| 1. |
- Han, Shuangshuang, et al.
(författare)
-
Application value of CyTOF 2 mass cytometer technology at single-cell level in human gastric cancer cells
- 2019
-
Ingår i: Experimental Cell Research. - : Elsevier. - 0014-4827 .- 1090-2422. ; 384:1
-
Tidskriftsartikel (refereegranskat)abstract
- Chemotherapy and radiotherapy are main adjuvant therapies for the treatment of gastric cancer, the treatment effects are individual difference, but the specific mechanism is unknown. CyTOF 2 mass cytometer (CyTOF) enables the detecting up to 135 parameters on single cell, the emergence of which is an opportunity for proteomics research. We first tried to apply CyTOF technique to gastric cancer cells. We verified applicability of CyTOF in gastric cancer cells, and analyzed the responses of seventeen proteins to chemoradiotherapy in human gastric cancer AGS cells. To analyze the high dimensional CyTOF data, we used two statistical and visualization tools including viSNE and Citrus. Two specific clusters were found which had differences in protein expression profiles. CyTOF technology is proved feasibility and value at single cell level of gastric cancer.
|
|
| 2. |
- Pham, Tuan, et al.
(författare)
-
Deep Learning of P73 Biomarker Expression in Rectal Cancer Patients
- 2019
-
Ingår i: 2019 International Joint Conference on Neural Networks (IJCNN). - : IEEE. - 9781728119854 - 9781728119861
-
Konferensbidrag (refereegranskat)abstract
- By applying deep learning, we were able to compare p73 protein expression patterns of different tissue types including normal mucosa, primary tumor and lymph node metastasis in rectal cancer patients using immunohistochemical slides. The pair-wise pattern comparisons were automatedly carried out by considering color, edge, blobs, and other morphological information in the images. We discovered that when the pattern dissimilarity between primary tumor and lymph node metastasis is relatively low among other tissue pairs (primary tumor and distant normal, biopsy and distant normal, biopsy and primary tumor, biopsy and primary tumor, lymph node metastasis and distant normal, lymph node metastasis and biopsy), there was an implication of short-time survival. This original result suggests a novel application of advanced artificial intelligence in machine learning for clinical finding in rectal cancer and encourages relevant study of multiple biomarker expressions in cancer patients.
|
|
| 3. |
- Wang, Chao-Jie, et al.
(författare)
-
Prognostic value of nuclear FBI-1 in patients with rectal cancer with or without preoperative radiotherapy
- 2019
-
Ingår i: Oncology Letters. - : Spandidos Publications. - 1792-1074 .- 1792-1082. ; 18:5, s. 5301-5309
-
Tidskriftsartikel (refereegranskat)abstract
- Factor that binds to the inducer of short transcripts of the human immunodeficiency virus-1 (FBI-1) represents as a crucial gene regulator in colorectal cancer; however, the correlation between FBI-1 and preoperative radiotherapy (RT) in rectal cancer (RC) has not yet been reported. The aim was to detect FBI-1 expression in patients with RC with or without RT, by immunohistochemistry and quantitative polymerase chain reaction, and to analyze its association with clinicopathological features and response to RT. The results from immunohistochemistry analysis (n=139) and reverse transcription-quantitative polymerase chain reaction (n=55) demonstrated that FBI-1 was overexpressed in patients with RC, whether they had received preoperative RT or not. Subsequently, the association between FBI-1 expression, and the clinicopathological features and response to RT in patients with RC was analyzed. Cytoplasmic FBI-1 was upregulated in non-RT (n=77) and RT (n=62) groups (17.7 vs. 74.0%, P<0.001; 41.1 vs. 69.4%, P=0.002, respectively) of patients with RC compared with normal mucosa. However, nuclear FBI-1 was downregulated (75.8 vs. 22.1%, P<0.001; 83.9 vs. 35.5%, P<0.001, respectively) in both groups. RT had no significant effect on FBI-1 expression in RC tissues. Furthermore, nuclear FBI-1 was positively associated with tumor-node-metastasis stage and distant recurrence (P=0.003 and P=0.010, respectively). In patients with stage I, II or III RC, higher nuclear FBI-1 expression was associated with poorer disease-free survival [hazard ratio (HR)=1.934, 95% confidence interval (CI): 1.055-3.579, P=0.033] and overall survival (HR=2.174, 95% CI: 1.102-4.290, P=0.025), independently of sex, age, growth pattern, differentiation and RT. In addition, FBI-1 was positively correlated with numerous biological factors, including p73 [Spearman's correlation coefficient (rs)=0.332, P=0.007], lysyl oxidase (rs=0.234, P=0.043), Wrap53 (rs=-0.425, P=0.0002) and peroxisome proliferator-activated receptor δ (rs=-0.294, P=0.026). In conclusion, the present study demonstrated that nuclear FBI-1 was an independent prognostic factor in patients with RC and correlated with numerous biological factors, which indicated that it may have multiple roles in RC.
|
|
| 4. |
- Zhang, Xueli, 1990-, et al.
