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Purpose To evaluate if the new Discovery Molecular Insights (DMI) PET/CT scanner provides equivalent results compared to the standard of care PET/CT scanners (GE Discovery 600 or GE Discovery 690) used in our clinic and to explore any possible differences in semi-quantitative measurements. Methods The local Institutional Review Board approved the protocol and written informed consent was obtained from each patient. Between September and November 2016, 50 patients underwent a single 18F-FDG injection and two scans: the clinical standard PET/CT followed immediately by the DMI PET/CT scan. We measured SUVmax and SUVmean of different background organs and up to four lesions per patient from data acquired using both scanners. Results DMI PET/CT identified all the 107 lesions detected by standard PET/CT scanners, as well as additional 37 areas of focal increased 18F-FDG uptake. The SUVmax values for all 107 lesions ranged 1.2 to 14.6 (mean ± SD: 2.8 ± 2.8), higher on DMI PET/CT compared with standard of care PET/CT. The mean lesion:aortic arch SUVmax ratio and mean lesion:liver SUVmax ratio were 0.2–15.2 (mean ± SD: 3.2 ± 2.6) and 0.2–8.5 (mean ± SD: 1.9 ± 1.4) respectively, higher on DMI PET/CT than standard PET/CT. These differences were statistically significant (P value < 0.0001) and not correlated to the delay in acquisition of DMI PET data (P < 0.0001). Conclusions Our study shows high performance of the new DMI PET/CT scanner. This may have a significant role in diagnosing and staging disease, as well as for assessing and monitoring responses to therapies.

Circulating tumor cells (CTCs) have been detected in the bloodstream of both early-stage and advanced cancer patients. However, very little is know about the dynamics of CTCs during cancer progression and the clinical relevance of longitudinal CTC enumeration. To address this, we developed a simple bioluminescence imaging assay to detect CTCs in mouse models of metastasis. In a 4T1 orthotopic metastatic mammary carcinoma mouse model, we demonstrated that this quantitative method offers sensitivity down to 2 CTCs in 0.1–1mL blood samples and high specificity for CTCs originating from the primary tumor, independently of their epithelial status. In this model, we simultaneously monitored blood CTC dynamics, primary tumor growth, and lung metastasis progression over the course of 24 days. Early in tumor development, we observed low numbers of CTCs in blood samples (10–15 cells/100 µL) and demonstrated that CTC dynamics correlate with viable primary tumor growth. To our knowledge, these data represent the first reported use of bioluminescence imaging to detect CTCs and quantify their dynamics in any cancer mouse model. This new assay is opening the door to the study of CTC dynamics in a variety of animal models. These studies may inform clinical decision on the appropriate timing of blood sampling and value of longitudinal CTC enumeration in cancer patients.

Non-Hodgkin's lymphoma is a disseminated, highly malignant cancer, with resistance to drug treatment based on molecular- and tissue-scale characteristics that are intricately linked. A critical element of molecular resistance has been traced to the loss of functionality in proteins such as the tumor suppressor p53. We investigate the tissue-scale physiologic effects of this loss by integrating in vivo and immunohistological data with computational modeling to study the spatiotemporal physical dynamics of lymphoma growth. We compare between drug-sensitive Eμ-myc Arf-/- and drug-resistant Eμ-myc p53-/- lymphoma cell tumors grown in live mice. Initial values for the model parameters are obtained in part by extracting values from the cellular-scale from whole-tumor histological staining of the tumor-infiltrated inguinal lymph node in vivo. We compare model-predicted tumor growth with that observed from intravital microscopy and macroscopic imaging in vivo, finding that the model is able to accurately predict lymphoma growth. A critical physical mechanism underlying drug-resistant phenotypes may be that the Eμ-myc p53-/- cells seem to pack more closely within the tumor than the Eμ-myc Arf-/- cells, thus possibly exacerbating diffusion gradients of oxygen, leading to cell quiescence and hence resistance to cell-cycle specific drugs. Tighter cell packing could also maintain steeper gradients of drug and lead to insufficient toxicity. The transport phenomena within the lymphoma may thus contribute in nontrivial, complex ways to the difference in drug sensitivity between Eμ-myc Arf-/- and Eμ-myc p53-/- tumors, beyond what might be solely expected from loss of functionality at the molecular scale. We conclude that computational modeling tightly integrated with experimental data gives insight into the dynamics of Non-Hodgkin's lymphoma and provides a platform to generate confirmable predictions of tumor growth., Author Summary Non-Hodgkin's lymphoma is a cancer that develops from white blood cells called lymphocytes in the immune system, whose role is to fight disease throughout the body. This cancer can spread throughout the whole body and be very lethal – in the US, one third of patients will die from this disease within five years of diagnosis. Chemotherapy is a usual treatment for lymphoma, but the cancer can become highly resistant to it. One reason is that a critical gene called p53 can become mutated and help the cancer to survive. In this work we investigate how cells with this mutation affect the cancer growth by performing experiments in mice and using a computer model. By inputting the model parameters based on data from the experiments, we are able to accurately predict the growth of the tumor as compared to tumor measurements in living mice. We conclude that computational modeling integrated with experimental data gives insight into the dynamics of Non-Hodgkin's lymphoma, and provides a platform to generate confirmable predictions of tumor growth.

