14 resultados para tumor classification

em Duke University


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Gliomagenesis is driven by a complex network of genetic alterations and while the glioma genome has been a focus of investigation for many years; critical gaps in our knowledge of this disease remain. The identification of novel molecular biomarkers remains a focus of the greater cancer community as a method to improve the consistency and accuracy of pathological diagnosis. In addition, novel molecular biomarkers are drastically needed for the identification of targets that may ultimately result in novel therapeutics aimed at improving glioma treatment. Through the identification of new biomarkers, laboratories will focus future studies on the molecular mechanisms that underlie glioma development. Here, we report a series of genomic analyses identifying novel molecular biomarkers in multiple histopathological subtypes of glioma and refine the classification of malignant gliomas. We have completed a large scale analysis of the WHO grade II-III astrocytoma exome and report frequent mutations in the chromatin modifier, alpha thalassemia mental retardation x-linked (ATRX), isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2), and mutations in tumor protein 53 (TP53) as the most frequent genetic mutations in low grade astrocytomas. Furthermore, by analyzing the status of recurrently mutated genes in 363 brain tumors, we establish that highly recurrent gene mutational signatures are an effective tool in stratifying homogeneous patient populations into distinct groups with varying outcomes, thereby capable of predicting prognosis. Next, we have established mutations in the promoter of telomerase reverse transcriptase (TERT) as a frequent genetic event in gliomas and in tissues with low rates of self renewal. We identify TERT promoter mutations as the most frequently mutated gene in primary glioblastoma. Additionally, we show that TERT promoter mutations in combination with IDH1 and IDH2 mutations are able to delineate distinct clinical tumor cohorts and are capable of predicting median overall survival more effectively than standard histopathological diagnosis alone. Taken together, these data advance our understanding of the genetic alterations that underlie the transformation of glial cells into neoplasms and we provide novel genetic biomarkers and multi – gene mutational signatures that can be utilized to refine the classification of malignant gliomas and provide opportunity for improved diagnosis.

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STUDY DESIGN: The inflammatory responses of primary human intervertebral disc (IVD) cells to tumor necrosis factor α (TNF-α) and an antagonist were evaluated in vitro. OBJECTIVE: To investigate an ability for soluble TNF receptor type II (sTNFRII) to antagonize TNF-α-induced inflammatory events in primary human IVD cells in vitro. SUMMARY OF BACKGROUND DATA: TNF-α is a known mediator of inflammation and pain associated with radiculopathy and IVD degeneration. sTNFRs and their analogues are of interest for the clinical treatment of these IVD pathologies, although information on the effects of sTNFR on human IVD cells remains unknown. METHODS: IVD cells were isolated from surgical tissues procured from 15 patients and cultured with or without 1.4 nmol/L TNF-α (25 ng/mL). Treatment groups were coincubated with varying doses of sTNFRII (12.5-100 nmol/L). Nitric oxide (NO), prostaglandin E₂ (PGE₂), and interleukin-6 (IL6) levels in media were quantified to characterize the inflammatory phenotype of the IVD cells. RESULTS: Across all patients, TNF-α induced large, statistically significant increases in NO, PGE₂, and IL6 secretion from IVD cells compared with controls (60-, 112-, and 4-fold increases, respectively; P < 0.0001). Coincubation of TNF-α with nanomolar doses of sTNFRII significantly attenuated the secretion of NO and PGE₂ in a dose-dependent manner, whereas IL6 levels were unchanged. Mean IC₅₀ values for NO and PGE₂ were found to be 35.1 and 20.5 nmol/L, respectively. CONCLUSION: Nanomolar concentrations of sTNFRII were able to significantly attenuate the effects of TNF-α on primary human IVD cells in vitro. These results suggest this sTNFR to be a potent TNF antagonist with potential to attenuate inflammation in IVD pathology.

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Since at least the early 1990s, stage and risk migration have been seen in patients with prostate cancer, likely corresponding to the institution of prostate specific antigen (PSA) screening in health systems. Preoperative risk factors, including PSA level and clinical stage, have decreased significantly. These improved prognostic variables have led to a larger portion of men being stratified with low-risk disease, as per the classification of D'Amico and associates. This, in turn, has corresponded with more favorable postoperative variables, including decreased extraprostatic tumor extension and prolonged biochemical-free recurrence rates. The advent of focal therapy is bolstered by findings of increased unilateral disease with decreased tumor volume. Increasingly, targeted or delayed therapies may be possible within the current era of lower risk disease.

