Classification of breast cancer precursors through exhaled breath

Shuster, Gregory; Gallimidi, Zahava; Reiss, Asnat Heyman; Dovgolevsky, Ekaterina; Billan, Salem; Abdah-Bortnyak, Roxolyana; Kuten, Abraham; Engel, Ahuva; Shiban, Ala; Tisch, Ulrike; Haick, Hossam

doi:10.1007/s10549-010-1317-x

Cited by 88 publications

(72 citation statements)

References 21 publications

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“…However, the downsides to these methods are that they are time consuming and require large size, expensive instrumentation and an expert operator. Moreover, to improve the detection in some of these devices, capturing and preconcentrating the breath sample is a prerequisite step [43,44]. …”

Section: Array-based Cancer Diagnosticsmentioning

confidence: 99%

“…Using the advantages of NPs, a nanoscale artificial nose has been designed by Haick and co-workers [44]. This simple, cost effective and portable sensor is able to detect cancer by analyzing the VOCs using pattern recognition methods.…”

Section: Array-based Cancer Diagnosticsmentioning

confidence: 99%

“…This simple, cost effective and portable sensor is able to detect cancer by analyzing the VOCs using pattern recognition methods. The nanoscale artificial nose is capable of identifying different odors even at very low concentrations and subtle differences [44]. The gas sensor is based on an array of highly cross-reactive chemiresistors made of AuNPs with different organic capping layers [11].…”

Section: Array-based Cancer Diagnosticsmentioning

confidence: 99%

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Array-Based Sensing Using Nanoparticles: An Alternative Approach for Cancer Diagnostics

Yazdani

Rotello

2014

Nanomedicine

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Array-based sensing using nanoparticles (NPs) provides an attractive alternative to specific biomarker-focused strategies for cancer diagnosis. The physical and chemical properties of NPs provide both the recognition and transduction capabilities required for biosensing. Array-based sensors utilize a combined response from the interactions between sensors and analytes to generate a distinct pattern (fingerprint) for each analyte. These interactions can be the result of either the combination of multiple specific biomarker recognition (specific binding) or multiple selective binding responses, known as chemical nose sensing. The versatility of the latter array-based sensing using NPs can facilitate the development of new personalized diagnostic methodologies in cancer diagnostics, a necessary evolution in the current healthcare system to better provide personalized treatments. This review will describe the basic principle of array-based sensors, along with providing examples of both invasive and noninvasive samples used in cancer diagnosis.

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Section: Array-based Cancer Diagnosticsmentioning

confidence: 99%

Section: Array-based Cancer Diagnosticsmentioning

confidence: 99%

Section: Array-based Cancer Diagnosticsmentioning

confidence: 99%

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Array-Based Sensing Using Nanoparticles: An Alternative Approach for Cancer Diagnostics

Yazdani

Rotello

2014

Nanomedicine

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“…However, the accuracy of imagining techniques is not optimal, and their ability to distinguish between benign breast diseases and invasive breast cancer lacks accuracy [60]. With this in mind, Shuster et al examined the ability of six spherical GNPs (core size of 3-6 nm) with different capping ligands and benzyl mercaptan-capped cubic platinum nanoparticle for identifying and distinguishing between benign breast conditions, cancer lesions and healthy states [61]. Pattern recognition analysis of the output signal demonstrated that two out of the seven sensors (spherical octadecylamine-capped GNPs and cubic benzyl mercaptan-capped platinum nano particles) could appropriately categorize healthy women, benign conditions and cancer lesions, with an overall accuracy of 86% [61].…”

Section: Breast Cancermentioning

confidence: 99%

Monolayer-Capped Gold Nanoparticles for Disease Detection From Breath

Nakhleh

Broza

Haick

2014

Nanomedicine (Lond.)

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The recognition of volatile organic compounds in breath samples is a promising approach for noninvasive safe diagnosis of disease. Spectrometry and spectroscopy methods used for breath analysis suffer from suboptimal accuracy, are expensive and are unsuitable for diagnostics. This article presents a concise review on arrays of monolayer-capped gold nanoparticle (GNP) sensors in conjugation with pattern recognition methods for cost-effective, fast and high-throughput point-of-care diagnostic results from exhaled breath samples. The article starts with a general introduction to the rationale and advantages of breath analysis as well as with a presentation of the utility of monolayer-capped GNP sensors in this field. The article continues with a presentation of the main fabrication and operation principles of these GNP sensors and concludes with selected examples regarding their utility in different fields of medicine, particularly in neurology, infectiology, respiratory medicine and oncology.

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“…[11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] This approach is based on the emission of VOCs from the cell membranes that primarily consist of amphipathic phospholipids, carbohydrates, and many integral membrane proteins. The cell membranes of different cell types are distinct.…”

Section: Introductionmentioning

confidence: 99%

The scent fingerprint of hepatocarcinoma: in-vitro metastasis prediction with volatile organic compounds (VOCs)

Amal¹,

Ding²,

Liu³

et al. 2012

IJN

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Background: Hepatocellular carcinoma (HCC) is a common and aggressive form of cancer. Due to a high rate of postoperative recurrence, the prognosis for HCC is poor. Subclinical metastasis is the major cause of tumor recurrence and patient mortality. Currently, there is no reliable prognostic method of invasion. Aim: To investigate the feasibility of fingerprints of volatile organic compounds (VOCs) for the in-vitro prediction of metastasis. Methods: Headspace gases were collected from 36 cell cultures (HCC with high and low metastatic potential and normal cells) and analyzed using nanomaterial-based sensors. Predictive models were built by employing discriminant factor analysis pattern recognition, and the classification success was determined using leave-one-out cross-validation. The chemical composition of each headspace sample was studied using gas chromatography coupled with mass spectrometry (GC-MS). Results: Excellent discrimination was achieved using the nanomaterial-based sensors between (i) all HCC and normal controls; (ii) low metastatic HCC and normal controls; (iii) high metastatic HCC and normal controls; and (iv) high and low HCC. Several HCC-related VOCs that could be associated with biochemical cellular processes were identified through GC-MS analysis. Conclusion:The presented results constitute a proof-of-concept for the in-vitro prediction of the metastatic potential of HCC from VOC fingerprints using nanotechnology. Further studies on a larger number of more diverse cell cultures are needed to evaluate the robustness of the VOC patterns. These findings could benefit the development of a fast and potentially inexpensive laboratory test for subclinical HCC metastasis.

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Classification of breast cancer precursors through exhaled breath

Cited by 88 publications

References 21 publications

Array-Based Sensing Using Nanoparticles: An Alternative Approach for Cancer Diagnostics

Array-Based Sensing Using Nanoparticles: An Alternative Approach for Cancer Diagnostics

Monolayer-Capped Gold Nanoparticles for Disease Detection From Breath

The scent fingerprint of hepatocarcinoma: in-vitro metastasis prediction with volatile organic compounds (VOCs)

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