Introduction We investigated the relationship of circulating tumor cells (CTCs) in non-small cell lung cancer (NSCLC) with tumor glucose metabolism as defined by 18F-fluorodeoxyglucose (FDG) uptake since both have been associated with patient prognosis. Materials & Methods We performed a retrospective screen of patients at four medical centers who underwent FDG PET-CT imaging and phlebotomy prior to a therapeutic intervention for NSCLC. We used an Epithelial Cell Adhesion Molecule (EpCAM) independent fluid biopsy based on cell morphology for CTC detection and enumeration (defined here as High Definition CTCs or “HD-CTCs”). We then correlated HD-CTCs with quantitative FDG uptake image data calibrated across centers in a cross-sectional analysis. Results We assessed seventy-one NSCLC patients whose median tumor size was 2.8 cm (interquartile range, IQR, 2.0–3.6) and median maximum standardized uptake value (SUVmax) was 7.2 (IQR 3.7–15.5). More than 2 HD-CTCs were detected in 63% of patients, whether across all stages (45 of 71) or in stage I disease (27 of 43). HD-CTCs were weakly correlated with partial volume corrected tumor SUVmax (r = 0.27, p-value = 0.03) and not correlated with tumor diameter (r = 0.07; p-value = 0.60). For a given partial volume corrected SUVmax or tumor diameter there was a wide range of detected HD-CTCs in circulation for both early and late stage disease. Conclusions CTCs are detected frequently in early-stage NSCLC using a non-EpCAM mediated approach with a wide range noted for a given level of FDG uptake or tumor size. Integrating potentially complementary biomarkers like these with traditional patient data may eventually enhance our understanding of clinical, in vivo tumor biology in the early stages of this deadly disease.

Reporter genes are powerful technologies that can be used to directly inform on the fate of transplanted cells in living subjects. Imaging reporter genes are often employed to quantify cell number, location(s), and viability with various imaging modalities. To complement this, reporters that are secreted from cells can provide a low-cost, in vitro diagnostic test to monitor overall cell viability at relatively high frequency without knowing the locations of all cells. Whereas protein-based secretable reporters have been developed, an RNA-based reporter detectable with amplification inherent PCR-based assays has not been previously described. MicroRNAs (miRNAs) are short non-coding RNAs (18-22 nt) that regulate mRNA translation and are being explored as relatively stable blood-based disease biomarkers. We developed an artificial miRNA-based secreted reporter, called Sec-miR, utilizing a coding sequence that is not expressed endogenously and does not have any known vertebrate target. Sec-miR was detectable in both the cells and culture media of transiently transfected cells. Cells stably expressing Sec-miR also reliably secreted it into the culture media. Mice implanted with parental HeLa cells or HeLa cells expressing both Sec-miR and the bioluminescence imaging (BLI) reporter gene Firefly luciferase (FLuc) were monitored over time for tumor volume, FLuc signal via BLI, and blood levels of Sec-miR. Significantly (p