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Surgery is one of the most effective and widely used procedures in treating human cancers, but a major problem is that the surgeon often fails to remove the entire tumor, leaving behind tumor-positive margins, metastatic lymph nodes, and/or satellite tumor nodules. Here we report the use of a hand-held spectroscopic pen device (termed SpectroPen) and near-infrared contrast agents for intraoperative detection of malignant tumors, based on wavelength-resolved measurements of fluorescence and surface-enhanced Raman scattering (SERS) signals. The SpectroPen utilizes a near-infrared diode laser (emitting at 785 nm) coupled to a compact head unit for light excitation and collection. This pen-shaped device effectively removes silica Raman peaks from the fiber optics and attenuates the reflected excitation light, allowing sensitive analysis of both fluorescence and Raman signals. Its overall performance has been evaluated by using a fluorescent contrast agent (indocyanine green, or ICG) as well as a surface-enhanced Raman scattering (SERS) contrast agent (pegylated colloidal gold). Under in vitro conditions, the detection limits are approximately 2-5 × 10(-11) M for the indocyanine dye and 0.5-1 × 10(-13) M for the SERS contrast agent. Ex vivo tissue penetration data show attenuated but resolvable fluorescence and Raman signals when the contrast agents are buried 5-10 mm deep in fresh animal tissues. In vivo studies using mice bearing bioluminescent 4T1 breast tumors further demonstrate that the tumor borders can be precisely detected preoperatively and intraoperatively, and that the contrast signals are strongly correlated with tumor bioluminescence. After surgery, the SpectroPen device permits further evaluation of both positive and negative tumor margins around the surgical cavity, raising new possibilities for real-time tumor detection and image-guided surgery.

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Responsive biomaterials play important roles in imaging, diagnostics, and therapeutics. Polymeric nanoparticles (NPs) containing hydrophobic and hydrophilic segments are one class of biomaterial utilized for these purposes. The incorporation of luminescent molecules into NPs adds optical imaging and sensing capability to these vectors. Here we report on the synthesis of dual-emissive, pegylated NPs with "stealth"-like properties, delivered intravenously (IV), for the study of tumor accumulation. The NPs were created by means of stereocomplexation using a methoxy-terminated polyethylene glycol and poly(D-lactide) (mPEG-PDLA) block copolymer combined with iodide-substituted difluoroboron dibenzoylmethane-poly(L-lactide) (BF2dbm(I)PLLA). Boron nanoparticles (BNPs) were fabricated in two different solvent compositions to study the effects on BNP size distribution. The physical and photoluminescent properties of the BNPs were studied in vitro over time to determine stability. Finally, preliminary in vivo results show that stereocomplexed BNPs injected IV are taken up by tumors, an important prerequisite to their use as hypoxia imaging agents in preclinical studies.

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As many as 20-70% of patients undergoing breast conserving surgery require repeat surgeries due to a close or positive surgical margin diagnosed post-operatively [1]. Currently there are no widely accepted tools for intra-operative margin assessment which is a significant unmet clinical need. Our group has developed a first-generation optical visible spectral imaging platform to image the molecular composition of breast tumor margins and has tested it clinically in 48 patients in a previously published study [2]. The goal of this paper is to report on the performance metrics of the system and compare it to clinical criteria for intra-operative tumor margin assessment. The system was found to have an average signal to noise ratio (SNR) >100 and <15% error in the extraction of optical properties indicating that there is sufficient SNR to leverage the differences in optical properties between negative and close/positive margins. The probe had a sensing depth of 0.5-2.2 mm over the wavelength range of 450-600 nm which is consistent with the pathologic criterion for clear margins of 0-2 mm. There was <1% cross-talk between adjacent channels of the multi-channel probe which shows that multiple sites can be measured simultaneously with negligible cross-talk between adjacent sites. Lastly, the system and measurement procedure were found to be reproducible when evaluated with repeated measures, with a low coefficient of variation (<0.11). The only aspect of the system not optimized for intra-operative use was the imaging time. The manuscript includes a discussion of how the speed of the system can be improved to work within the time constraints of an intra-operative setting.

