scholarly journals Prognostic value of prostaglandin I2 synthase and its correlation with tumor-infiltrating immune cells in lung cancer, ovarian cancer, and gastric cancer

Aging ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 9658-9685
Author(s):  
Danian Dai ◽  
Bo Chen ◽  
Yanling Feng ◽  
Weizhong Wang ◽  
Yanhui Jiang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Lung Cancer ◽  
Ovarian Cancer ◽  
Immune Cells ◽  
Prognostic Value ◽  
Prostaglandin I2

Prognostic value of peripheral naive CD8+ T cells in oligometastatic non-small-cell lung cancer

2021 ◽  
Author(s):  
Xin Zhao ◽  
Yan Zhang ◽  
Zhenlin Gao ◽  
Yaguang Han
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
T Cells ◽  
Small Cell Lung Cancer ◽  
Immune Cells ◽  
Prognostic Value ◽  
Progression Free Survival ◽  
Small Cell ◽  
Small Cell Lung ◽  
Free Survival

Aim: This study aimed to investigate the prognostic value of peripheral naive and memory CD8+ and CD4+ T cells and other immune cells in patients with oligometastatic non-small-cell lung cancer (NSCLC) undergoing radiotherapy (RT). Methods: A total of 142 patients with oligometastatic NSCLC treated with RT were enrolled, and their blood samples were collected within 3 days before RT. Immune cells were identified by flow cytometry. Results: Patients with high levels of naive CD8+ T cells had longer overall survival (p = 0.004) and progression-free survival (p = 0.001) than those with low levels of naive CD8+ T cells. Multivariate analyses revealed that naive CD8+ T cells were independently correlated with overall survival (p = 0.019) and progression-free survival (p = 0.024). Conclusion: The results suggest that peripheral naive CD8+ T cells may be an independent prognostic indicator for patients with oligometastatic NSCLC undergoing RT.

scholarly journals Prognostic value of immune cells in the tumor microenvironment of early-stage lung cancer: a meta-analysis

Oncotarget ◽  
2019 ◽  
Vol 10 (67) ◽  
pp. 7142-7155 ◽  
Author(s):  
Stephanie Tuminello ◽  
Rajwanth Veluswamy ◽  
Wil Lieberman-Cribbin ◽  
Sacha Gnjatic ◽  
Francesca Petralia ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Prognostic Value ◽  
Early Stage ◽  
Meta Analysis ◽  
Early Stage Lung Cancer ◽  
Stage Lung Cancer

scholarly journals A PILOT CLINICAL TRIAL TO MONITOR RESPONSE TO CHEMOTHERAPY USING THE CA-62 MARKER OF EPITHELIAL CARCINOMAS

2019 ◽  
Vol 18 (5) ◽  
pp. 18-28
Author(s):  
G. G. Khakimova ◽  
Zh. R. Cherkasova ◽  
S. A. Tsurkan ◽  
G. A. Fedchikov ◽  
N. V. Suganov ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Gastric Cancer ◽  
Lung Cancer ◽  
Ovarian Cancer ◽  
Cancer Colorectal ◽  
Performance Status ◽  
Small Cell ◽  
Small Cell Lung ◽  
Neuroendocrine Cancer ◽  
Response To Chemotherapy

The objective of the study was to assess the feasibility of using CA -62 marker of epithelial carcinomas for monitoring treatment response and detecting cancer progression or recurrence during chemotherapy.Material and Methods. A 12-month double-blind clinical trial was conducted by two independent groups: clinical oncologists and biochemists, and involved 89 patients with different cancers confirmed by histopathological findings. The other inclusion criteria were: the presence of at least one measurable lesion according to the RECIST criteria, ECOG performance status 0-2 and satisfactory laboratory parameters. The expression of CA -62 cancer marker was measured by immunochemiluminescent assay used for the detection of epithelial carcinomas.Results. The elevated level of CA -62 marker was observed in 76 patients before starting the treatment. After completion chemotherapy, the level of this marker decreased to the normal reference ranges (<4600 U/ml) in 53 % of patients and remained increased in 24 % of patients. Of 24 % of patients with the initial low level of CA -62 marker (1000–4000 U/ml) before treatment, 12 % had no changes in the level of this marker during chemotherapy; however, 5 % of these patients had disease progression and 7 % had stable disease after starting the treatment. In 12 % of patients with an initial low CA -62 level, it increased during chemotherapy, indicating disease progression.Conclusion. The changes in the level of CA -62 marker during chemotherapy in patients with gastric cancer, small-cell lung cancer, colorectal cancer, neuroendocrine cancer and ovarian cancer showed a high correlation (76–100 % depending on the tumor site) with the performance status of the patients according to RECIST criteria. The CA -62 marker was shown to be feasible for monitoring gastric cancer, small-cell lung cancer, colorectal cancer, neuroendocrine cancer and ovarian cancer as well as for assessing the response to chemotherapy.