PURPOSE:(S)-4-(3-[18F]Fluoropropyl)-L-glutamic acid (18F-FSPG) is a novel radiopharmaceutical for Positron Emission Tomography (PET) imaging. It is a glutamate analogue that can be used to measure xC- transporter activity. This study was performed to assess the feasibility of 18F-FSPG for imaging orthotopic brain tumors in small animals and the translation of this approach in human subjects with intracranial malignancies. EXPERIMENTAL DESIGN:For the small animal study, GS9L glioblastoma cells were implanted into brains of Fischer rats and studied with 18F-FSPG, the 18F-labeled glucose derivative 18F-FDG and with the 18F-labeled amino acid derivative 18F-FET. For the human study, five subjects with either primary or metastatic brain cancer were recruited (mean age 50.4 years). After injection of 300 MBq of 18F-FSPG, 3 whole-body PET/Computed Tomography (CT) scans were obtained and safety parameters were measured. The three subjects with brain metastases also had an 18F-FDG PET/CT scan. Quantitative and qualitative comparison of the scans was performed to assess kinetics, biodistribution, and relative efficacy of the tracers. RESULTS:In the small animals, the orthotopic brain tumors were visualized well with 18F-FSPG. The high tumor uptake of 18F-FSPG in the GS9L model and the absence of background signal led to good tumor visualization with high contrast (tumor/brain ratio: 32.7). 18F-FDG and 18F-FET showed T/B ratios of 1.7 and 2.8, respectively. In the human pilot study, 18F-FSPG was well tolerated and there was similar distribution in all patients. All malignant lesions were positive with 18F-FSPG except for one low-grade primary brain tumor. In the 18F-FSPG-PET-positive tumors a similar T/B ratio was observed as in the animal model. CONCLUSIONS:18F-FSPG is a novel PET radiopharmaceutical that demonstrates good uptake in both small animal and human studies of intracranial malignancies. Future studies on larger numbers of subjects and a wider array of brain tumors are planned. TRIAL REGISTRATION:ClinicalTrials.gov NCT01186601.

KRAS mutant lung cancers are generally refractory to chemotherapy as well targeted agents. To date, the identification of drugs to therapeutically inhibit K-RAS have been unsuccessful, suggesting that other approaches are required. We demonstrate in both a novel transgenic mutant Kras lung cancer mouse model and in human lung tumors that the inhibition of Twist1 restores a senescence program inducing the loss of a neoplastic phenotype. The Twist1 gene encodes for a transcription factor that is essential during embryogenesis. Twist1 has been suggested to play an important role during tumor progression. However, there is no in vivo evidence that Twist1 plays a role in autochthonous tumorigenesis. Through two novel transgenic mouse models, we show that Twist1 cooperates with KrasG12D to markedly accelerate lung tumorigenesis by abrogating cellular senescence programs and promoting the progression from benign adenomas to adenocarcinomas. Moreover, the suppression of Twist1 to physiological levels is sufficient to cause Kras mutant lung tumors to undergo senescence and lose their neoplastic features. Finally, we analyzed more than 500 human tumors to demonstrate that TWIST1 is frequently overexpressed in primary human lung tumors. The suppression of TWIST1 in human lung cancer cells also induced cellular senescence. Hence, TWIST1 is a critical regulator of cellular senescence programs, and the suppression of TWIST1 in human tumors may be an effective example of pro-senescence therapy., Author Summary Lung cancer is the most common cause of cancer death worldwide. The Twist1 gene encodes for an essential transcription factor required for embryogenesis and overexpressed in many cancer types. It has yet to be shown in vivo whether Twist1 plays a role in the initiation or maintenance of cancer. Here we demonstrate using novel transgenic mouse models that Twist1 cooperates to induce lung tumorigenesis by suppressing cellular senescence programs. Moreover, the suppression of Twist1 in murine tumors elicited cellular senescence and the loss of a neoplastic phenotype. We found that TWIST1 is commonly overexpressed in human lung cancers. Finally, the inhibition of TWIST1 levels in human lung cancer cells was associated with loss of proliferation, induction of cellular senescence, and the inability to form tumors in mice. Hence, we conclude that TWIST1 is a key regulator of cellular senescence programs during tumorigenesis. The targeted inactivation of TWIST1 may be an effective pro-senescence therapy for human lung adenocarcinomas.

