Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer

Liquid biopsies, examinations of tumor components in body fluids, have shown promise for predicting clinical outcomes. To evaluate tumor-associated genomic and genetic variations in plasma cell-free DNA (cfDNA) and their associations with treatment response and overall survival, we applied whole genome and targeted sequencing to examine the plasma cfDNAs derived from 20 patients with advanced prostate cancer. Sequencing-based genomic abnormality analysis revealed locus-specific gains or losses that were common in prostate cancer, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. To estimate tumor burden in cfDNA, we developed a Plasma Genomic Abnormality (PGA) score by summing the most significant copy number variations. Cox regression analysis showed that PGA scores were significantly associated with overall survival (p < 0.04). After androgen deprivation therapy or chemotherapy, targeted sequencing showed significant mutational profile changes in genes involved in androgen biosynthesis, AR activation, DNA repair, and chemotherapy resistance. These changes may reflect the dynamic evolution of heterozygous tumor populations in response to these treatments. These results strongly support the feasibility of using non-invasive liquid biopsies as potential tools to study biological mechanisms underlying therapy-specific resistance and to predict disease progression in advanced prostate cancer.

Predicting time to castration resistance in hormone sensitive prostate cancer by a personalization algorithm based on a mechanistic model integrating patient data

BACKGROUND

Prostate cancer (PCa) is a leading cause of cancer death of men worldwide. In hormone-sensitive prostate cancer (HSPC), androgen deprivation therapy (ADT) is widely used, but an eventual failure on ADT heralds the passage to the castration-resistant prostate cancer (CRPC) stage. Because predicting time to failure on ADT would allow improved planning of personal treatment strategy, we aimed to develop a predictive personalization algorithm for ADT efficacy in HSPC patients.

METHODS

A mathematical mechanistic model for HSPC progression and treatment was developed based on the underlying disease dynamics (represented by prostate-specific antigen; PSA) as affected by ADT. Following fine-tuning by a dataset of ADT-treated HSPC patients, the model was embedded in an algorithm, which predicts the patient's time to biochemical failure (BF) based on clinical metrics obtained before or early in-treatment.

RESULTS

The mechanistic model, including a tumor growth law with a dynamic power and an elaborate ADT-resistance mechanism, successfully retrieved individual time-courses of PSA (R(2) = 0.783). Using the personal Gleason score (GS) and PSA at diagnosis, as well as PSA dynamics from 6 months after ADT onset, and given the full ADT regimen, the personalization algorithm accurately predicted the individual time to BF of ADT in 90% of patients in the retrospective cohort (R(2) = 0.98).

CONCLUSIONS

The algorithm we have developed, predicting biochemical failure based on routine clinical tests, could be especially useful for patients destined for short-lived ADT responses and quick progression to CRPC. Prospective studies must validate the utility of the algorithm for clinical decision-making.

Whole blood defensin mRNA expression is a predictive biomarker of docetaxel response in castration-resistant prostate cancer

This study tested the potential of circulating RNA-based signals as predictive biomarkers for docetaxel response in patients with metastatic castration-resistant prostate cancer (CRPC). RNA was analyzed in blood from six CRPC patients by whole-transcriptome sequencing (total RNA-sequencing) before and after docetaxel treatment using the Illumina’s HiSeq platform. Targeted RNA capture and sequencing was performed in an independent cohort of ten patients with CRPC matching the discovery cohort to confirm differential expression of the genes. Response to docetaxel was defined on the basis of prostate-specific antigen levels and imaging criteria. Two-way analysis of variance was used to compare differential gene expression in patients classified as responders versus nonresponders before and after docetaxel treatment. Thirty-four genes with two-fold differentially expressed transcripts in responders versus nonresponders were selected from total RNA-sequencing for further validation. Targeted RNA capture and sequencing showed that 13/34 genes were differentially expressed in responders. Alpha defensin genes DEFA1, DEFA1B, and DEFA3 exhibited significantly higher expression in responder patients compared with nonresponder patients before administration of chemotherapy (fold change >2.5). In addition, post-docetaxel treatment significantly increased transcript levels of these defensin genes in responders (fold change >2.8). Our results reveal that patients with higher defensin RNA transcripts in blood respond well to docetaxel therapy. We suggest that monitoring DEFA1, DEFA1B, and DEFA3 RNA transcripts in blood prior to treatment will be helpful to determine which patients are better candidates to receive docetaxel chemotherapy.

