Terahertz Photons Inhibit Cancer Cells Long Term by Suppressing Nano Telomerase Activity.

Telomeres are nanoscale DNA-protein complexes to protect and stabilize chromosomes. The reexpression of telomerase in cancer cells is a key determinant crucial for the infinite proliferation and long-term survival of most cancer cells. However, the use of telomerase inhibitors for cancer treatment may cause problems such as poor specificity, drug resistance, and cytotoxicity. Here, we discovered a nondrug and noninvasive terahertz modulation strategy capable of the long-term suppression of cancer cells by inhibiting telomerase activity. First, we found that an optimized frequency of 33 THz photon irradiation effectively inhibited the telomerase activity by molecular dynamics simulation and frequency filtering experiments. Moreover, in vitro experiments showed that telomerase activity in 4T1 and MCF-7 cells significantly decreased by 77% and 80% respectively, after 21 days of regular 33 THz irradiation. Furthermore, two kinds of cells were found to undergo aging, apoptosis, and DNA double-strand breaks caused by telomere crisis, which seriously affected the survival of cancer cells. In addition, the tumorigenicity of 4T1 cells irradiated with 33 THz waves for 21 days in in vivo mice decreased by 70%. In summary, this study demonstrates the potential application of THz modulation in nano therapy for cancer.

Identification of hepatocellular carcinoma and paracancerous tissue based on the peak area in FTIR microspectroscopy.

Hepatocellular carcinoma (HCC) is one of the most common primary hepatic malignancies across the world. The annual incidence and death rates have increased at the highest rate of all cancers in recent years. Surgical resection is a potentially curative option for solitary HCC or unilobar disease without evidence of metastases or vascular invasion. This study focuses on the molecular differences between the HCC foci and paracancerous tissues and provides some valuable biomarkers based on the vibrational spectrum. Fourier transform infrared (FTIR) spectroscopy is a non-invasive and qualitative and semi-quantitative analysis technique that has been widely applied for the identification of macromolecular changes in biological tissues. In this study, the FTIR spectra of the HCC foci and the paracancerous tissues were recorded separately, and ten areas under the absorption peaks of all the specimens were calculated. The result demonstrates that the areas of protein-related absorption peaks at 1398 cm-1, 1548 cm-1, 1654 cm-1 and 3070 cm-1 may be the key indicators of the two different regions. After coupling with the classification algorithms of k-nearest neighbor (KNN), random forest (RF) and support vector machine (SVM), it was found that SVM with an RBF kernel performed best with the AUC (area under the ROC curve) reaching 0.997, and the performance was better than the feature based on the full spectrum. This reveals that the peak area-based FTIR spectra combined with the SVM algorithm may be a promising tool in identifying the HCC foci and the paracancerous tissues.