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BACKGROUND: The conventional treatment protocol in high-intensity focused ultrasound (HIFU) therapy utilizes a dense-scan strategy to produce closely packed thermal lesions aiming at eradicating as much tumor mass as possible. However, this strategy is not most effective in terms of inducing a systemic anti-tumor immunity so that it cannot provide efficient micro-metastatic control and long-term tumor resistance. We have previously provided evidence that HIFU may enhance systemic anti-tumor immunity by in situ activation of dendritic cells (DCs) inside HIFU-treated tumor tissue. The present study was conducted to test the feasibility of a sparse-scan strategy to boost HIFU-induced anti-tumor immune response by more effectively promoting DC maturation. METHODS: An experimental HIFU system was set up to perform tumor ablation experiments in subcutaneous implanted MC-38 and B16 tumor with dense- or sparse-scan strategy to produce closely-packed or separated thermal lesions. DCs infiltration into HIFU-treated tumor tissues was detected by immunohistochemistry and flow cytometry. DCs maturation was evaluated by IL-12/IL-10 production and CD80/CD86 expression after co-culture with tumor cells treated with different HIFU. HIFU-induced anti-tumor immune response was evaluated by detecting growth-retarding effects on distant re-challenged tumor and tumor-specific IFN-gamma-secreting cells in HIFU-treated mice. RESULTS: HIFU exposure raised temperature up to 80 degrees centigrade at beam focus within 4 s in experimental tumors and led to formation of a well-defined thermal lesion. The infiltrated DCs were recruited to the periphery of lesion, where the peak temperature was only 55 degrees centigrade during HIFU exposure. Tumor cells heated to 55 degrees centigrade in 4-s HIFU exposure were more effective to stimulate co-cultured DCs to mature. Sparse-scan HIFU, which can reserve 55 degrees-heated tumor cells surrounding the separated lesions, elicited an enhanced anti-tumor immune response than dense-scan HIFU, while their suppressive effects on the treated primary tumor were maintained at the same level. Flow cytometry analysis showed that sparse-scan HIFU was more effective than dense-scan HIFU in enhancing DC infiltration into tumor tissues and promoting their maturation in situ. CONCLUSION: Optimizing scan strategy is a feasible way to boost HIFU-induced anti-tumor immunity by more effectively promoting DC maturation.

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Glioblastomas are deadly cancers that display a functional cellular hierarchy maintained by self-renewing glioblastoma stem cells (GSCs). GSCs are regulated by molecular pathways distinct from the bulk tumor that may be useful therapeutic targets. We determined that A20 (TNFAIP3), a regulator of cell survival and the NF-kappaB pathway, is overexpressed in GSCs relative to non-stem glioblastoma cells at both the mRNA and protein levels. To determine the functional significance of A20 in GSCs, we targeted A20 expression with lentiviral-mediated delivery of short hairpin RNA (shRNA). Inhibiting A20 expression decreased GSC growth and survival through mechanisms associated with decreased cell-cycle progression and decreased phosphorylation of p65/RelA. Elevated levels of A20 in GSCs contributed to apoptotic resistance: GSCs were less susceptible to TNFalpha-induced cell death than matched non-stem glioma cells, but A20 knockdown sensitized GSCs to TNFalpha-mediated apoptosis. The decreased survival of GSCs upon A20 knockdown contributed to the reduced ability of these cells to self-renew in primary and secondary neurosphere formation assays. The tumorigenic potential of GSCs was decreased with A20 targeting, resulting in increased survival of mice bearing human glioma xenografts. In silico analysis of a glioma patient genomic database indicates that A20 overexpression and amplification is inversely correlated with survival. Together these data indicate that A20 contributes to glioma maintenance through effects on the glioma stem cell subpopulation. Although inactivating mutations in A20 in lymphoma suggest A20 can act as a tumor suppressor, similar point mutations have not been identified through glioma genomic sequencing: in fact, our data suggest A20 may function as a tumor enhancer in glioma through promotion of GSC survival. A20 anticancer therapies should therefore be viewed with caution as effects will likely differ depending on the tumor type.

