List Of Candidate Biomarkers Research Articles

ScRNA-seq based copy number variations (CNVs) detection identified TPSB2 and TPSAB1 as prognostic biomarkers in Gastric Cancer(GC).

e16021 Background: Gastric Cancer (GC) is the third leading cause of cancer-related mortality around the world, with a relatively poor prognosis. Single-cell RNA-sequencing (scRNA-seq) is a powerful tool to analyze tumor microenvironment at a comprehensive resolution, revealing previously uncharacterized molecular complexities. CNVs detection based on scRNA-seq data can reveal genome heterogeneity, therefore identify prognostic biomarkers at the single cell level. Methods: ScRNA-seq data from publicly available dataset (Anuja S et.al, CCR 2020) with 3 gastric cancer tissues, and 3 paired adjacent normal tissues was used. We inferred CNVsusing non-malignant cells as reference to estimate the mutations of malignant cells based on InferCNV package. Survival analysis was made by Kaplan-Meier method on TCGA-STAD (Stomach adenocarcinoma) cohort to identify the CNV genes with prognostic ability. To further explore these genes, their correlations with CD8+T cells marker ( CD8A) and malignant marker ( EPCAM) were analyzed based on the Spearman Correlation Method. Results: From a total of 11,459 cells, comprising 3 gastric cancer tissues (7,634 cells), and 3 paired adjacent normal tissues (3,825 cells), we identified 23 clusters that belonged to different types of cells including Endothelial, Epithelial, Fibroblast, B cells, Myeloid cells, T cells and NK cells. InferCNV analysis predicted 5 CNV regions and 209 CNV genes according to the heterogeneity between malignant and non-malignant cells. Survival analysis based on RNA-seq data from TCGA-STAD cohort, enabled us to narrow down the list of candidate biomarkers to 22 genes with prognostic ability. Among them, the specific functions of TPSB2 and TPSAB1 in GC, especially in their prognosis value, remain unclear. Downregulations of these 2 genes were both associated with longer progression-free survival (PFS). More specifically, expression profiles of gene TPSB2 and TPSAB1 were positively correlated with Epithelial marker genes (p = 0.02 and 0.03 respectively) but negatively correlated with CD8+ T lymphocytes (p = 0.02 and 0.11 respectively). Conclusions: Our analysis suggested that the high expressions of gene TPSB2 and TPSAB1 are associated with poor prognosis in GC patients. And these two genes are correlated with low T lymphocyte infiltration and an immune-suppressive environment, which could be possible prognosis biomarkers to identify patients with a more aggressive tumor evolution.

Back Cover: Label‐Free Quantitative Proteomic Screening of Candidate Plasma Biomarkers for the Prognosis of Breast Cancer with Different Lymph Node Statuses

Patients with lymph node involvement have less favorable prognosis and higher risk of recurrence. A label-free quantitative proteomic strategy is applied to construct plasma proteomes of ten patients with different lymph node statuses. The present dataset provides a list of candidate biomarkers that can be used for early diagnosis and prognosis of breast cancer with lymph node metastasis. This is reported by Ling Chen, Weibo Zhao, Jing He, Liqi Li, Dong Meng, Dongyan Cai, Jinjin Yu, Daozhen Chen, Yibo Wu and Tao Zhou, article number 1700117.

Label-Free Quantitative Proteomic Screening of Candidate Plasma Biomarkers for the Prognosis of Breast Cancer with Different Lymph Node Statuses.

Lymph node status is a crucial predictor for the overall survival of invasive breast cancer. However, lymph node involvement is only detected in about half of HER2-positive patients. Since patients with lymph node involvement has less favorable prognosis and higher risk of recurrence, it is important to develop plasma protein biomarkers for distinguishing lymph node metastasis. A label-free quantitative proteomic strategy to construct plasma proteomes of ten patients with small size HER2-positive breast cancer (five patients with lymph node metastasis versus five patients without lymph node metastasis) is applied. A total of 388 proteins are identified, of which 33 proteins are differentially expressed. Statistical analyses suggested the present strategy is low cost and highly efficient in initial screening of plasma biomarkers. In silico analyses using various bioinformatics databases show that these altered proteins are highly associated with breast disease, cancer pathway, lymph node morphology, metastasis, complement pathway, and immune regulation. The present dataset provides a list of candidate biomarkers that could be used for early differentiation diagnosis and prognosis of breast cancer with lymph node metastasis.