The effect of liraglutide on endothelial function in patients with type 2 diabetes

This single-centre, 12-week, double-blind, placebo-controlled trial assessed how the human glucagon-like-peptide 1 analogue liraglutide impacted endothelial function in adult patients (n = 49) with type 2 diabetes and no overt cardiovascular disease. Patients were randomized to liraglutide, placebo or glimepiride. At baseline and Week 12, venous occlusion plethysmography was used to measure forearm blood flow (FBF) in response to acetylcholine (ACh) and sodium nitroprusside (SNP) before and after (L)-N(G)-monomethyl arginine (L-NMMA) infusion. At Week 12, ACh-mediated FBF increased with liraglutide and decreased with placebo; however, the between-treatment difference was not significant (p = 0.055). Inhibition of ACh-mediated FBF after L-NMMA infusion increased with liraglutide and decreased with placebo; this between-treatment difference was also not significant (p = 0.149). No change in FBF was observed with SNP. Liraglutide did not significantly impact endothelium-dependent vasodilation after 12 weeks; however, additional investigations looking at the effect of liraglutide on endothelial function in alternative vasculature and during the postprandial period are warranted.

Exosomal miR-1290 and miR-375 as prognostic markers in castration-resistant prostate cancer

BACKGROUND

Extracellular microRNAs (miRNAs) embedded in circulating exosomes may serves as prognostic biomarkers in cancer.

OBJECTIVE

To identify and evaluate plasma exosomal miRNAs for prognosis in castration-resistant prostate cancer (CRPC).

DESIGN, SETTING, AND PARTICIPANTS

RNA sequencing was performed to identify candidate exosomal miRNAs associated with overall survival in a screening cohort of 23 CRPC patients. Candidate miRNAs were further evaluated for prognosis using quantitative real-time polymerase chain reaction in a follow-up cohort of 100 CRPC patients.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Cox regression and Kaplan-Meier survival analyses were used to evaluate survival association using candidate miRNAs along with clinical prognostic factors.

RESULTS AND LIMITATIONS

RNA sequencing in screening cohort generated approximately 6.80 million mappable reads per patient. Of those with normalized read counts ≥ 5, 43% were mapped to miRNAs for a total of 375 known and 57 novel miRNAs. Cox regression analysis identified an association of miR-1290, -1246, and -375 with overall survival (false discover rate < 0.05). Of those, higher levels of miR-1290 and -375 were significantly associated with poor overall survival (p < 0.004) in the follow-up cohort. Incorporation of miR-1290/-375 into putative clinical prognostic factors-based models in CRPC stage significantly improved predictive performance with a time-dependent area under the curve increase from 0.66 to 0.73 (p = 6.57 × 10(-6)).

CONCLUSIONS

Plasma exosomal miR-1290 and miR-375 are promising prognostic biomarkers for CRPC patients. Prospective validation is needed for further evaluation of these candidate miRNAs.

PATIENT SUMMARY

In this study, we evaluated whether small RNAs circulating in blood could be used to predict clinical outcomes in late-stage prostate cancer patients. We identified two blood-based small RNAs whose levels showed significant association with survival. Our results warrant further investigation because the noninvasive blood-based test has great potential in the management of late-stage prostate cancer.

Exosomal microRNA as prognostic biomarkers in metastatic castrate-resistant prostate cancer (mCRPC)