The emerging field of photoacoustic tomography is rapidly evolving with many new system designs and reconstruction algorithms being published. Many systems use water as a coupling medium between the scanned object and the ultrasound transducers. Prior to a scan, the water is heated to body temperature to enable small animal imaging. During the scan, the water heating system of some systems is switched off to minimize the risk of bubble formation, which leads to a gradual decrease in water temperature and hence the speed of sound. In this work, we use a commercially available scanner that follows this procedure, and show that a failure to model intra-scan temperature decreases as small as 1.5°C leads to image artifacts that may be difficult to distinguish from true structures, particularly in complex scenes. We then improve image quality by continuously monitoring the water temperature during the scan and applying variable speed of sound corrections in the image reconstruction algorithm. While upgrading to an air bubble-free heating pump and keeping it running during the scan could also solve the changing temperature problem, we show that a software correction for the temperature changes provides a cost-effective alternative to a hardware upgrade. The efficacy of the software corrections was shown to be consistent across objects of widely varying appearances, namely physical phantoms, ex vivo tissue, and in vivo mouse imaging. To the best of our knowledge, this is the first study to demonstrate the efficacy of modeling temporal variations in the speed of sound during photoacoustic scans, as opposed to spatial variations as focused on by previous studies. Since air bubbles pose a common problem in ultrasonic and photoacoustic imaging systems, our results will be useful to future small animal imaging studies that use scanners with similarly limited heating units.

Background Placental dysfunction underlies numerous complications of pregnancy. A major obstacle to understanding the roles of potential mediators of placental pathology has been the absence of suitable methods for tissue-specific gene manipulation and sensitive assays for studying gene functions in the placentas of intact animals. We describe a sensitive and noninvasive method of repetitively tracking placenta-specific gene expression throughout pregnancy using lentivirus-mediated transduction of optical reporter genes in mouse blastocysts. Methodology/Principal Findings Zona-free blastocysts were incubated with lentivirus expressing firefly luciferase (Fluc) and Tomato fluorescent fusion protein for trophectoderm-specific infection and transplanted into day 3 pseudopregnant recipients (GD3). Animals were examined for Fluc expression by live bioluminescence imaging (BLI) at different points during pregnancy, and the placentas were examined for tomato expression in different cell types on GD18. In another set of experiments, blastocysts with maximum photon fluxes in the range of 2.0E+4 to 6.0E+4 p/s/cm2/sr were transferred. Fluc expression was detectable in all surrogate dams by day 5 of pregnancy by live imaging, and the signal increased dramatically thereafter each day until GD12, reaching a peak at GD16 and maintaining that level through GD18. All of the placentas, but none of the fetuses, analyzed on GD18 by BLI showed different degrees of Fluc expression. However, only placentas of dams transferred with selected blastocysts showed uniform photon distribution with no significant variability of photon intensity among placentas of the same litter. Tomato expression in the placentas was limited to only trophoblast cell lineages. Conclusions/Significance These results, for the first time, demonstrate the feasibility of selecting lentivirally-transduced blastocysts for uniform gene expression in all placentas of the same litter and early detection and quantitative analysis of gene expression throughout pregnancy by live BLI. This method may be useful for a wide range of applications involving trophoblast-specific gene manipulations in utero.

F18 2-Fluoro 2-deoxyglucose (FDG) has been the gold standard in positron emission tomography (PET) oncologic imaging since its introduction into the clinics several years ago. Seeking to complement FDG in the diagnosis of breast cancer using radio labeled fructose based analogs, we investigated the expression of the chief fructose transporter-GLUT 5 in breast cancer cells and human tissues. Our results indicate that GLUT 5 is not over-expressed in breast cancer tissues as assessed by an extensive immunohistochemistry study. RT-PCR studies showed that the GLUT 5 mRNA was present at minimal amounts in breast cancer cell lines. Further knocking down the expression of GLUT 5 in breast cancer cells using RNA interference did not affect the fructose uptake in these cell lines. Taken together these results are consistent with GLUT 5 not being essential for fructose uptake in breast cancer cells and tissues.

