Bino Varghese

Truncating Mutation in the Autophagy Gene UVRAG Confers Oncogenic Properties and Chemosensitivity in Colorectal Cancers

Autophagy-related factors are implicated in metabolic adaptation and cancer metastasis. However, the role of autophagy factors in cancer progression and their effect in treatment response remain largely elusive. Recent studies have shown that UVRAG, a key autophagic tumour suppressor, is mutated in common human cancers. Here we demonstrate that the cancer-related UVRAG frameshift (FS), which does not result in a null mutation, is expressed as a truncated UVRAGFS in colorectal cancer (CRC) with microsatellite instability (MSI), and promotes tumorigenesis. UVRAGFS abrogates the normal functions of UVRAG, including autophagy, in a dominant-negative manner. Furthermore, expression of UVRAGFS can trigger CRC metastatic spread through Rac1 activation and epithelial-to-mesenchymal transition, independently of autophagy. Interestingly, UVRAGFS expression renders cells more sensitive to standard chemotherapy regimen due to a DNA repair defect. These results identify UVRAG as a new MSI target gene and provide a mechanism for UVRAG participation in CRC pathogenesis and treatment response.

A Microfluidic Technique to Probe Cell Deformability

Here we detail the design, fabrication, and use of a microfluidic device to evaluate the deformability of a large number of individual cells in an efficient manner. Typically, data for ~10(2) cells can be acquired within a 1 hr experiment. An automated image analysis program enables efficient post-experiment analysis of image data, enabling processing to be complete within a few hours. Our device geometry is unique in that cells must deform through a series of micron-scale constrictions, thereby enabling the initial deformation and time-dependent relaxation of individual cells to be assayed. The applicability of this method to human promyelocytic leukemia (HL-60) cells is demonstrated. Driving cells to deform through micron-scale constrictions using pressure-driven flow, we observe that human promyelocytic (HL-60) cells momentarily occlude the first constriction for a median time of 9.3 msec before passaging more quickly through the subsequent constrictions with a median transit time of 4.0 msec per constriction. By contrast, all-trans retinoic acid-treated (neutrophil-type) HL-60 cells occlude the first constriction for only 4.3 msec before passaging through the subsequent constrictions with a median transit time of 3.3 msec. This method can provide insight into the viscoelastic nature of cells, and ultimately reveal the molecular origins of this behavior.

Quantitative Contour Analysis as an Image-based Discriminator Between Benign and Malignant Renal Tumors

OBJECTIVE To investigate whether morphologic analysis can differentiate between benign and malignant renal tumors on clinically acquired imaging. MATERIALS AND METHODS Between 2009 and 2014, 3-dimensional tumor volumes were manually segmented from contrast-enhanced computerized tomography (CT) images from 150 patients with predominantly solid, nonmacroscopic fat-containing renal tumors: 100 renal cell carcinomas and 50 benign lesions (eg, oncocytoma and lipid-poor angiomyolipoma). Tessellated 3-dimensional tumor models were created from segmented voxels using MATLAB code. Eleven shape descriptors were calculated: sphericity, compactness, mean radial distance, standard deviation of the radial distance, radial distance area ratio, zero crossing, entropy, Feret ratio, convex hull area and convex hull perimeter ratios, and elliptic compactness. Morphometric parameters were compared using the Wilcoxon rank-sum test to investigate whether malignant renal masses demonstrate more morphologic irregularity than benign ones. RESULTS Only CHP in sagittal orientation (median 0.96 vs 0.97) and EC in coronal orientation (median 0.92 vs 0.93) differed significantly between malignant and benign masses (P = .04). When comparing these 2 metrics between coronal and sagittal orientations, similar but nonsignificant trends emerged (P = .07). Other metrics tested were not significantly different in any imaging plane. CONCLUSION Computerized image analysis is feasible using shape descriptors that otherwise cannot be visually assessed and used without quantification. Shape analysis via the transverse orientation may be reasonable, but encompassing all 3 planar dimensions to characterize tumor contour can achieve a more comprehensive evaluation. Two shape metrics (CHP and EC) may help distinguish benign from malignant renal tumors, an often challenging goal to achieve on imaging and biopsy.

Claudin-18–mediated YAP activity regulates lung stem and progenitor cell homeostasis and tumorigenesis

Claudins, the integral tight junction (TJ) proteins that regulate paracellular permeability and cell polarity, are frequently dysregulated in cancer; however, their role in neoplastic progression is unclear. Here, we demonstrated that knockout of Cldn18, a claudin family member highly expressed in lung alveolar epithelium, leads to lung enlargement, parenchymal expansion, increased abundance and proliferation of known distal lung progenitors, the alveolar epithelial type II (AT2) cells, activation of Yes-associated protein (YAP), increased organ size, and tumorigenesis in mice. Inhibition of YAP decreased proliferation and colony-forming efficiency (CFE) of Cldn18–/– AT2 cells and prevented increased lung size, while CLDN18 overexpression decreased YAP nuclear localization, cell proliferation, CFE, and YAP transcriptional activity. CLDN18 and YAP interacted and colocalized at cell-cell contacts, while loss of CLDN18 decreased YAP interaction with Hippo kinases p-LATS1/2. Additionally, Cldn18–/– mice had increased propensity to develop lung adenocarcinomas (LuAd) with age, and human LuAd showed stage-dependent reduction of CLDN18.1. These results establish CLDN18 as a regulator of YAP activity that serves to restrict organ size, progenitor cell proliferation, and tumorigenesis, and suggest a mechanism whereby TJ disruption may promote progenitor proliferation to enhance repair following injury.

