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

Haitham Amal, Lu Ding, Bin-bin Liu, Ulrike Tisch, Zhen-qin Xu, Da-you Shi, Yan Zhao, Jie Chen, Rui-xia Sun, Hu Liu, Sheng-Long Ye, Zhao-you Tang, Hossam Haick, Haitham Amal, Lu Ding, Bin-bin Liu, Ulrike Tisch, Zhen-qin Xu, Da-you Shi, Yan Zhao, Jie Chen, Rui-xia Sun, Hu Liu, Sheng-Long Ye, Zhao-you Tang, Hossam Haick

Abstract

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.

Keywords: GC-MS; hepatocarcinoma; metastasis; sensor; volatile organic compound.

Figures

Figure 1
Figure 1
The DFA models that discriminated between (A) HCC cells (including cells with high and low metastatic potential) and normal control cells; (B) HCC-LMP cells and normal control cells; (C) HCC-HMP cells and normal control cells; and (D) HCC-LMP and HCC-HMP cells. Every point represents one cell culture. Note: The sensors used for the four DFA models are listed in Table 1. Abbreviations: DFA, discriminant factor analysis; HCC, hepatocellular carcinoma; HCC-LMP, hepatocellular carcinoma cells with low metastatic potential; HCC-HMP, hepatocellular carcinoma cells with high metastatic potential.

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