Background Optical imaging (OI) techniques such as bioluminescence and fluorescence imaging have been widely used to track diseases in a non-invasive manner within living subjects. These techniques generally require bioluminescent and fluorescent probes. Here we demonstrate the feasibility of using radioactive probes for in vivo molecular OI. Methodology/Principal Findings By taking the advantages of low energy window of light (1.2–3.1 eV, 400–1000 nm) resulting from radiation, radionuclides that emit charged particles such as β+ and β− can be successfully imaged with an OI instrument. In vivo optical images can be obtained for several radioactive probes including 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG), Na18F, Na131I, 90YCl3 and a 90Y labeled peptide that specifically target tumors. Conclusions/Significance These studies demonstrate generalizability of radioactive OI technique. It provides a new molecular imaging strategy and will likely have significant impact on both small animal and clinical imaging.

Background Increasing efforts and financial resources are being invested in early cancer detection research. Blood assays detecting tumor biomarkers promise noninvasive and financially reasonable screening for early cancer with high potential of positive impact on patients' survival and quality of life. For novel tumor biomarkers, the actual tumor detection limits are usually unknown and there have been no studies exploring the tumor burden detection limits of blood tumor biomarkers using mathematical models. Therefore, the purpose of this study was to develop a mathematical model relating blood biomarker levels to tumor burden. Methods and Findings Using a linear one-compartment model, the steady state between tumor biomarker secretion into and removal out of the intravascular space was calculated. Two conditions were assumed: (1) the compartment (plasma) is well-mixed and kinetically homogenous; (2) the tumor biomarker consists of a protein that is secreted by tumor cells into the extracellular fluid compartment, and a certain percentage of the secreted protein enters the intravascular space at a continuous rate. The model was applied to two pathophysiologic conditions: tumor biomarker is secreted (1) exclusively by the tumor cells or (2) by both tumor cells and healthy normal cells. To test the model, a sensitivity analysis was performed assuming variable conditions of the model parameters. The model parameters were primed on the basis of literature data for two established and well-studied tumor biomarkers (CA125 and prostate-specific antigen [PSA]). Assuming biomarker secretion by tumor cells only and 10% of the secreted tumor biomarker reaching the plasma, the calculated minimally detectable tumor sizes ranged between 0.11 mm3 and 3,610.14 mm3 for CA125 and between 0.21 mm3 and 131.51 mm3 for PSA. When biomarker secretion by healthy cells and tumor cells was assumed, the calculated tumor sizes leading to positive test results ranged between 116.7 mm3 and 1.52 × 106 mm3 for CA125 and between 27 mm3 and 3.45 × 105 mm3 for PSA. One of the limitations of the study is the absence of quantitative data available in the literature on the secreted tumor biomarker amount per cancer cell in intact whole body animal tumor models or in cancer patients. Additionally, the fraction of secreted tumor biomarkers actually reaching the plasma is unknown. Therefore, we used data from published cell culture experiments to estimate tumor cell biomarker secretion rates and assumed a wide range of secretion rates to account for their potential changes due to field effects of the tumor environment. Conclusions This study introduced a linear one-compartment mathematical model that allows estimation of minimal detectable tumor sizes based on blood tumor biomarker assays. Assuming physiological data on CA125 and PSA from the literature, the model predicted detection limits of tumors that were in qualitative agreement with the actual clinical performance of both biomarkers. The model may be helpful in future estimation of minimal detectable tumor sizes for novel proteomic biomarker assays if sufficient physiologic data for the biomarker are available. The model may address the potential and limitations of tumor biomarkers, help prioritize biomarkers, and guide investments into early cancer detection research efforts., Sanjiv Gambhir and colleagues describe a linear one-compartment mathematical model that allows estimation of minimal detectable tumor sizes based on blood tumor biomarker assays., Editors' Summary Background. Cancers—disorganized masses of cells that can occur in any tissue—develop when cells acquire genetic changes that allow them to grow uncontrollably and to spread around the body (metastasize). If a cancer (tumor) is detected when it is small, surgery can often provide a cure. Unfortunately, many cancers (particularly those deep inside the body) are not detected