Fast Fourier transform-based analysis of renal masses on contrast-enhanced computed tomography images for grading of tumor

Purpose: Evaluate the feasibility of spectral analysis, particularly fast fourier transform (FFT), to help clinicians differentiate clear cell renal cell carcinoma (ccRCC) tumor grades using contrast-enhanced computed tomography (CECT) images of renal masses, quantitatively, and compare their performance to the Fuhrman grading system. Materials and Methods: Regions of interest of the whole lesion were manually segmented and co-registered from multiphase CT acquisitions of 95 patients with ccRCC. Here, FFT is employed to objectively quantify the texture of a tumor surface by evaluating tissue gray-level patterns and automatically measure frequency-based texture metrics. An independent t-test or a Wilcoxon rank sum test (depending on the data distribution) was used to determine if the spectral analysis metrics would produce statistically significant differences between the tumor grades. Receiver operating characteristic (ROC) curve analysis was used to evaluate the usefulness of spectral metrics in predicting the ccRCC grade. Results: The Wilcoxon test showed that there was a significant difference in complexity index between the different tumor grades, p < 0.01 at all the four phases of CECT acquisition. In all cases a positive correlation was observed between tumor grade and complexity index. ROC analysis revealed the importance of the entropy of FFT amplitude, FFT phase and complexity index and its ability to identify grade 1 and grade 4 tumors from the rest of the population. Conclusion: Our study suggests that FFT-based spectral metrics can differentiate between ccRCC grades, and in combination with other metrics improve patient management and prognosis of renal masses.

MP72-18 ASSOCIATION OF COMPUTED TOMOGRAPHY-BASED RADIOMIC FEATURES WITH EPIGENETIC VARIATION OF CLEAR CELL RENAL CELL CARCINOMA USING DNA METHYLATION

either ccA (less aggressive) or ccB (more aggressive) molecular subtypes. Age-and sex-adjusted logistic regression models estimated associations between sarcopenia and molecular subtype separately for obese and non-obese patients. Statistical significance was regarded as a p-value of<0.05. RESULTS: The cohort was predominantly male (77%), white (97%), and had localized disease (62%). Median age was 58.7 years (IQR: 34-86.7). Overall, 53% of patients were obese, 39% were sarcopenic, and 58% of tumors were ccB subtype. Sarcopenic patients were more likely to have ccB tumors (66.7%) compared to patients without sarcopenia (26.1%) p1⁄40.00008. Among patients who were not obese, aggressive ccB subtype was more common in sarcopenic (69.6%) than non-sarcopenic patients (30.8%) (p1⁄40.03). A similar pattern was observed among patients who were obese; aggressive ccB subtype was more common in sarcopenic (57.1%) than non-sarcopenic patients (24.2%) (p1⁄40.04). CONCLUSIONS: While preliminary, our findings suggest that sarcopenia is associated with aggressive ccRCC regardless of obesity and lend biologic support to the observation that sarcopenia is associated with poor prognosis. It is not clear whether sarcopenia is a cause or consequence of tumor aggressiveness. RNA-Seq analysis of tumor tissue is being carried out to explore specific mechanisms underlying these observations.

Avian tail ontogeny, pygostyle formation, and interpretation of juvenile Mesozoic specimens

The avian tail played a critical role in the evolutionary transition from long- to short-tailed birds, yet its ontogeny in extant birds has largely been ignored. This deficit has hampered efforts to effectively identify intermediate species during the Mesozoic transition to short tails. Here we show that fusion of distal vertebrae into the pygostyle structure does not occur in extant birds until near skeletal maturity, and mineralization of vertebral processes also occurs long after hatching. Evidence for post-hatching pygostyle formation is also demonstrated in two Cretaceous specimens, a juvenile enantiornithine and a subadult basal ornithuromorph. These findings call for reinterpretations of Zhongornis haoae, a Cretaceous bird hypothesized to be an intermediate in the long- to short-tailed bird transition, and of the recently discovered coelurosaur tail embedded in amber. Zhongornis, as a juvenile, may not yet have formed a pygostyle, and the amber-embedded tail specimen is reinterpreted as possibly avian. Analyses of relative pygostyle lengths in extant and Cretaceous birds suggests the number of vertebrae incorporated into the pygostyle has varied considerably, further complicating the interpretation of potential transitional species. In addition, this analysis of avian tail development reveals the generation and loss of intervertebral discs in the pygostyle, vertebral bodies derived from different kinds of cartilage, and alternative modes of caudal vertebral process morphogenesis in birds. These findings demonstrate that avian tail ontogeny is a crucial parameter specifically for the interpretation of Mesozoic specimens, and generally for insights into vertebrae formation.