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Background: The purpose of this study was to evaluate cell free nucleic acid based biomarkers for prognosis in mCRPC stage. Methods: Uniformly collected blood from mCRPC patients was processed for plasma which was used for exosomal RNA extraction. RNA sequencing was applied to examine microRNA (miRNA) profiles initially in a discovery cohort of 23 mCRPC patients. The sequences from fastq files were mapped to human miRBase (release 19) for known miRNA read counts. A software package (miRDeep2) was used for novel miRNA prediction. Cox regression was used for association of candidate miRNAs with overall survival (OS), defined as time from development of mCRPC to death or last follow up after adjusting for Gleason Score (GS) and time on androgen deprivation (AD) for hormone sensitive disease. miRNAs significantly associated with OS (FDR<0.05) were then validated in an independent cohort of 100 mCRPC subjects using univariate Cox regression. Results: RNA sequencing generated >10 million mappable reads per specimen in the discovery cohort. Among these reads ~50% were known miRNAs which included 1237 unique RNA sequences. Due to low abundance of most RNA transcripts, only miRNAs (n=250) with >/= 32 reads (on average) were analyzed. Four mRNAs (miR-1290, -1246, -375 and a predicted miRNA on chr. 12) were associated with OS(FDR<0.05). These were evaluated as prognotic markers in the independent cohort (N=100) using real time RT-PCR. Median time on AD for this cohort prior to progression to mCRPC was 35.7 (range: 3.5-136) months; median GS was 7; median follow up after mCRPC development was 12.5 (1-41) months at which time 28 patients had died. Elevated expression for miR-1290 and -375 were associated with shorter OS after adjusting for GS and AD time with a Hazard Ratio (HR) for miR-375 of 1.19 (CI: 1.006-1.18); (p=0.04) and a HR for miR1290 of 1.58 (CI:1.01-2.4); (p=0.04). A stronger association with shorter OS was observed for elevated expression of both miRs-HR of 2.02 (CI: 1.1-3.6) (p=0.01). Conclusions: Blood-based nucleic acid assays are easily accessible for biomarker development in mCRPC. Results from this study suggest specific exosomal miRs are of prognostic value in mCRPC and should be validated in larger cohorts.

Effect of hyperglycemia on human monocyte activation

Our recent study defined the chemokine-induced human monocyte signaling under normoglycemic condition. To explore the hyperglycemia-induced monocyte signaling, we performed adhesion, migration, and transmigration assays on human monocytes obtained from THP-1 cell line in the presence of normal (5 mM) and high (10 and 20 mM) glucose concentrations without chemokines. We observed augmented (P < 0.01) monocyte adhesion to human umbilical vein endothelial cell monolayer at 10 than 5 mM glucose with no further increase at 20-mM glucose concentration (P < 0.07 vs 10 mM; P < 0.01 vs 5 mM). But incremental increases in monocyte migration (P < 0.01), transmigration (P < 0.01), and stress fiber response (P < 0.01) were observed at 10- and 20-mM glucose concentrations in comparison to 5-mM glucose concentrations. We found gradational increase (P < 0.01) in phosphorylation of Akt(S473) and glycogen synthase kinase (GSK3β(S9)) in hyperglycemia (10 and 20 mM) when compared with 5 mM glucose. Furthermore, hyperglycemia (both 10 and 20 mM)-treated monocyte showed up-regulated phosphorylation of p101 and p110γ subunits of PI-3 kinase in comparison to 5 mM glucose. Hyperglycemia-induced monocyte migration was restored to basal levels in the presence of PI-3 kinase inhibitor, LY. These observations imply that modest hyperglycemia per se, as is commonly observed in diabetic individuals, is a potent stimulator of monocyte activity even without chemokines.

Both vascular endothelial growth factor and soluble Flt-1 are increased in type 2 diabetes but not in impaired fasting glucose

OBJECTIVE

Inadequate vascular remodeling is contributory to increased cardiovascular events in people with type 2 diabetes mellitus (DM) and impaired fasting glucose (IFG). Vascular endothelial growth factor (VEGF) and its regulatory molecule soluble Flt-1(sFlt-1) play important roles in atherogenesis.

RESEARCH DESIGN

We measured fasting plasma concentrations of VEGF and sFlt-1 in 11 nondiabetic (ND) (aged 46.1 +/- 2.1 years; body mass index [BMI], 26.1 +/- 0.9 kg/m; glucose, 5.0 +/- 0.1 mM), 15 IFG (aged 52.9 +/- 1.8 years; BMI, 32.7 +/- 1.3 kg/m; glucose, 6.4 +/- 0.1 mM), and 8 DM (aged 55.8 +/- 3.2 years; BMI, 30.0 +/- 1.0 kg/m; glucose, 9.3 +/- 0.5 mM) subjects.

RESULTS

Plasma VEGF (42.1 +/- 4.0 vs 24.2 +/- 0.9 vs 29.4 +/- 3.8 pg/mL, respectively) and sFlt-1 (119.4 +/- 4.9 vs 58.9 +/- 3.2 vs 56.7 +/- 1.2 pg/mL, respectively) concentrations were higher (P < 0.04) in DM than IFG and ND subjects. Whereas VEGF concentrations were significantly lower (P < 0.05) in IFG than in ND subjects, sFlt-1 concentrations did not differ between the IFG and ND subjects.

