• Journal of Biomedical Engineering Research
• /
• v.38 no.5
• /
• pp.271-276
• /
• 2017

Cancer biomarkers are using in the diagnosis, staging, prognosis and prediction of disease progression. But, there are not sufficiently profiled and validated in early detection and risk classification of prostate cancer. In this study, we have devoted to finding a panel of serum biomarkers that are able to detect the diagnosis of prostate cancer. The serum samples were consisted of 111 prostate cancer and 343 control samples and examined. Eleven biomarkers were constructed in this study, and then nine biomarkers were relevant to candidate biomarkers by using t test. Finally, four biomarkers, PSA, ApoA2, CYFRA21.1 and TTR, were selected as the prostate cancer biomarker panel, logistic regression was used to identify algorithms for diagnostic biomarker combinations(AUC = 0.9697). A panel of combination biomarkers is less invasive and could supplement clinical diagnostic accuracy.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.7
• /
• pp.2601-2611
• /
• 2015

Prostate cancer, with a lifetime prevalence of one in six men, is the second cause of malignancy-related death and the most prevalent cancer in men in many countries. Nowadays, prostate cancer diagnosis is often based on the use of biomarkers, especially prostate-specific antigen (PSA) which can result in enhanced detection at earlier stage and decreasing in the number of metastatic patients. However, because of the low specificity of PSA, unnecessary biopsies and mistaken diagnoses frequently occur. Prostate cancer has various features so prognosis following diagnosis is greatly variable. There is a requirement for new prognostic biomarkers, particularly to differentiate between inactive and aggressive forms of disease, to improve clinical management of prostate cancer. Research continues into finding additional markers that may allow this goal to be attained. We here selected a group of candidate biomarkers including PSA, PSA velocity, percentage free PSA, $TGF{\beta}1$, AMACR, chromogranin A, IL-6, IGFBPs, PSCA, biomarkers related to cell cycle regulation, apoptosis, PTEN, androgen receptor, cellular adhesion and angiogenesis, and also prognostic biomarkers with Genomic tests for discussion. This provides an outline of biomarkers that are presently of prognostic interest in prostate cancer investigation.

• Journal of Digestive Cancer Research
• /
• v.3 no.1
• /
• pp.5-10
• /
• 2015

With advances in the understanding of the biology and genetics of colorectal cancer (CRC), diagnostic biomarkers that may predict the existence or future presence of cancer or a hereditary condition, and prognostic and treatment biomarkers that may direct the approach to therapy have been developed. Biomarkers can be ascertained and assayed from any tissue that may demonstrate the diagnostic or prognostic value, including from blood cells, epithelial cells via buccal swab, fresh or archival cancer tissue, as well as from cells shed into fecal material. For CRC, current examples of biomarkers for screening and surveillance include germline testing for suspected hereditary CRC syndromes, and stool DNA tests for screening average at-risk patients. Molecular biomarkers for CRC that may alter patient care and treatment include the presence or absence of microsatellite instability, the presence or absence of mutant KRAS, BRAF or PIK3CA, and the level of expression of 15-PGDH in the colorectal mucosa. Molecularly targeted therapies and some general therapeutic approaches rely on biomarker information. Additional novel biomarkers are on the horizon that will undoubtedly further the approach to precision or individualized medicine.

• BMB Reports
• /
• v.41 no.9
• /
• pp.615-625
• /
• 2008

Over a last decade, intense interest has been focused on biomarker discovery and their clinical uses. This interest is accelerated by the completion of human genome project and the progress of techniques in proteomics. Especially, cancer biomarker discovery is eminent in this field due to its anticipated critical role in early diagnosis, therapy guidance, and prognosis monitoring of cancers. Among cancers, lung cancer, one of the top three major cancers, is the one showing the highest mortality because of failure in early diagnosis. Numerous potential DNA biomarkers such as hypermethylations of the promoters and mutations in K-ras, p53, and protein biomarkers; carcinoembryonic antigen (CEA), CYFRA21-1, plasma kallikrein B1 (KLKB1), Neuron-specific enolase, etc. have been discovered as lung cancer biomarkers. Despite extensive studies thus far, few are turned out to be useful in clinic. Even those used in clinic do not show enough sensitivity, specificity and reproducibility for general use. This review describes what the cancer biomarkers are for, various types of lung cancer biomarkers discovered at present and predicted future advance in lung cancer biomarker discovery with proteomics technology.

• Asian Pacific Journal of Cancer Prevention
• /
• v.13 no.5
• /
• pp.1911-1915
• /
• 2012

Aim: New technologies for the early detection of pancreatic cancer (PC) are urgently needed. The aim of the present study was to screen for the potential protein biomarkers in serum using proteomic fingerprint technology. Methods: Magnetic beads combined with surface-enhanced laser desorption/ionization (SELDI) TOF MS were used to profile and compare the protein spectra of serum samples from 85 patients with pancreatic cancer, 50 patients with acute-on-chronic pancreatitis and 98 healthy blood donors. Proteomic patterns associated with pancreatic cancer were identified with Biomarker Patterns Software. Results: A total of 37 differential m/z peaks were identified that were related to PC (P < 0.01). A tree model of biomarkers was constructed with the software based on the three biomarkers (7762 Da, 8560 Da, 11654 Da), this showing excellent separation between pancreatic cancer and non-cancer., with a sensitivity of 93.3% and a specificity of 95.6%. Blind test data showed a sensitivity of 88% and a specificity of 91.4%. Conclusions: The results suggested that serum biomarkers for pancreatic cancer can be detected using SELDI-TOF-MS combined with magnetic beads. Application of combined biomarkers may provide a powerful and reliable diagnostic method for pancreatic cancer with a high sensitivity and specificity.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.20
• /
• pp.8529-8538
• /
• 2014