(författare)
-
Chromogranin-A Expression as a Novel Biomarker for Early Diagnosis of Colon Cancer Patients
- 2019
-
Ingår i: International Journal of Molecular Sciences. - : MDPI. - 1661-6596 .- 1422-0067. ; 20:12
-
Tidskriftsartikel (refereegranskat)abstract
- Colon cancer is one of the major causes of cancer death worldwide. The five-year survival rate for the early-stage patients is more than 90%, and only around 10% for the later stages. Moreover, half of the colon cancer patients have been clinically diagnosed at the later stages. It is; therefore, of importance to enhance the ability for the early diagnosis of colon cancer. Taking advantages from our previous studies, there are several potential biomarkers which have been associated with the early diagnosis of the colon cancer. In order to investigate these early diagnostic biomarkers for colon cancer, human chromogranin-A (CHGA) was further analyzed among the most powerful diagnostic biomarkers. In this study, we used a logistic regression-based meta-analysis to clarify associations of CHGA expression with colon cancer diagnosis. Both healthy populations and the normal mucosa from the colon cancer patients were selected as the double normal controls. The results showed decreased expression of CHGA in the early stages of colon cancer as compared to the normal controls. The decline of CHGA expression in the early stages of colon cancer is probably a new diagnostic biomarker for colon cancer diagnosis with high predicting possibility and verification performance. We have also compared the diagnostic powers of CHGA expression with the typical oncogene KRAS, classic tumor suppressor TP53, and well-known cellular proliferation index MKI67, and the CHGA showed stronger ability to predict early diagnosis for colon cancer than these other cancer biomarkers. In the protein-protein interaction (PPI) network, CHGA was revealed to share some common pathways with KRAS and TP53. CHGA might be considered as a novel, promising, and powerful biomarker for early diagnosis of colon cancer.
|
|
| 5. |
- Zhang, Xueli, 1990-, et al.
(författare)
-
Potential Applications of DNA, RNA and Protein Biomarkers in Diagnosis, Therapy and Prognosis for Colorectal Cancer : A Study from Databases to AI-Assisted Verification
- 2019
-
Ingår i: Cancers. - : MDPI. - 2072-6694. ; 11:2
-
Tidskriftsartikel (refereegranskat)abstract
- In order to find out the most valuable biomarkers and pathways for diagnosis, therapy and prognosis in colorectal cancer (CRC) we have collected the published CRC biomarkers and established a CRC biomarker database (CBD: http://sysbio.suda.edu.cn/CBD/index.html). In this study, we analysed the single and multiple DNA, RNA and protein biomarkers as well as their positions in cancer related pathways and protein-protein interaction (PPI) networks to describe their potential applications in diagnosis, therapy and prognosis. CRC biomarkers were collected from the CBD. The RNA and protein biomarkers were matched to their corresponding DNAs by the miRDB database and the PubMed Gene database, respectively. The PPI networks were used to investigate the relationships between protein biomarkers and further detect the multiple biomarkers. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Ontology (GO) annotation were used to analyse biological functions of the biomarkers. AI classification techniques were utilized to further verify the significances of the multiple biomarkers in diagnosis and prognosis for CRC. We showed that a large number of the DNA, RNA and protein biomarkers were associated with the diagnosis, therapy and prognosis in various degrees in the CRC biomarker networks. The CRC biomarkers were closely related to the CRC initiation and progression. Moreover, the biomarkers played critical roles in cellular proliferation, apoptosis and angiogenesis and they were involved in Ras, p53 and PI3K pathways. There were overlaps among the DNA, RNA and protein biomarkers. AI classification verifications showed that the combined multiple protein biomarkers played important roles to accurate early diagnosis and predict outcome for CRC. There were several single and multiple CRC protein biomarkers which were associated with diagnosis, therapy and prognosis in CRC. Further, AI-assisted analysis revealed that multiple biomarkers had potential applications for diagnosis and prognosis in CRC.
|
|
