We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected from 1404 subjects having one of 17 different disease conditions included in the study or having no evidence of any disease (healthy controls). Blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined. Analysis of the artificially intelligent nanoarray also showed that each disease has its own unique breathprint, and that the presence of one disease would not screen out others. Cluster analysis showed a reasonable classification power of diseases from the same categories. The effect of confounding clinical and environmental factors on the performance of the nanoarray did not significantly alter the obtained results. The diagnosis and classification power of the nanoarray was also validated by an independent analytical technique, i.e., gas chromatography linked with mass spectrometry. This analysis found that 13 exhaled chemical species, called volatile organic compounds, are associated with certain diseases, and the composition of this assembly of volatile organic compounds differs from one disease to another. Overall, these findings could contribute to one of the most important criteria for successful health intervention in the modern era, viz. easy-to-use, inexpensive (affordable), and miniaturized tools that could also be used for personalized screening, diagnosis, and follow-up of a number of diseases, which can clearly be extended by further development.

Metastasis remains one of the major challenges before hepatocellular carcinoma (HCC) is finally conquered. This paper summarized a decade's studies on HCC metastasis at the Liver Cancer Institute of Fudan University. We have established a stepwise metastatic human HCC model system, which included a metastatic HCC model in nude mice (LCI-D20), a HCC cell line with high metastatic potential (MHCC97), a relatively low metastatic potential cell clone (MHCC97L) and several stepwise high metastatic potential cell clones (MHCC97H, HCCLM3, and HCCLM6) from their parent MHCC97 cell. Endeavors have been made for searching human HCC metastasis-related chromosomes/proteins/genes. Monogene-based studies revealed that HCC invasion/metastasis was similar to that of other solid tumors, and the biological characteristics of small HCC were only slightly better than that of large HCC. Using comparative genomic hybridization (CGH), fluorescence in situ hybridization (FISH), genotyping, cDNA microarray, and 2-dimensional gel electrophoresis, we obtained some interesting results. In particular, in collaboration with the National Institute of Health (NIH) in the United States, we generated a molecular signature that can classify metastatic HCC patients, identified osteopontin as a lead gene in the signature, and found that genes favoring metastasis progression were initiated in the primary tumors. We also found that chromosome 8p deletion, particularly in the region of 8p23, was associated with HCC metastasis. Cytokeratin 19 was identified as one of the proteins, which was found in MHCC97H, but not in MHCC97L cells. Experimental interventions using the high metastatic nude mice model have provided clues for the prevention of HCC metastasis. Translation from workbench to bedside demonstrated that serum VEGF, microvessel density, and p53 scoring may be of value for the prediction of postoperative metastatic recurrence. Interferon alpha proved effective for the prevention of recurrence both experimentally and clinically. In conclusion, HCC metastasis that probably initiated in the primary tumor is a multigene-involved, multistep, and changing process. The further elucidation of the mechanism underlying HCC metastasis will provide a more solid basis for the prediction and prevention of the metastatic recurrence of HCC.

Background:Upper digestive endoscopy with biopsy and histopathological evaluation of the biopsy material is the standard method for diagnosing gastric cancer (GC). However, this procedure may not be widely available for screening in the developing world, whereas in developed countries endoscopy is frequently used without major clinical gain. There is a high demand for a simple and non-invasive test for selecting the individuals at increased risk that should undergo the endoscopic examination. Here, we studied the feasibility of a nanomaterial-based breath test for identifying GC among patients with gastric complaints.Methods:Alveolar exhaled breath samples from 130 patients with gastric complaints (37 GC/32 ulcers / 61 less severe conditions) that underwent endoscopy/biopsy were analyzed using nanomaterial-based sensors. Predictive models were built employing discriminant factor analysis (DFA) pattern recognition, and their stability against possible confounding factors (alcohol/tobacco consumption; Helicobacter pylori) was tested. Classification success was determined (i) using leave-one-out cross-validation and (ii) by randomly blinding 25% of the samples as a validation set. Complementary chemical analysis of the breath samples was performed using gas chromatography coupled with mass spectrometry.Results:Three DFA models were developed that achieved excellent discrimination between the subpopulations: (i) GC vs benign gastric conditions, among all the patients (89% sensitivity; 90% specificity); (ii) early stage GC (I and II) vs late stage (III and IV), among GC patients (89% sensitivity; 94% specificity); and (iii) ulcer vs less severe, among benign conditions (84% sensitivity; 87% specificity). The models were insensitive against the tested confounding factors. Chemical analysis found that five volatile organic compounds (2-propenenitrile, 2-butoxy-ethanol, furfural, 6-methyl-5-hepten-2-one and isoprene) were significantly elevated in patients with GC and/or peptic ulcer, as compared with less severe gastric conditions. The concentrations both in the room air and in the breath samples were in the single p.p.b.v range, except in the case of isoprene.Conclusion:The preliminary results of this pilot study could open a new and promising avenue to diagnose GC and distinguish it from other gastric diseases. It should be noted that the applied methods are complementary and the potential marker compounds identified by gas-chromatography/mass spectrometry are not necessarily responsible for the differences in the sensor responses. Although this pilot study does not allow drawing far-reaching conclusions, the encouraging preliminary results presented here have initiated a large multicentre clinical trial to confirm the observed patterns for GC and benign gastric conditions.

No abstract

Given that only a subset of patients with colorectal cancer (CRC) benefit from immune checkpoint therapy, efforts are ongoing to identify markers that predict immunotherapeutic response. Increasing evidence suggests that microbes influence the efficacy of cancer therapies. Fusobacterium nucleatum induces different immune responses in CRC with different microsatellite-instability (MSI) statuses. Here, we investigated the effect of F. nucleatum on anti-PD-L1 therapy in CRC. We found that high F. nucleatum levels correlate with improved therapeutic responses to PD-1 blockade in patients with CRC. Additionally, F. nucleatum enhanced the antitumor effects of PD-L1 blockade on CRC in mice and prolonged survival. Combining F. nucleatum supplementation with immunotherapy rescued the therapeutic effects of PD-L1 blockade. Furthermore, F. nucleatum induced PD-L1 expression by activating STING signaling and increased the accumulation of interferon-gamma (IFN-γ)+ CD8+ tumor-infiltrating lymphocytes (TILs) during treatment with PD-L1 blockade, thereby augmenting tumor sensitivity to PD-L1 blockade. Finally, patient-derived organoid models demonstrated that increased F. nucleatum levels correlated with an improved therapeutic response to PD-L1 blockade. These findings suggest that F. nucleatum may modulate immune checkpoint therapy for CRC.