Abstract 5678
Background
Hepatocellular carcinoma (HCC) has relatively sensitive and specific serum tumor antigen markers (AFP), which is also the most common serological marker for cancer screening. However, there are unignorable limitations, including possible false-negatives/positives owing to confounding conditions. Reliable non-invasive diagnostics is still in urgent need. This work proposes a novel LDI-TOF-MS technique for HCC screening and diagnosis. By taking advantage of 3D nanostructures and machine learning, our technique enables high fidelity and reproducibility.
Methods
An LDI-TOF-MS platform was established for HCC screening and was applied to 139 patients with liver cancer, as well as 203 healthy controls (Table). All mass spectrum was collected within a mass range of 100 to 1,100 Da for metabolites. Based on the data acquired by LDI-TOF-MS, SVM algorithm was developed and applied for automated cancer classification across six cancer types, which was further validated by single blinded samples with randomly selected cancer patients and controls.Table: 1432P
Summary of patient and healthy control characteristics
Patient Type | N | Gender | Gender | Age | AJCC Stage | AJCC Stage | AJCC Stage | AJCC Stage |
---|---|---|---|---|---|---|---|---|
M(%) | F(%) | I | II | III | IV | |||
HCC | 139 | 120 (86.33%) | 19 (13.67%) | 55.63± 11.22(25-80) | 51 | 48 | 40 | - |
HC | 203 | 117 (57.64%) | 86 (42.36%) | 47.68± 10.78(23-76) | - | - | - | - |
Results
This assay demonstrated an average sensitivity of 96% and a specificity over 98% in detecting HCC. In our cohort, 47 of 137 HCC patients (35.77%) were AFP negative (AFP<20ng/ml, stage I n = 18, stage II n = 17 and stage III n = 12). Here, we showed that the LDI-TOF-MS recognized almost all AFP-negative HCC. The sensitivity and specificity were obviously superior to AFP in HCC: only 2 of 137 HCCs (1.46%) were misclassified as healthy controls. In contrast, AFP positive and AFP negative HCCs were not readily distinguished by this method. Therefore, this method was independent of tumor markers.
Conclusions
This work established a low-cost, high-throughput procedure based on trace amount of serum to identify HCC as well as healthy controls with superior precision, making it a promising technique for clinical cancer research and translation.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Zhongshan Hospital, Fudan University.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
2671 - Luminal B breast cancer prognosis prediction by comprehensive analysis of Homeobox genes
Presenter: Ayako Nakashoji
Session: Poster Display session 3
Resources:
Abstract
2650 - Long non-coding RNA E2F4as promotes tumor progression and predicts patient prognosis in human ovarian cancer
Presenter: Sun-Ae Park
Session: Poster Display session 3
Resources:
Abstract
1462 - FGF19 promotes esophageal squamous cell carcinoma progression by inhibiting autophagy
Presenter: Lisha Ying
Session: Poster Display session 3
Resources:
Abstract
5787 - Proof of concept on the role of ex vivo lung cancer spheroids, cytokines expression and PBMCs profiling in monitoring disease history and response to treatments.
Presenter: Raimondo Di Liello
Session: Poster Display session 3
Resources:
Abstract
5253 - Circulating microRNAs related to DNA damage response as predictors of survival in metastatic non- small cell lung cancer patients treated with platinum-based chemotherapy
Presenter: Dimitris Mavroudis
Session: Poster Display session 3
Resources:
Abstract
5286 - Prognostic value of CTCs in advanced NSCLC patients treated with platinum-based chemotherapy
Presenter: Silvia Calabuig-Fariñas
Session: Poster Display session 3
Resources:
Abstract
5781 - Exosomes in NSCLC as a source of biomarkers
Presenter: Elena Duréndez
Session: Poster Display session 3
Resources:
Abstract
1447 - The role of Pim-1 in the development and progression of papillary thyroid carcinoma
Presenter: Xin Zhu
Session: Poster Display session 3
Resources:
Abstract
1323 - Development and Validation of a RNA-Seq Based Prognostic Signature in Neuroblastoma
Presenter: Jian-Guo Zhou
Session: Poster Display session 3
Resources:
Abstract
3290 - Identification of meningioma patients in high risk of tumor recurrence using microRNA profiling
Presenter: Josef Srovnal
Session: Poster Display session 3
Resources:
Abstract