A Decision-Support Tool for Renal Mass Classification

We investigate the viability of statistical relational machine learning algorithms for the task of identifying malignancy of renal masses using radiomics-based imaging features. Features characterizing the texture, signal intensity, and other relevant metrics of the renal mass were extracted from multiphase contrast-enhanced computed tomography images. The recently developed formalism of relational functional gradient boosting (RFGB) was used to learn human-interpretable models for classification. Experimental results demonstrate that RFGB outperforms many standard machine learning approaches as well as the current diagnostic gold standard of visual qualification by radiologists.

Computed tomography-based texture analysis of bladder cancer: differentiating urothelial carcinoma from micropapillary carcinoma

PurposeThe purpose of the study is to determine the feasibility of using computed tomography-based texture analysis (CTTA) in differentiating between urothelial carcinomas (UC) of the bladder from micropapillary carcinomas (MPC) of the bladder.MethodsRegions of interests (ROIs) of computerized tomography (CT) images of 33 MPCs and 33 UCs were manually segmented and saved. Custom MATLAB code was used to extract voxel information corresponding to the ROI. The segmented tumors were input to a pre-existing radiomics platform with a CTTA panel. A total of 58 texture metrics were extracted using four different texture extraction techniques and statistically analyzed using a Wilcoxon rank-sum test to determine the differences between UCs and MPCs.ResultsOf the 58 texture metrics extracted using the gray level co-occurrence matrix (GLCM) and gray level difference matrix (GLDM), 28 texture metrics were statistically significant (p < 0.05) for differences in tumor textures and 27 texture metrics were statistically significant (p < 0.05) for peritumoral fat textures. The remaining nine metrics extracted using histogram and fast Fourier transform analyses did not show significant differences between the textures of the tumors and their peritumoral fat.ConclusionsCTTA shows that MPC have a more heterogeneous texture compared to UC. As visual discrimination of MPC from UC from clinical CT scans are difficult, results from this study suggest that tumor heterogeneity extracted using GLCM and GLDM may be a good imaging aid in segregating MPC from UC. This tool can aid clinicians in further sub-classifying bladder cancers on routine imaging, a process which has potential to alter treatment and patient care.

MP08-13 MR RADIOMICS IN THE RISK STRATIFICATION OF PROSTATE CANCER

INTRODUCTION AND OBJECTIVES: The current paradigm in prostate cancer risk stratification, including DRE, PSA values, and prostate biopsy, has resulted in overdiagnosis and overtreatment. A noninvasive marker is needed to more accurately differentiate between aggressive and indolent disease. This study evaluated multiparametric magnetic resonance imaging (mpMRI)-derived texture metrics as a biomarker for prostate cancer risk stratification. METHODS: In this IRB approved, retrospective study, we identified 66 prostate cancer lesions in patients who underwent 3T mpMRI prior to prostate biopsy. Biopsy proven Prostate cancer lesions were divided into high, intermediate, and low risk categories per National Comprehensive Cancer Network guidelines. Lesion regions of interest were manually segmented from apparent diffusion coefficient (ADC) and T2 weighted images (T2WI). Texture analysis was performed using gray-level co-occurrence matrices (GLCM), fast Fourier transfer-based spectral metrics, and ADC and T2 signal intensity. Kruskall Wallis test and analysis of variance were used to determine if there is an association between texture metrics and prostate cancer risk categories. Stepwise logistic regression was used to select the best predictors in discriminating high risk lesions from other lesions. RESULTS: Of the spectral metrics, Complexity Index on ADC and T2WI was significantly different (p<0.01) between the risk categories. ADC-derived GLCM metrics variance, contrast, homogeneity, dissimilarity, and difference of average were significantly different (p<0.01) between the risk categories. Of the texture metrics, GLCM Variance on ADC (ADC_Var) and Information Measures of Correlation 1 on T2WI (T2_ICM1) were the best metrics in discriminating high risk lesions from intermediate and low risk lesions and were selected in the final prediction model. Used alone, the areas under the receiver operator curve (AUC) for ADC_Var and T2_IMC1 were 0.77 (95%CI: 0.64-0.9) and 0.71 (95%CI: 0.59-0.82) respectively. The AUC when using both metrics together was 0.83 (95%CI: 0.72-0.94). CONCLUSIONS: mpMRI-based texture analysis can differentiate high risk prostate cancer lesions from intermediate and low risk lesions, demonstrating promise as a biomarker for prostate cancer risk stratification.