until they are large enough to cause pain or other symptoms by pressing against surrounding tissue. By this time, it may be impossible to remove the original tumor surgically and there may be metastases scattered around the body. In such cases, radiotherapy and chemotherapy can sometimes help, but the outlook for patients whose cancers are detected late is often poor. Consequently, researchers are trying to develop early detection tests for different types of cancer. Many tumors release specific proteins—“cancer biomarkers”—into the blood and the hope is that it might be possible to find sets of blood biomarkers that detect cancers when they are still small and thus save many lives. Why Was This Study Done? For most biomarkers, it is not known how the amount of protein detected in the blood relates to tumor size or how sensitive the assays for biomarkers must be to improve patient survival. In this study, the researchers develop a “linear one-compartment” mathematical model to predict how large tumors need to be before blood biomarkers can be used to detect them and test this model using published data on two established cancer biomarkers—CA125 and prostate-specific antigen (PSA). CA125 is used to monitor the progress of patients with ovarian cancer after treatment; ovarian cancer is rarely diagnosed in its early stages and only one-fourth of women with advanced disease survive for 5 y after diagnosis. PSA is used to screen for prostate cancer and has increased the detection of this cancer in its early stages when it is curable. What Did the Researchers Do and Find? To develop a model that relates secreted blood biomarker levels to tumor sizes, the researchers assumed that biomarkers mix evenly throughout the patient's blood, that cancer cells secrete biomarkers into the fluid that surrounds them, that 0.1%–20% of these secreted proteins enter the blood at a continuous rate, and that biomarkers are continuously removed from the blood. The researchers then used their model to calculate the smallest tumor sizes that might be detectable with these biomarkers by feeding in existing data on CA125 and on PSA, including assay detection limits and the biomarker secretion rates of cancer cells growing in dishes. When only tumor cells secreted the biomarker and 10% of the secreted biomarker reach the blood, the model predicted that ovarian tumors between 0.11 mm3 (smaller than a grain of salt) and nearly 4,000 mm3 (about the size of a cherry) would be detectable by measuring CA125 blood levels (the range was determined by varying the amount of biomarker secreted by the tumor cells and the assay sensitivity); for prostate cancer, the detectable tumor sizes ranged from similar lower size to about 130 mm3 (pea-sized). However, healthy cells often also secrete small quantities of cancer biomarkers. With this condition incorporated into the model, the estimated detectable tumor sizes (or total tumor burden including metastases) ranged between grape-sized and melon-sized for ovarian cancers and between pea-sized to about grapefruit-sized for prostate cancers. What Do These Findings Mean? The accuracy of the calculated tumor sizes provided by the researchers' mathematical model is limited by the lack of data on how tumors behave in the human body and by the many assumptions incorporated into the model. Nevertheless, the model predicts detection limits for ovarian and prostate cancer that broadly mirror the clinical performance of both biomarkers. Somewhat worryingly, the model also indicates that a tumor may have to be very large for blood biomarkers to reveal its presence, a result that could limit the clinical usefulness of biomarkers, especially if they are secreted not only by tumor cells but also by healthy cells. Given this finding, as more information about how biomarkers behave in the human body becomes available, this model (and more complex versions of it) should help researchers decide which biomarkers are likely to improve early cancer detection and patient outcomes. Additional Information. Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050170. The US National Cancer Institute provides a brief description of what cancer is and how it develops and a fact sheet on tumor markers; it also provides information on all aspects of ovarian and prostate cancer for patients and professionals, including information on screening and testing (in English and Spanish) The UK charity Cancerbackup also provides general information about cancer and more specific information about ovarian and prostate cancer, including the use of CA125 and PSA for screening and follow-up The American Society of Clinical Oncology offers a wide range of information on various cancer types, including online published articles on the current status of cancer diagnosis and management from the educational book developed by the annual meeting faculty and presenters. Registration is mandatory, but information is free

