Quantitative detection of the human cervical cancer oncogene for monitoring the minimal residual disease in acute leukemia

Discrimination of different cancer types clustering Raman spectra by a super paramagnetic stochastic network approach

Based in high sensitivity and specificity reported recently in detection of the cancer, the technique of Raman spectroscopy is proposed to discriminate between breast cancer, leukemia and cervical cancer using blood serum samples from patients officially diagnosed. In order to classify Raman spectra, clustering method known as Super Paramagnetic Clustering based on statistical physics concepts with a stochastic approach was implemented. Comparing firstly average Raman spectra of the three cancers, some peaks that allowed differentiating one cancer from other were identified, however, other peaks allowed concluding that there are biochemical similarities among them. According to these spectra, the band associated with amide I (1654 cm-1) and one of two shoulders assigned to amide III (1230-1282 cm-1) allowed discriminating leukemia from breast and cervical cancer, whereas band 714 cm-1 (polysaccharides) achieves to differentiate cervical cancer from leukemia and breast cancer, and bulged region, 1040 - 1100 cm-1 (phenylalanine, phospholipid) discriminated breast cancer from leukemia and cervical cancer. Subsequently, Super Paramagnetic Clustering method was applied to Raman spectra to study similarity relationships between cancers based on the biochemical composition of serum samples. Finally, as a cross check method, the standard method to classify Raman spectra of breast cancer, leukemia and cervical cancer, known as principal components analysis, was used showing excellent agreement with results of Super Paramagnetic Clustering method. Preliminary results demonstrated that Raman spectroscopy and Super Paramagnetic Clustering method can be used to discriminate between breast cancer, leukemia and cervical cancer samples using blood serum samples.

Targeting HCCR expression resensitizes gastric cancer cells to chemotherapy via down-regulating the activation of STAT3

The human cervical cancer oncogene (HCCR) has been found to be overexpressed in a variety of human cancers. However, the level of expression of HCCR and its biological function in gastric cancer are largely unknown. In this study, we evaluated HCCR expression in several gastric cancer cell lines and in one normal gastric mucosal cell line. We established a 5-FU-resistant gastric cancer cell subline, and we evaluated its HCCR expression. HCCR expression levels were high in gastric cancer lines, and expression was significantly increased in the 5-FU-resistant cancer cell subline. HCCR expression affected cell growth by regulating apoptosis in the cancer cells, and it had a positive correlation with p-STAT3 expression. Western blot and luciferase reporter assays showed that the activation of STAT3 upregulated HCCR expression in a positive feedback loop model. In vivo and in vitro studies showed that HCCR plays an important role in the apoptosis induced by 5-FU. Our data demonstrate that HCCR is probably involved in apoptosis and cancer growth and that it functions as a p-STAT3 stimulator in a positive feedback loop model. In gastric cancer cells, HCCR confers a more aggressive phenotype and resistance to 5-FU-based chemotherapy.