Acinetobacter, Aeromonas and Trichococcus populations dominate the microbial community within urban sewer infrastructure

We evaluated the population structure and temporal dynamics of the dominant community members within sewage influent from two wastewater treatment plants (WWTPs) in Milwaukee, WI. We generated > 1.1 M bacterial pyrotag sequences from the V6 hypervariable region of 16S rRNA genes from 38 influent samples and two samples taken upstream in the sanitary sewer system. Only a small fraction of pyrotags from influent samples (∼ 15%) matched sequences from human faecal samples. The faecal components of the sewage samples included enriched pyrotag populations from Lactococcus and Enterobacteriaceae relative to their fractional representation in human faecal samples. In contrast to the large number of distinct pyrotags that represent faecal bacteria such as Lachnospiraceae and Bacteroides, only one or two unique V6 sequences represented Acinetobacter, Aeromonas and Trichococcus, which collectively account for nearly 35% of the total sewage community. Two dominant Acinetobacter V6 pyrotags (designated Acineto tag 1 and Acineto tag 2) fluctuated inversely with a seasonal pattern over a 3-year period, suggesting two distinct Acinetobacter populations respond differently to ecological forcings in the system. A single nucleotide change in the V6 pyrotags accounted for the difference in these populations and corresponded to two phylogenetically distinct clades based on full-length sequences. Analysis of wavelet functions, derived from a mathematical model of temporal fluctuations, demonstrated that other abundant sewer associated populations including Trichococcus and Aeromonas had temporal patterns similar to either Acineto tag 1 or Acineto tag 2. Populations with related temporal fluctuations were found to significantly correlate with the same WWTP variables (5-day BOD, flow, ammonia, total phosphorous and suspended solids). These findings illustrate that small differences in V6 sequences can represent phylogenetically and ecologically distinct taxa. This work provides insight into microbial community composition and dynamics within the defined environment of urban sewer infrastructure.

A noninvasive multimodal sono-contrast NIR spectroscopy system for breast cancer diagnosis: Clinical trial

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Background: A noninvasive multimodal sono-constrast spectroscopy system was developed to detect breast cancer from benign mass. An IRB approved clinical study has been carried out to evaluate its diagnostic power. Fourteen patients with histologically-proven cancer and 26 with benign mass were enrolled with informed consent.

Methods: This system combines three modules: diffuse reflectance spectroscopy, ultrasonography and low intensity focused ultrasound (LIFU). It reports the optical functional difference in cancer and benign mass after transient LIFU interaction with vascular flow. The optical intensity and LIFU signals were collected during each study. The ratio of optical intensities at wavelengths 685 nm and 830 nm was decomposed into low frequency and high frequency components using wavelet analysis.

Results: Comparison of the high frequency component showed that LIFU stimulated transitory fluctuation in benign mass, but not in malignant tissue, as quantified by mean absolute deviation (MAD). The ratios of MAD during LIFU vs. baseline in cancer and benign mass are [mean (max/min/std)] 2.04 (3.27/1.41/0.43) and 3.00 (4.29/1.86/0.62). This suggests that high frequency fluctuation was amplified in benign mass during LIFU stimulation. There are a few outliers due to poor patient setup or patient movement during procedure. The MAD ratios are significantly different in cancer vs. benign mass (p<<0.01). An ROC curve was generated by varying threshold MAD values. The area under ROC curve (AUC) was calculated to be 0.91. With threshold 2.3, sensitivity of 92.8% and specificity of 80.8% can be achieved. Backward stepwise regression study reveals that system performance is not affected by patient age (hormone status), tumor depth and tumor size.

Conclusions: Current results demonstrate the effectiveness of the multimodal system in characterizing breast cancer vs. benign mass. LIFU appears to exert more pronounced influence on blood flow in benign mass than in tumor. This lack of response to LIFU in breast cancer is possibly due to its abnormal blood vasculature. The analysis is ongoing to incorporate ultrasound imaging parameters with spectroscopy to further improve the diagnostic power.