CONCLUSIONS

Although plasma VEGF concentrations were higher (35%) in DM than in ND subjects, VEGF action on vascular remodeling was likely attenuated by higher sFlt-1 concentrations in DM. In contrast, IFG subjects did not have major perturbations in either VEGF or sFlt-1 levels. Further studies defining the roles of these mediators in DM and IFG are necessary to extend these observations.

Effect of hyperglycemia on human monocyte activation

Our recent study defined the chemokine-induced human monocyte signaling under normoglycemic condition. To explore the hyperglycemia-induced monocyte signaling, we performed adhesion, migration, and transmigration assays on human monocytes obtained from THP-1 cell line in the presence of normal (5 mM) and high (10 and 20 mM) glucose concentrations without chemokines. We observed augmented (P < 0.01) monocyte adhesion to human umbilical vein endothelial cell monolayer at 10 than 5 mM glucose with no further increase at 20-mM glucose concentration (P < 0.07 vs 10 mM; P < 0.01 vs 5 mM). But incremental increases in monocyte migration (P < 0.01), transmigration (P < 0.01), and stress fiber response (P < 0.01) were observed at 10- and 20-mM glucose concentrations in comparison to 5-mM glucose concentrations. We found gradational increase (P < 0.01) in phosphorylation of Akt(S473) and glycogen synthase kinase (GSK3β(S9)) in hyperglycemia (10 and 20 mM) when compared with 5 mM glucose. Furthermore, hyperglycemia (both 10 and 20 mM)-treated monocyte showed up-regulated phosphorylation of p101 and p110γ subunits of PI-3 kinase in comparison to 5 mM glucose. Hyperglycemia-induced monocyte migration was restored to basal levels in the presence of PI-3 kinase inhibitor, LY. These observations imply that modest hyperglycemia per se, as is commonly observed in diabetic individuals, is a potent stimulator of monocyte activity even without chemokines.

RGS-GAIP-interacting protein controls breast cancer progression

Although the importance of RGS-GAIP-interacting protein (GIPC) in the biology of malignant cells is well known, the molecular mechanism of GIPC in the inhibition of tumor progression has not been identified. This study focused on elucidating the molecular role of GIPC in breast cancer progression. By using a human breast tumor specimen, an in vivo mouse model, and breast cancer cell lines, we showed for the first time that GIPC is involved in breast cancer progression through regulation of breast cancer cell proliferation, survival, and invasion. Furthermore, we found that the Akt/Mdm2/p53 axis, insulin-like growth factor-1 receptor, matrix metalloproteinase-9, and Cdc42 were downstream of GIPC signaling in breast cancer cells. Moreover, we showed that wild-type p53 reduced GIPC-induced breast cancer cell survival, whereas mutant p53 inhibited GIPC-induced cell invasion. Finally, we demonstrated that an N-myristoylated GIPC peptide (CR1023, N-myristoyl-PSQSSSEA) capable of blocking the PDZ domain of GIPC successfully inhibited MDA-MB-231 cell proliferation, survival, and further in vivo tumor growth. Taken together, these findings demonstrate the importance of GIPC in breast tumor progression, which has a potentially significant impact on the development of therapies against many common cancers expressing GIPC, including breast and renal cancer.

Role of AKT-glycogen synthase kinase axis in monocyte activation in human beings with and without type 2 diabetes