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Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers.

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Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

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Nanomedicine has attracted increasing attention in recent years, because it offers great promise to provide personalized diagnostics and therapy with improved treatment efficacy and specificity. In this study, we developed a gold nanostar (GNS) probe for multi-modality theranostics including surface-enhanced Raman scattering (SERS) detection, x-ray computed tomography (CT), two-photon luminescence (TPL) imaging, and photothermal therapy (PTT). We performed radiolabeling, as well as CT and optical imaging, to investigate the GNS probe's biodistribution and intratumoral uptake at both macroscopic and microscopic scales. We also characterized the performance of the GNS nanoprobe for in vitro photothermal heating and in vivo photothermal ablation of primary sarcomas in mice. The results showed that 30-nm GNS have higher tumor uptake, as well as deeper penetration into tumor interstitial space compared to 60-nm GNS. In addition, we found that a higher injection dose of GNS can increase the percentage of tumor uptake. We also demonstrated the GNS probe's superior photothermal conversion efficiency with a highly concentrated heating effect due to a tip-enhanced plasmonic effect. In vivo photothermal therapy with a near-infrared (NIR) laser under the maximum permissible exposure (MPE) led to ablation of aggressive tumors containing GNS, but had no effect in the absence of GNS. This multifunctional GNS probe has the potential to be used for in vivo biosensing, preoperative CT imaging, intraoperative detection with optical methods (SERS and TPL), as well as image-guided photothermal therapy.

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BACKGROUND: Antibodies (Abs) to the HPV16 proteome increase risk for HPV-associated OPC (HPVOPC). The goal of this study was to investigate the association of a panel of HPV16 Abs with risk for OPC as well as the association of these Abs with tumor HPV and smoking status among patients with OPC. METHODS: IgG Abs to the HPV16 antigens E1, E2, E4, E5, E6, E7, L1, L2 were quantified using a programmable ELISA assay. Sera were obtained from 258 OPC patients at diagnosis and 250 healthy controls. HPV16 tumor status was measured by PCR for 137 cases. Multivariable logistic regression was used to calculate odds ratios for the association of HPV16 Abs with risk for OPC. RESULTS: HPV16 E1, E2, E4, E5, E6, E7 and L1-specific IgG levels were elevated in OPC patients compared to healthy controls (p<0.05). After multivariable adjustment, Ab positivity for NE2, CE2, E6, and/or E7 was associated with OPC risk (OR [95% CI], 249.1 [99.3-624.9]). Among patients with OPC, Ab positivity for these antigens was associated with tumor HPV status, especially among never or light smokers (OR [95% CI], 6.5 [2.1-20.1] and OR [95% CI], 17.5 [4.0-77.2], respectively). CONCLUSIONS: Antibodies to HPV16 proteins are associated with increased risk for HPVOPC. Among patients with OPC, HPV16 Abs are associated with tumor HPV status, in particular among HPV positive patients with no or little smoking history.

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A human endogenous retrovirus type E (HERV-E) was recently found to be selectively expressed in most renal cell carcinomas (RCCs). Importantly, antigens derived from this provirus are immunogenic, stimulating cytotoxic T cells that kill RCC cells in vitro and in vivo. Here, we show HERV-E expression is restricted to the clear cell subtype of RCC (ccRCC) characterized by an inactivation of the von Hippel-Lindau (VHL) tumor-suppressor gene with subsequent stabilization of hypoxia-inducible transcription factors (HIFs)-1α and -2α. HERV-E expression in ccRCC linearly correlated with HIF-2α levels and could be silenced in tumor cells by either transfection of normal VHL or small interfering RNA inhibition of HIF-2α. Using chromatin immunoprecipitation, we demonstrated that HIF-2α can serve as transcriptional factor for HERV-E by binding with HIF response element (HRE) localized in the proviral 5' long terminal repeat (LTR). Remarkably, the LTR was found to be hypomethylated only in HERV-E-expressing ccRCC while other tumors and normal tissues possessed a hypermethylated LTR preventing proviral expression. Taken altogether, these findings provide the first evidence that inactivation of a tumor suppressor gene can result in aberrant proviral expression in a human tumor and give insights needed for translational research aimed at boosting human immunity against antigenic components of this HERV-E.