A real-time prostate cancer detection technique using needle insertion force and patient-specific criteria during percutaneous intervention

In this article, the authors present a novel real-time cancer detection technique by using needle insertion forces in conjunction with patient-specific criteria during percutaneous interventions. Needle insertion experiments and pathological analysis were performed for developing a computer-aided detection (CAD) model. Backward stepwise regression method was performed to identify the statistically significant patient-specific factors. A baseline force model was then developed using these significant factors. The threshold force model that estimated the lower bound of the cancerous tissue forces was formulated by adding an adjustable classifier to the baseline force model. Tradeoff between sensitivity and specificity was obtained by varying the threshold value of the classifier, from which the receiver-operating characteristic (ROC) curve was generated. Sequential quadratic programming was used to optimize the CAD model by maximizing the area under the ROC curve (AUC) using a set of model-training patient data. When the CAD model was evaluated using an independent set of model-validation patient data, an AUC of 0.90 was achieved. The feasibility of cancer detection in real time during percutaneous interventions was established.

A real-time prostate cancer detection technique using needle insertion force and patient-specific criteria during percutaneous intervention

In this article, the authors present a novel real-time cancer detection technique by using needle insertion forces in conjunction with patient-specific criteria during percutaneous interventions. Needle insertion experiments and pathological analysis were performed for developing a computer-aided detection (CAD) model. Backward stepwise regression method was performed to identify the statistically significant patient-specific factors. A baseline force model was then developed using these significant factors. The threshold force model that estimated the lower bound of the cancerous tissue forces was formulated by adding an adjustable classifier to the baseline force model. Trade-off between sensitivity and specificity was obtained by varying the threshold value of the classifier, from which the receiver-operating characteristic (ROC) curve was generated. Sequential quadratic programming was used to optimize the CAD model by maximizing the area under the ROC curve (AUC) using a set of model-training patient data. When the CAD model was evaluated using an independent set of model-validation patient data, an AUC of 0.90 was achieved. The feasibility of cancer detection in real time during percutaneous interventions was established.

Targeting of breast cancer with non-oncology drugs – possible novel therapeutic option for triple-negative breast cancer

Abstract #2119

Introduction: Triple-negative breast cancer (TNBC) is defined by lack of ER, and PR expression and normal HER2 expression. It is characterized by aggressive biological presentation and unfavorable outcome. It is associated with frequent lack of response to current chemotherapy agents. Recently, 392 drugged genes that serve as targets for 1557 both oncologic and non-oncologic drugs were identified from the pharmacologic database DrugBank (Lauss et al. Pharmacogenomics 2007). In this study, we compared expression levels of these known drug targets between TNBC and receptor-positive cancers. Methods: Gene expression profiles were obtained from fine needle biopsies of newly diagnosed early stage breast cancer before any therapy (n=133, MDACC dataset). Differential expression of these genes was validated in a second independent data set (n=286, Rotterdam dataset) and in a panel of cell lines (n=19). In order to assess the functional relevance of known drug targets overexpressed in TNBC we performed in vitro experiments. Cell lines were treated with various concentrations of selected drugs alone or in combination with paclitaxel. Results: We mapped 675 U133A probe sets representing 347 unique drug targets to the Affymetrix U133A Genechip. 44 drug targets were overexpressed in TNBC compared to non-TNBC in the MDACC dataset. Thirty-three of these (75%) were also overexpressed among TNBC compared to non-TNBC in the Rotterdam dataset. Glutathione-S-transferase pi (GSTpi, target of clomipramine) was the most highly and consistently overexpressed target in human TNBC and in estrogen- and HER2-receptor-negative breast cancer cell lines. The GSTpi overexpressing (and triple negative) human mammary cell line HBL-100 showed dose-dependent inhibition of growth after 144 hrs of incubation with clomipramine, whereas growth of the GSTpi-low expressing (non-triple negative) breast cancer cell lines MCF-7 and SKBR3 was not inhibited by this drug. Treatment with clomipramine did not alter sensitivity to paclitaxel in either cell line in vitro. Conclusion: Gene expression analysis indicates that targets for several known drugs are over expressed in TNBC relative to other types of breast cancers. We hypothesize that some of these drugs may influence the behavior of TNBC and may represent future therapeutic options. Further experiments are needed to fully explore the functional implications of these findings; however, our preliminary results suggest that inhibition of GSTpi with clomipramine leads to inhibition of cell growth of TNBC cell lines in vitro.

Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2119.