Monocyte activation by chemokines is a vital trigger for initiation of atherosclerotic process. Circulating levels of platelet activating factor (PAF), a recognized chemokine, is known to be increased in type 2 diabetes that is linked to accelerated atherosclerosis. To explore the molecular basis we examined the signalling pathways involved in PAF induced monocyte activation. PAF increased migration in monocytes obtained from THP-1 cells, nondiabetic and diabetic subjects. This effect was blocked by AKT inhibition. It did so by phosphorylation of glycogen synthase kinase (GSK)-3βS⁹, which was completely blocked by AKT inhibition. Additionally, PAF induced GSK-3β phosphorylation was linked to Rac-1 activation and Rho-A inactivation leading to migration. Paradoxically, inhibition of GSK-3β phosphorylation also augmented monocyte migration in THP-1, ND and diabetic monocytes through phosphorylation of AKT and activation of Rho-A that was independent of GSK. This was validated when (i) overexpression of dominant negative mutants of Rho-A reversed GSK inhibitor induced monocyte migration and (ii) AKT inhibition blocked GSK inhibitor induced Rho-A activity. Constitutively active ARAP3 (Rho-GAP) appears to have a regulatory role in monocyte activity during GSK inhibition. Finally, inhibition of monocyte GSK-3β activity (by inhibitors and genetic manipulation) led to enhanced migration in diabetes compared to persons without diabetes. We conclude that diabetic monocytes show increased migratory capacity in response to GSK-3β inhibition. GSK inhibitors developed to treat the metabolic complications of diabetes should therefore be used with caution.

Neuropilin-1 upholds dedifferentiation and propagation phenotypes of renal cell carcinoma cells by activating Akt and sonic hedgehog axes

Expression of neuropilin-1 (NRP-1) has been shown in many cancer cells, but its molecular effect on tumorigenesis is largely unknown. In this report, we show that in aggressive types of renal cell carcinoma (RCC), NRP-1 is expressed at a high level. We show that after knockdown of NRP-1 by short hairpin RNA, RCC cells express significantly lower levels of MDM-2 and p63 proteins but higher levels of p53, and exhibit reduced migration and invasion. When implanted in mice, RCC cells with a reduced NRP-1 level have a statistically significant smaller tumor-forming ability than control cells. Also, NRP-1 knockdown RCC cells exhibit a more differentiated phenotype, as evidenced by the expression of epithelial-specific and kidney-specific cadherins, and the inhibition of sonic hedgehog expression participated in this effect. Inhibition of sonic hedgehog expression can be reversed by DeltaNp63alpha overexpression. Our study reveals that NRP-1 helps maintain an undifferentiated phenotype in cancer cells.

Lack of an effect of pioglitazone or glipizide on lipoprotein-associated phospholipase A2 in type 2 diabetes

OBJECTIVE

To study the effects of pioglitazone, a peroxisome proliferator-activated receptor-y agonist with vascular beneficial effects, and glipizide, an insulin secretagogue, on novel inflammatory vascular risk markers in subjects with and without type 2 diabetes.

METHODS

We studied 11 subjects without diabetes and 19 matched subjects with diabetes. The subjects with diabetes were randomly assigned to receive either 45 mg daily of pioglitazone (N = 8) or 10 mg daily of glipizide (N = 11) (median dose) for 12 weeks. Lipoprotein-associated phospholipase A2 (LpPLA2), vascular cell adhesion molecule (VCAM-1), intracellular adhesion molecule (ICAM-1), and e-selectin were measured by established techniques before and after therapy with either agent. The subjects without diabetes were studied only once.

RESULTS

The study subjects with diabetes had higher (P<0.05) LpPLA2, e-selectin, and VCAM-1 levels than did those without diabetes. ICAM-1 levels tended to be higher (P = 0.07) in the study subjects with than in those without diabetes. Neither pioglitazone nor glipizide therapy significantly altered LpPLA2 or VCAM-1 concentrations. While pioglitazone therapy reduced (P<0.05) eselectin concentrations, glipizide therapy reduced (P<0.03) ICAM-1 concentrations.

CONCLUSION

Type 2 diabetes is associated with elevated concentrations of the novel vascular risk marker LpPLA2 and inflammatory risk markers e-selectin and VCAM-1. Neither pioglitazone nor glipizide significantly altered LpPLA2, VCAM-1, or highly sensitive C-reactive protein levels after 12 weeks of therapy. In study subjects with type 2 diabetes, e-selectin concentrations declined significantly with pioglitazone therapy, whereas ICAM-1 concentrations decreased significantly with glipizide therapy.

