Orna Barash

Volatile Organic Compounds of Lung Cancer and Possible Biochemical Pathways

Biochemical Pathways Meggie Hakim,† Yoav Y. Broza,† Orna Barash,† Nir Peled,‡ Michael Phillips, Anton Amann, and Hossam Haick*,† †The Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, TechnionIsrael Institute of Technology, Haifa 32000, Israel ‡The Thoracic Cancer Research and Detection Center, Sheba Medical Center, Tel-Aviv University, Tel-Aviv 52621, Israel Menssana Research, Inc., Fort Lee, New Jersey 07024, United States Breath Research Institute, Austrian Academy of Sciences, 6850 Dornbirn, Austria University-Clinic for Anesthesia, Innsbruck Medical University, 6020 Innsbruck, Austria

Sniffing the Unique “Odor Print” of Non‐Small‐Cell Lung Cancer with Gold Nanoparticles

A highly sensitive and fast-response array of sensors based on gold nanoparticles, in combination with pattern recognition methods, can distinguish between the odor prints of non-small-cell lung cancer and negative controls with 100% accuracy, with no need for preconcentration techniques. Additionally, preliminary results indicate that the same array of sensors might serve as a better tool for understanding the biochemical source of volatile organic compounds that might occur in cancer cells and appear in the exhaled breath, as compared to traditional spectrometry techniques. The reported results provide a launching pad to initiate a bedside tool that might be able to screen for early stages of lung cancer and allow higher cure rates. In addition, such a tool might be used for the immediate diagnosis of fresh (frozen) tissues of lung cancer in operating rooms, where a dichotomic diagnosis is crucial to guide surgeons.

Classification of lung cancer histology by gold nanoparticle sensors

UNLABELLED We propose a nanomedical device for the classification of lung cancer (LC) histology. The device profiles volatile organic compounds (VOCs) in the headspace of (subtypes of) LC cells, using gold nanoparticle (GNP) sensors that are suitable for detecting LC-specific patterns of VOC profiles, as determined by gas chromatography-mass spectrometry analysis. Analyzing the GNP sensing signals by support vector machine allowed significant discrimination between (i) LC and healthy cells; (ii) small cell LC and non-small cell LC; and between (iii) two subtypes of non-small cell LC: adenocarcinoma and squamous cell carcinoma. The discriminative power of the GNP sensors was then linked with the chemical nature and composition of the headspace VOCs of each LC state. These proof-of-concept findings could totally revolutionize LC screening and diagnosis, and might eventually allow early and differential diagnosis of LC subtypes with detectable or unreachable lung nodules. FROM THE CLINICAL EDITOR In this study, a nanomedical device that profiles volatile organic compounds (VOCs) in lung cancer cells is investigated, using a matrix of gold nanoparticle (GNP) sensors that are suitable for detecting lung cancer (LC) specific patterns of VOC profiles. This device might eventually allow early differential diagnosis of LC subtypes including unreachable lung nodules.

Volatile fingerprints of cancer specific genetic mutations

UNLABELLED We report on a new concept for profiling genetic mutations of (lung) cancer cells, based on the detection of patterns of volatile organic compounds (VOCs) emitted from cell membranes, using an array of nanomaterial-based sensors. In this in-vitro pilot study we have derived a volatile fingerprint assay for representative genetic mutations in cancer cells that are known to be associated with targeted cancer therapy. Five VOCs were associated with the studied oncogenes, using complementary chemical analysis, and were discussed in terms of possible metabolic pathways. The reported approach could lead to the development of novel methods for guiding treatments, so that patients could benefit from safer, more timely and effective interventions that improve survival and quality of life while avoiding unnecessary invasive procedures. Studying clinical samples (tissue/blood/breath) will be required as next step in order to determine whether this cell-line study can be translated into a clinically useful tool. FROM THE CLINICAL EDITOR In this novel study, a new concept for profiling genetic mutations of (lung) cancer cells is described, based on the detection of patterns of volatile organic compounds emitted from cell membranes, using an array of nano-gold based sensors.

