3dRRI, a 3D spoiled gradient echo scan. bssfp3dRRI, a 3D balanced SSFP scan. afi3dRRI, a 3D Actual Flip-angle Imaging (AFI) scan. fseRRI/fsemsRRI, a SPLICER multi-slice fast spin echo (RARE) scan. sgeRRI/gemsRRI, a SPLICER multi-slice spoiled gradient echo scan. mseRRI/memsRRI, a SPLICER multi-slice multi spin echo scan. semsRRI, a SPLICER multi-slice spin echo scan (VnmrJ 4.2 only). The accompanying open source package software includes: Reconstruction/conversion to NIfTI-1 format, http://nifti.nimh.nih.gov/ Generation of Flip Angle maps from AFI data. Package Files in Repository: PV6.0.1_RRIpkg_01.tar.gz: Package for ParaVision 6.0.1 on the Bruker AVANCE III HD console. PV6.0.1_RRIpkg_01_INSTALL.txt: Installation instructions for PV6.0.1_RRIpkg_01.tar.gz. VJ4.2_patches.tar.gz: Patches for VnmrJ 4.2 on the Varian VNMRS and DD2 consoles. VJ4.2_RRIpkg_01.bsx: Self extracting package for VnmrJ 4.2 on the Varian VNMRS and DD2 consoles. VJ4.2_RRIpkg_01_INSTALL.txt: Installation instructions for VJ4.2_RRIpkg_01.bsx. Data Files in Repository: SPLICER_RARE.tar.gz: SPLICER RARE vs Ungated RARE (gzipped tarfile). SPLICER_RARE.zip: SPLICER RARE vs Ungated RARE (zipped file). The SPLICER_RARE archives include a stability test of the SPLICER acquisition mode with 10 repeats of a 2D multi-slice RARE scan with ETL 8, effective TE 24 ms, TR 2000 ms, THK 0.5 mm, 24 contiguous slices, FOV 32 × 32 mm2 and matrix 128 × 128. For comparison, 20 repeats of an ungated scan acquired in a virtually identical scan time were acquired with otherwise identical parameters. Data were acquired on a 4.7 T 310 mm horizontal bore Biospec AVANCE III HD preclinical imaging system equipped with 114 mm bore gradient insert (Bruker BioSpin GmbH, Germany). The files included are: SPLICER_RARE.nii: 10 repeats of a SPLICER RARE scan. SPLICER_RARE_mean.nii: The pixel by pixel mean of SPLICER_RARE.nii. SPLICER_RARE_stdev.nii: The pixel by pixel standard deviation of SPLICER_RARE.nii. SPLICER_RARE_snr.nii: The pixel by pixel SNR = SPLICER_RARE_mean.nii/SPLICER_RARE_stdev.nii. Ungated_RARE.nii: 20 repeats of an Ungated RARE scan Ungated_RARE_mean.nii: The pixel by pixel mean of Ungated_RARE.nii. Ungated_RARE_stdev.nii: The pixel by pixel standard deviation of Ungated_RARE.nii. Ungated_RARE_snr.nii: The pixel by pixel SNR = Ungated_RARE_mean.nii/Ungated_RARE_stdev.nii. The 'nii' data are in the NIfTI-1 format, http://nifti.nimh.nih.gov/ ImageJ is a suitable viewer, http://imagej.nih.gov/ij

Automated reacquisition for respiration insensitive scanning with MRI

Automated and immediate reacquisition of data that are corrupted by respiratory motion has been developed to improve respiration insensitive scanning in small animal MRI. Methods have been developed to maximise the efficiency with which respiratory and cardio-respiratory synchronised scans can be acquired and provide quantitative image data that exhibit a remarkably low level of motion artefact. 3D dynamic contrast enhanced (DCE)-MRI is performed with a mean frame interval of 13.7 s which enables early passage of contrast agent to be detected in the major vessels, the heart and lungs, and essentially presents an angiographic blood volume image of the mouse thorax. 2D steady state maintained CINE MRI is performed with a 3.24 ms frame interval starting within 3.24 ms of the cardiac R-wave. The CINE data exhibit very homogeneous image intensities throughout the cardiac cycle without any amplitude modulations, often referred to as 'flashing', which should enable more robust quantitative analyses of cardiac function. Files: *.nii are NIfTI-1 formatted image files, http://nifti.nimh.nih.gov/. ImageJ is a suitable viewer, http://imagej.nih.gov/ij/ CINE.nii: CINE MRI frames acquired during the cardiac cycle of a mouse. DCE001noreacq.nii: DCE MRI frames of mouse 1 without reacquisition. DCE001reacq.nii: DCE MRI frames of mouse 1 with reacquisition. DCE00n.nii: DCE MRI frames of mouse n with reacquisition (n = [2,7]). LungAngio.avi avi movie file showing angiographic blood volume image of the thorax of mouse 1. Generated from the difference between DCE MRI frames 10 and 11 of DCE001reacq.nii. *.txt are ASCII text files. reacq00n.txt: DCE MRI reacquisition file for mouse n (n = [1,7]). The files show duplicate successive entries for those acquisition blocks that were reacquired. The number of uncorrupted acquisition blocks per breath interval can be deduced from the files. timestamp00n.txt: DCE MRI timestamp file for mouse n (n = [1,7]). The files show timestamps for the acquisition of the centre of k-space for each DCE MRI frame

Nonlinear least squares fitting for variable flip angle T1 estimation

The niiT1vfa program enables a fast nonlinear least squares fit for T1 estimation using a robust and efficient version of the Levenberg-Marquardt minimization algorithm provided by a derivative solver in the Gnu Scientific Library (GSL, http://www.gnu.org/software/gsl/). Input data are variable flip angle (VFA) '.nii' data and (optionally) a processed actual flip angle imaging (AFI) 'nii' data set containing the flip angle (FA) distribution resulting from the prescribed AFI flip angle. FA maps provide a voxel wise FA correction for the VFA FA prescription during fitting. Output data are a T1 estimate (T1_VFA.nii), a M0* = Mo.exp(-TE/T2*) estimate (M0_VFA.nii), and (optionally) the number of iterations (NIT_VFA.nii). The 'nii' data are in the NIfTI-1 format, http://nifti.nimh.nih.gov/ ImageJ is a suitable viewer, http://imagej.nih.gov/ij/ The niiT1vfa program was used to calculate the T1 maps from the VFA data and FA maps of four consecutively scanned mice that are publically available courtesy of the Bodleian Digital Library Systems and Services of the University of Oxford at http://dx.doi.org/10.5287/bodleian:a4awG5r7R. See Content.txt for further details