Neural models for auditory localization based on spectral cues

In this paper we analyze several auditory localization neural models that are based on head related transfer functions (HRTFs). HRTFs represent the combined directional-spectral response of the pinnae head and torso. The role of HRTFs in such modeling has hitherto been underestimated despite substantial experimental evidence to its relevance in spatial hearing, especially in determining direction of high-frequency sound sources. In the first section we suggest a neural model that links the physiology of binaural processing to a neural network that extracts spectral ratios. These ratios correspond to HRTFs ratios and can provide auditory directional cues. Next, we compare several methods of matching HRTFs ratios using discriminative matching measure (DMM). We consider several solutions to the matching problem from a neural signal processing viewpoint. We compare correlation based approaches with DMM optimization approach and with a non-linear approach based on neural back-propagation algorithm. All three models can be implemented by neural networks. Finally, we include experimental results of simulations that are conducted using these methods. Experiments show that the back-propagation based neural network yields the best results in terms of DMM both for narrow-band and broad band excitation. The back-propagation neural network is also superior in matching noisy HRTF ratio vectors.

Shape from recognition: a novel approach for 3-D face shape recovery

In this paper, we develop a novel framework for robust recovery of three-dimensional (3-D) surfaces of faces from single images. The underlying principle is shape from recognition, i.e., the idea that pre-recognizing face parts can constrain the space of possible solutions to the image irradiance equation, thus allowing robust recovery of the 3-D structure of a specific part. Parts of faces like nose, lips and eyes are recognized and localized using robust expansion matching filter templates under varying pose and illumination. Specialized backpropagation based neural networks are then employed to recover the 3-D shape of particular face parts. Representation using principal components allows to efficiently encode classes of objects such as nose, lips, etc. The specialized networks are designed and trained to map the principal component coefficients of the part images to another set of principal component coefficients that represent the corresponding 3-D surface shapes. To achieve robustness to viewing conditions, the network is trained with a wide range of illumination and viewing directions. A method for merging recovered 3-D surface regions by minimizing the sum squared error in overlapping areas is also derived. Quantitative analysis of the reconstruction of the surface parts in varying illumination and pose show relatively small errors, indicating that the method is robust and accurate. Several examples showing recovery of the complete face also illustrate the efficacy of the approach.

Generalized feature extraction using expansion matching

A novel generalized feature extraction method based on the expansion matching (EXM) method and on the Karhunen-Loeve transform (KLT) is presented. The method provides an efficient way to locate complex features of interest like corners and junctions with reduced number of filtering operations. The EXM method is used to design optimal detectors for a set of model elementary features. The KL representation of these model EXM detectors is used to filter the image and detect candidate interest points from the energy peaks of the eigen coefficients. The KL coefficients at these candidate points are then used to efficiently reconstruct the response and differentiate real junctions and corners from arbitrary features in the image. The method is robust to additive noise and is able to successfully extract, classify, and find the myriad compositions of corner and junction features formed by combinations of two or more edges or lines. This method differs from previous works in several aspects. First, it treats the features not as distinct entities, but as combinations of elementary features. Second, it employs an optimal set of elementary feature detectors based on the EM approach. Third, the method incorporates a significant reduction in computational complexity by representing a large set of EXM filters by a relatively small number of eigen filters derived by the KL transform of the basic EXM filter set. This is a novel application of the KL transform, which is usually employed to represent signals and not impulse responses as in our present work.

An auditory localization model based on high-frequency spectral cues

We present in this paper a connectionist model that extracts interaural intensity differences (IID) from head-related transfer functions (HRTF) in the form of spectral cues to localize broadband high-frequency auditory stimuli, in both azimuth and elevation. A novel discriminative matching measure (DMM) is defined and optimized to characterize matching this IID spectrum. The optimal DMM approach and a novel back-propagation-based fuzzy model of localization are shown to be capable of localizing sources in azimuth, using only spectral IID cues. The fuzzy neural network model is extended to include localization in elevation. The use of training data with additive noise provides robustness to input errors. Outputs are modeled as two-dimensional Gaussians that act as membership functions for the fuzzy sets of sound locations. Error back-propagation is used to train the network to correlate input patterns and the desired output patterns. The fuzzy outputs are used to estimate the location of the source by detecting Gaussians using the max-energy paradigm. The proposed model shows that HRTF-based spectral IID patterns can provide sufficient information for extracting localization cues using a connectionist paradigm. Successful recognition in the presence of additive noise in the inputs indicates that the computational framework of this model is robust to errors made in estimating the IID patterns. The localization errors for such noisy patterns at various elevations and azimuths are compared and found to be within limits of localization blurs observed in humans.