Monobodies are binding scaffold proteins originating from a human fibronectin domain III (Fn3) scaffold that can be easily engineered with specificity and affinity. Human EphA2 (hEphA2) is an early detection marker protein for various tumors including lung, breast, and colon cancer. In this study, we isolated two hEphA2-specific monobodies (E1 and E10) by screening a yeast surface display library. They showed the same amino acid sequence except in the DE loop and had high affinity (similar to 2 nM Kd) against hEphA2. E1 bound only hEphA2 and mEphA2, although it bound hEphA2 with an affinity 2-fold higher than that of mEphA2. However, E10 also bound the mEphA6 and mEphA8 homologs as well as hEphA2 and mEphA2. Thus, E1 but not E10 was highly specific for hEphA2. E1 specifically bound human cells and xenograft tumor tissues expressing hEphA on the cell surface. In vivo optical imaging showed strong targeting of Cy5.5-labeled E1 to mouse tumor tissue induced by PC3 cells, a human prostate cancer cell line that expresses a high level of hEphA2. In conclusion, the highly specific monobody E1 is useful as a hEphA2 probe candidate for in vivo diagnosis and therapy.

The detection of biomarker-targeting surface-enhanced Raman scattering (SERS) nanoparticles (NPs) in the human gastrointestinal tract has the potential to improve early cancer detection; however, a clinically relevant device with rapid Raman-imaging capability has not been described. Here we report the design and in vivo demonstration of a miniature, non-contact, opto-electro-mechanical Raman device as an accessory to clinical endoscopes that can provide multiplexed molecular data via a panel of SERS NPs. This device enables rapid circumferential scanning of topologically complex luminal surfaces of hollow organs (e.g., colon and esophagus) and produces quantitative images of the relative concentrations of SERS NPs that are present. Human and swine studies have demonstrated the speed and simplicity of this technique. This approach also offers unparalleled multiplexing capabilities by simultaneously detecting the unique spectral fingerprints of multiple SERS NPs. Therefore, this new screening strategy has the potential to improve diagnosis and to guide therapy by enabling sensitive quantitative molecular detection of small and otherwise hard-to-detect lesions in the context of white-light endoscopy.

Despite advances in the field of nuclear medicine, the imaging of bacterial infections has remained a challenge. The existing reagents suffer from poor sensitivity and specificity. In this study we investigate the potential of a novel PET (positron emission tomography) tracer that overcomes these limitations.

Photoacoustic imaging combines the high contrast of optical imaging with the spatial resolution and penetration depth of ultrasound. This technique holds tremendous potential for imaging in small animals and importantly, is clinically translatable. At present, there is no accepted standard physical phantom that can be used to provide routine quality control and performance evaluation of photoacoustic imaging instruments. With the growing popularity of the technique and the advent of several commercial small animal imaging systems, it is important to develop a strategy for assessment of such instruments. Here, we developed a protocol for fabrication of physical phantoms for photoacoustic imaging from polyvinyl chloride plastisol (PVCP). Using this material, we designed and constructed a range of phantoms by tuning the optical properties of the background matrix and embedding spherical absorbing targets of the same material at different depths. We created specific designs to enable: routine quality control; the testing of robustness of photoacoustic signals as a function of background; and the evaluation of the maximum imaging depth available. Furthermore, we demonstrated that we could, for the first time, evaluate two small animal photoacoustic imaging systems with distinctly different light delivery, ultrasound imaging geometries and center frequencies, using stable physical phantoms and directly compare the results from both systems.