Unique volatolomic signatures of TP53 and KRAS in lung cells

Background:Volatile organic compounds (VOCs) are potential biomarkers for cancer detection in breath, but it is unclear if they reflect specific mutations. To test this, we have compared human bronchial epithelial cell (HBEC) cell lines carrying the KRASV12 mutation, knockdown of TP53 or both with parental HBEC cells.Methods:VOC from headspace above cultured cells were collected by passive sampling and analysed by thermal desorption gas chromatography mass spectrometry (TD-GC–MS) or sensor array with discriminant factor analysis (DFA).Results:In TD-GC–MS analysis, individual compounds had limited ability to discriminate between cell lines, but by applying DFA analysis combinations of 20 VOCs successfully discriminated between all cell types (accuracies 80–100%, with leave-one-out cross validation). Sensor array detection DFA demonstrated the ability to discriminate samples based on their cell type for all comparisons with accuracies varying between 77% and 93%.Conclusions:Our results demonstrate that minimal genetic changes in bronchial airway cells lead to detectable differences in levels of specific VOCs identified by TD-GC–MS or of patterns of VOCs identified by sensor array output. From the clinical aspect, these results suggest the possibility of breath analysis for detection of minimal genetic changes for earlier diagnosis or for genetic typing of lung cancers.

Differentiation between genetic mutations of breast cancer by breath volatolomics

Mapping molecular sub-types in breast cancer (BC) tumours is a rapidly evolving area due to growing interest in, for example, targeted therapy and screening high-risk populations for early diagnosis. We report a new concept for profiling BC molecular sub-types based on volatile organic compounds (VOCs). For this purpose, breath samples were collected from 276 female volunteers, including healthy, benign conditions, ductal carcinoma in situ (DCIS) and malignant lesions. Breath samples were analysed by gas chromatography mass spectrometry (GC-MS) and artificially intelligent nanoarray technology. Applying the non-parametric Wilcoxon/Kruskal-Wallis test, GC-MS analysis found 23 compounds that were significantly different (p < 0.05) in breath samples of BC patients with different molecular sub-types. Discriminant function analysis (DFA) of the nanoarray identified unique volatolomic signatures between cancer and non-cancer cases (83% accuracy in blind testing), and for the different molecular sub-types with accuracies ranging from 82 to 87%, sensitivities of 81 to 88% and specificities of 76 to 96% in leave-one-out cross-validation. These results demonstrate the presence of detectable breath VOC patterns for accurately profiling molecular sub-types in BC, either through specific compound identification by GC-MS or by volatolomic signatures obtained through statistical analysis of the artificially intelligent nanoarray responses.

Exhaled Volatile Organic Compounds as Noninvasive Markers in Breast Cancer

Volatile organic compounds (VOCs) in exhaled breath are interesting candidates as breast cancer (BC) markers for malignancy, staging, histology, genotype, and distinction from other malignant and benign diseases. VOC BC markers can be derived either as BC-specific compounds by analytical chemistry or as collective breath prints by statistical treatment of the output of sensor arrays. Despite the great potential of applications in clinical diagnostics, only few studies for breath VOC BC markers have been done, and breath testing for BC has not yet left the realm of research and entered clinical practice, mainly due to lack of standardization of the experimental techniques. In this chapter, we will outline the vast potential of exhaled VOC as a novel class of molecular BC markers and describe the challenges on the way from bench to bedside. In this chapter, we provide a didactic approach to the state-of-the-art experimental techniques for breath collection, sample storage, analysis of the breath VOCs, and direct breath printing, and we present examples for applications of diagnosing BC by VOC profiling.

7.1.1 Invited: Chemical Nanoarrays for Early Detection and Screening of Lung Cancer via Volatile Biomarkers

Lung cancer is the leading cause of cancer-related deaths worldwide. The cancer’s stage, histology and genetic mutations determine a patient’s prognosis and treatment. Here we present an artificial electronic nose (NA-NOSE), which makes use of cross-reactive chemical sensor nanoarrays, for the detection of volatile biomarkers in breath samples as well as in the headspace of in-vitro cell lines of lung cancer. A series of proof-of-concept studies with the NA-NOSE have shown an excellent ability to distinguish between lung cancer and healthy states, between different histologies of link cancer, and between lung cancer genetic mutations that can benefit from targeted treatments. The proposed biomarker-based testing NA-NOSE technology holds future potential as a cost-effective, fast and reliable diagnostic test for early disease detection and monitoring of the disease progression. The NANOSE would be suitable for use outside of specialist settings and could significantly reduce in the burden on the health budget.