Abstract 5513: An immune-active tumor microenvironment favors clinical response to ipilimumab

Abstract Ipilimumab, a fully human monoclonal antibody specific to CTLA-4, has shown improvement in overall survival in previously treated advance melanoma patients. As a consequence of blockade of the T cell regulatory molecule CTLA-4, ipilimumab treatment is associated with proliferation and activation of peripheral T cells. An important factor for impacting tumor growth however, is whether these T cells can successfully migrate into the tumor. In order to gain a better understanding of the various tumor-associated components that determine the clinical activity of ipilimumab in melanoma tumors, Affymetrix gene expression profiling and pathway analysis were retrospectively performed on 46 primary or metastatic melanoma tumors, collected in a complete phase II clinical trial in advanced melanoma patients. In biopsies obtained at baseline (before treatment), there were 361 differentially genes expressed (≥ 1.5 fold difference in expression, p ≤ 0.01); most over-expressed transcripts and pathways associated with favorable clinical activity were immune-related. Furthermore, differential analysis of mRNA from pre- and post-treatment tumor biopsies pointed to additional increase in the expression of these genes after treatment. Interestingly, ipilimumab treatment was associated with down-regulation of a number of melanoma-associated transcripts in the tumors within a short time (3 weeks after the first dose). Our preliminary results suggest that high pre-existing immune-activity favors clinical response to ipilimumab. These analyses also provide a list of candidate biomarkers with potential predictive value for response to ipilimumab, to be confirmed in a larger, placebo controlled clinical trial. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5513. doi:10.1158/1538-7445.AM2011-5513

Abstract 4560: Integrative proteomic profiling of pancreatic cancer cell line supernatants, pancreatic juice and ascites fluid for the identification of novel pancreatic cancer biomarkers

Abstract Pancreatic cancer is a highly lethal malignancy for which circulating biomarkers with high sensitivity and specificity are urgently needed. Proteins secreted or shed from tumor cells and their microenvironment have the highest chance of reaching the circulation and serving as measurable indicators of disease status. In this respect, we extensively characterized the proteomes of pancreatic cancer cell culture supernatants, in conjunction with proximal biological fluids, for the identification of novel candidate biomarkers. Specifically, we characterized the secretomes of the pancreatic cancer cell lines MIA-PaCa2, BxPc-3, Capan1, SU.86.86, CFPAC-1 and Panc1, along with the normal pancreatic ductal epithelial cell line HPDE, through multidimensional separation using strong-cation exchange chromatography, and reverse-phase chromatography coupled online to an LTQ-Orbitrap hybrid mass spectrometer. For each cell line, optimal growth conditions to achieve increased protein secretion with minimal cell death were first selected for, and each cell line was analyzed using three biological replicates. Generated spectra were searched against both MASCOT and X!Tandem using the human IPI 3.62 forward and reverse database and results were integrated using Scaffold 2.06 software. This resulted in a non-redundant list of between 2000 and 3500 proteins identified in the conditioned media from each of the cell lines, with a false positive rate of approximately 1%. Together, a total of 5009 non-redundant proteins with unique gene names were identified in the seven cell lines combined. Upon performing gene ontology annotations, approximately 27% of the proteins were found to localize to the extracellular or plasma membrane components. We subsequently performed proteomic analysis of pancreatic juice from cancer and chronic pancreatitis patients, as well as ascites fluid from pancreatic cancer patients. Through integration of the proteins identified in the pancreatic juice and ascites fluid analyses with that of the cell line conditioned media, we prioritized a list of candidate biomarkers for verification in serum from cancer versus controls through established quantitative methods. To aid in our candidate selection, we also performed multiple pathway and tissue specificity analyses using publically available databases, and made comparisons to proteins identified in relevant tissue proteomics and microarray studies found in the literature. Our analysis identified many previously studied pancreatic cancer biomarkers, which serves to validate our discovery approach. To our knowledge, this study comprises the most exhaustive proteome from pancreatic cancer cell lines, and the proteins identified through integration of the multiple biological sources can now serve as a mine for novel biomarkers and therapeutic targets. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4560.