Activation of the PI3K/Akt pathway, a critical step for survival in cancer cells is often associated with decreased sensitivity to several chemotherapeutic drugs. PIK3CA gene amplification is observed in 16–24% of epithelial ovarian cancer (EOC) patients in conjunction with p53 mutations. A 900 bp long PIK3CA promoter is shown to be negatively regulated by p53 in ovarian surface epithelial cells but the consequence of chemotherapeutic drug treatments on this promoter in ovarian cancer cells is largely unknown. We aim to study the modulation of this promoter by cisplatin using an improved fusion reporter in ovarian cancer cells and tumor xenografts by non-invasive imaging approach. A PIK3CA sensor was developed using a bi-fusion reporter from a newly constructed library of bi- and tri-fusion vectors comprising of two mutant far red fluorescent proteins (mcherry/mch and tdTomato/tdt), a mutant firefly luciferase (fluc2), and a PET reporter protein (ttk). In vivo imaging of mice implanted with 293T cells transiently expressing these bi- and tri-fusion reporters along with respective controls revealed comparable activity of each reporter in the fusion background and fluc2-tdt as the most sensitive one. Repression of the PIK3CA sensor by drugs was inversely proportional to cellular p53 level in a germline (PA1) and in an EOC (A2780) cell line but not in a p53 deficient EOC (SKOV3) cell line. Bioluminescence imaging of tumor xenografts stably expressing the PIK3CA sensor in PA1 and A2780 cells exhibited attenuating activity without any change in SKOV3 tumors expressing the PIK3CA sensor after cisplatin treatment. Sequential mutation at p53 binding sites showed gradual increase in promoter activity and decreased effects of the drugs. These newly developed PIK3CA-fluc2-tdt and the mutant reporter sensors thus would be extremely useful for screening new drugs and for functional assessment of PIK3CA expression from intact cells to living subjects.

Raman spectroscopy is a powerful technique for detecting and quantifying analytes in chemical mixtures. A critical part of Raman spectroscopy is the use of a computer algorithm to analyze the measured Raman spectra. The most commonly used algorithm is the classical least squares method, which is popular due to its speed and ease of implementation. However, it is sensitive to inaccuracies or variations in the reference spectra of the analytes (compounds of interest) and the background. Many algorithms, primarily multivariate calibration methods, have been proposed that increase robustness to such variations. In this study, we propose a novel method that improves robustness even further by explicitly modeling variations in both the background and analyte signals. More specifically, it extends the classical least squares model by allowing the declared reference spectra to vary in accordance with the principal components obtained from training sets of spectra measured in prior characterization experiments. The amount of variation allowed is constrained by the eigenvalues of this principal component analysis. We compare the novel algorithm to the least squares method with a low-order polynomial residual model, as well as a state-of-the-art hybrid linear analysis method. The latter is a multivariate calibration method designed specifically to improve robustness to background variability in cases where training spectra of the background, as well as the mean spectrum of the analyte, are available. We demonstrate the novel algorithm's superior performance by comparing quantitative error metrics generated by each method. The experiments consider both simulated data and experimental data acquired from in vitro solutions of Raman-enhanced gold-silica nanoparticles.

Genetically modified adipose tissue derived mesenchymal stromal cells (hAMSCs) with tumor homing capacity have been proposed for localized therapy of chemo- and radiotherapy resistant glioblastomas. We demonstrate an effective procedure to optimize glioblastoma therapy based on the use of genetically modified hAMSCs and in vivo non invasive monitoring of tumor and therapeutic cells. Glioblastoma U87 cells expressing Photinus pyralis luciferase (Pluc) were implanted in combination with hAMSCs expressing a trifunctional Renilla reniformis luciferase-red fluorescent protein-thymidine kinase reporter in the brains of SCID mice that were subsequently treated with ganciclovir (GCV). The resulting optimized therapy was effective and monitoring of tumor cells by bioluminescence imaging (BLI) showed that after 49 days GCV treatment reduced significantly the hAMSC treated tumors; by a factor of 10(4) relative to controls. Using a Pluc reporter regulated by an endothelial specific promoter and in vivo BLI to image hAMSC differentiation we gained insight on the therapeutic mechanism. Implanted hAMSCs homed to tumor vessels, where they differentiated to endothelial cells. We propose that the tumor killing efficiency of genetically modified hAMSCs results from their association with the tumor vascular system and should be useful vehicles to deliver localized therapy to glioblastoma surgical borders following tumor resection.