scholarly journals Biglycan Overexpression Predicts Poor Prognosis of Gastric Cancer

2021 ◽  
Author(s):  
Xin-zhou Huang ◽  
Hui Chen ◽  
Wen-ming Song ◽  
Ying-ying Wang ◽  
Meiyuan Zhou ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Prognostic Value ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Clinicopathological Parameters ◽  
Receptor Interaction ◽  
Significant Implication ◽  
Mrna Levels

Abstract Background: Biglycan (BGN) encodes an extracellular matrix (ECM) proteoglycan. However, the potential diagnostic and prognostic value of BGN in gastric cancer (GC) have not yet been reported. In this analysis, BGN expression in GC was evaluated across the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Oncomine databases, and verified using immunohistochemistry (IHC). The relationship between BGN expression and clinicopathological parameters was assessed by chi-square test and logistic regression. We analyzed the prognostic value of BGN. Then, Gene set enrichment analysis (GSEA) was used to screen the signaling pathways involved in high BGN expression datasets in GC. Finally, CIBERSORT was used to evaluate the infiltration of immune cells in GC tissues, and the correlation between BGN and infiltrating immune cells was analyzed.Results: The results showed that the mRNA levels of BGN were significantly up-regulated in GC compared with normal tissues (all P <0.001). The Kaplan-Meier plotter online database suggested that patients with high BGN expression had a poor prognosis (P=1.3e-10). In addition, using gene sets analysis, we found that pathways of bladder cancer, Wnt-signaling, TGF-beta signaling, and ECM-receptor interaction were differentially activated in high-expression BGN tissues. Furthermore, CIBERSORT analysis for the proportion of TICs revealed that macrophages M2 was positively correlated with BGN expression. Conclusions: In conclusion, BGN can be used as potential diagnostic markers of GC, and immune cell infiltration plays an important role in the occurrence and progression of GC. The finding may have significant implication for the diagnosis, prognosis and treatment of GC.

scholarly journals Comprehensive analysis of the expression of SLC30A family genes and prognosis in human gastric cancer

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yongdong Guo ◽  
Yutong He
Keyword(s):  
Gastric Cancer ◽  
Immune Cells ◽  
Survival Data ◽  
Prognostic Value ◽  
Expression Patterns ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Human Gastric Cancer ◽  
Advanced Tumor Stage ◽  
Advanced Tumor

Abstract The solute carrier 30 (SLC30) family genes play a fundamental role in various cancers. However, the diverse expression patterns, prognostic value, and potential mechanism of SLC30A family genes in gastric cancer (GC) remain unknown. Herein, we analyzed the expression and survival data of SLC30A family genes in GC patients using multiple bioinformatic approaches. Expression data of SLC30A family genes for GC patients were extracted from the Cancer Genome Atlas (TCGA) and genetic alteration frequency assessed by using cBioportal database. And validated the expression of SLC30A family genes in GC tissues and corresponding normal tissues. The prognostic value of SLC30A family genes in gastric cancer patients were explored using Kaplan–Meier plotter database. Functional enrichment analysis performed using DAVID database and clusterProfiler package. And ssGSEA algorithm was performed to explore the relationship between the SLC30A family genes and the infiltration of immune cells. We found that the median expression levels of SLC30A1-3, 5–7, and 9 were significantly upregulated in gastric cancer tissues compared to non-cancerous tissues, while SLC30A4 was downregulated. Meanwhile, SLC30A1-7, and 9 were significantly correlated with advanced tumor stage and nodal metastasis status, SLC30A5-7, and 9–10 were significantly related to the Helicobacter pylori infection status of GC patients. High expression of five genes (SLC30A1, 5–7, and 9) was significantly correlated with better overall survival (OS), first progression survival (FPS), and post progression survival (PPS). Conversely, upregulated SLC30A2-4, 8, and 10 expression was markedly associated with poor OS, FP and PPS. And SLC30A family genes were closely associated with the infiltration of immune cells. The present study implied that SLC30A5 and 7 may be potential biomarkers for predicting prognosis in GC patients, SLC30A2 and 3 play an oncogenic role in GC patients and could provide a new strategy for GC patients treatment.