According to the China tumor registry 2013 annual report, breast cancer, lung cancer, and ovarian cancer are three common cancers in China nowadays, with high mortality due to the absence of early diagnosis technology. However, proteomics has been widespreadly implanted into every field of life science and medicine as an important part of post-genomics era research. The development of theory and technology in proteomics has provided new ideas and research fields for cancer research. Proteomics can be used not only for elucidating the mechanisms of carcinogenesis focussing on whole proteins of the tissue or cell, but also seeking the biomarkers for diagnosis and therapy of cancer. In this review, we introduce proteomics principles, covering current technology used in exploring early diagnosis biomarkers of breast cancer, lung cancer and ovarian cancer.

• Journal of Biomedical Engineering Research
• /
• v.30 no.2
• /
• pp.122-128
• /
• 2009

Cancer serum biomarkers have advanced our ability to more accurately predict tumor classification, prognostic/metastatic potential, and response potential to novel chemotherapies. Serum amyloid A (SAA) and Vascular endothelial growth factor (VEGF) have potential utility as a serum biomarker for lung cancer. Quantum dots, nanometer-sized crystals, have a high quantum yield, sensitivity, and pronounced photostability. The properties of quantum dots can be efficiently applied to the detection of serum biomarkers in immunoassays as fluorescent probe. We used quantum dots as fluorescent probes in immunoassays and attempted to detect serum amyloid A and vascular endothelial growth factor as serum biomarkers of lung cancer. This fluorescence immunoassay based on the properties of quantum dots is applicable to the detection of serum biomarkers for lung cancer. The fluorescence immunoassay with quantum dots should allow the efficient and specific detection of serum amyloid A (SAA) for the possible diagnosis of lung cancer.

• Mass Spectrometry Letters
• /
• v.4 no.4
• /
• pp.59-66
• /
• 2013

A metabolomics study was conducted to identify urinary biomarkers for breast cancer, using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS), analyzed by principal components analysis (PCA) as well as a partial least squares-discriminant analysis (PLS-DA) for a metabolic pattern analysis. To find potential biomarkers, urine samples were collected from before- and after-mastectomy of breast cancer patients and healthy controls. Androgens, corticoids, estrogens, nucleosides, and polyols were quantitatively measured and urinary metabolic profiles were constructed through PCA and PLS-DA. The possible biomarkers were discriminated from quantified targeted metabolites with a metabolic pattern analysis and subsequent screening. We identified two biomarkers for breast cancer in urine, ${\beta}$-cortol and 5-methyl-2-deoxycytidine, which were categorized at significant levels in a student t-test (p-value < 0.05). The concentrations of these metabolites in breast cancer patients significantly increased relative to those of controls and patients after mastectomy. Biomarkers identified in this study were highly related to metabolites causing oxidative DNA damage in the endogenous metabolism. These biomarkers are not only useful for diagnostics and patient stratification but can be mapped on a biochemical chart to identify the corresponding enzyme for target identification via metabolomics.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.8
• /
• pp.3425-3428
• /
• 2015

Objective: To explore the association of serum tumor abnormal protein (TAP) with other serological biomarkers e.g. carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), carbohydrate antigen 19-9 (CA19-9) and its clinical application in colorectal cancer (CRC) patients. Methods: Patients (N=98) were enrolled into this study with histologically or cytologically confirmed CRC. Using a test kit, the level of TAP was determined, while chemiluminescence was used to measure the levels of some other common serological biomarkers e.g. CEA, CA125 and CA19-9. Results: The area of TAP condensed particulate matter decreased after chemotherapy compared with before chemotherapy when CT or MRI scans showed disease control. In contrast, it increased with disease progression (P<0.05). Furthermore, a statistically significant difference was confirmed in monitoring of TAP and common serological biomarkers e.g. CEA and CA19-9 (p<0.05). Conclusions: Detecting TAP in CRC patients has high sensitivity and specificity and can be used as a new independent indicator for clinically monitoring CRC patients in the course of chemotherapy.

• Experimental and Molecular Medicine
• /
• v.50 no.12
• /
• pp.10.1-10.11
• /
• 2018

Cancer growth and progression are associated with immune suppression. Cancer cells have the ability to activate different immune checkpoint pathways that harbor immunosuppressive functions. Monoclonal antibodies that target immune checkpoints provided an immense breakthrough in cancer therapeutics. Among the immune checkpoint inhibitors, PD-1/PD-L1 and CTLA-4 inhibitors showed promising therapeutic outcomes, and some have been approved for certain cancer treatments, while others are under clinical trials. Recent reports have shown that patients with various malignancies benefit from immune checkpoint inhibitor treatment. However, mainstream initiation of immune checkpoint therapy to treat cancers is obstructed by the low response rate and immune-related adverse events in some cancer patients. This has given rise to the need for developing sets of biomarkers that predict the response to immune checkpoint blockade and immune-related adverse events. In this review, we discuss different predictive biomarkers for anti-PD-1/PD-L1 and anti-CTLA-4 inhibitors, including immune cells, PD-L1 overexpression, neoantigens, and genetic and epigenetic signatures. Potential approaches for further developing highly reliable predictive biomarkers should facilitate patient selection for and decision-making related to immune checkpoint inhibitor-based therapies.