Perbandingan CART dan Random Forest untuk Deteksi Kanker berbasis Klasifikasi Data Microarray

2020 ◽  
Vol 4 (5) ◽  
pp. 805-812
Author(s):  
Riska Chairunisa ◽  
Adiwijaya ◽  
Widi Astuti
Keyword(s):  
Breast Cancer ◽  
Lung Cancer ◽  
Ovarian Cancer ◽  
Random Forest ◽  
Classification And Regression Tree ◽  
Classification Method ◽  
Discrete Wavelet ◽  
Prostate Tumors ◽  
Cancer Data ◽  
Colon Tumors

Cancer is one of the deadliest diseases in the world with a mortality rate of 57,3% in 2018 in Asia. Therefore, early diagnosis is needed to avoid an increase in mortality caused by cancer. As machine learning develops, cancer gene data can be processed using microarrays for early detection of cancer outbreaks. But the problem that microarray has is the number of attributes that are so numerous that it is necessary to do dimensional reduction. To overcome these problems, this study used dimensions reduction Discrete Wavelet Transform (DWT) with Classification and Regression Tree (CART) and Random Forest (RF) as classification method. The purpose of using these two classification methods is to find out which classification method produces the best performance when combined with the DWT dimension reduction. This research use five microarray data, namely Colon Tumors, Breast Cancer, Lung Cancer, Prostate Tumors and Ovarian Cancer from Kent-Ridge Biomedical Dataset. The best accuracy obtained in this study for breast cancer data were 76,92% with CART-DWT, Colon Tumors 90,1% with RF-DWT, lung cancer 100% with RF-DWT, prostate tumors 95,49% with RF-DWT, and ovarian cancer 100% with RF-DWT. From these results it can be concluded that RF-DWT is better than CART-DWT.  

Distribution of Microsatellite Instability in Danish Ovarian Tumor Patients and the Prognostic Value in Ovarian Cancer Patients

2008 ◽  
Vol 17 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Farah D. Begum ◽  
Claus K. Høgdall ◽  
Susanne K. Kjær ◽  
Jan Blaakær ◽  
Lise Christensen ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Microsatellite Instability ◽  
Cancer Patients ◽  
Ovarian Tumor ◽  
Prognostic Value ◽  
Tumor Patients

THE PROGNOSTIC VALUE OF PD-L1 EXPRESSION IN TUMOR AND IMMUNE CELLS IN SQUAMOUS CELL CARCINOMA OF THE ORAL MUCOSA

2017 ◽  
Vol 63 (5) ◽  
pp. 759-765
Author(s):  
Svetlana Kutukova ◽  
Natalya Belyak ◽  
Grigoriy Raskin ◽  
Marina Mukhina ◽  
Georgiy Manikhas ◽  
...  
Keyword(s):  
Oral Mucosa ◽  
Malignant Tumor ◽  
Immune Cells ◽  
Prognostic Value ◽  
Hard Palate ◽  
Malignant Tumors ◽  
Small Cell ◽  
Alveolar Process ◽  
Small Cell Lung ◽  
Lower Jaw

The most frequent of malignant tumor cites of the oral mucosa are tongue - 55 %, mucosa of the cheek - 12 %, the fundus of the oral cavity - 10 %, the alveolar process of the upper jaw and the hard palate - 9 %, the alveolar process of the lower jaw - 6 %, the soft palate - 2 %. Malignant tumor cells carry PD-L1 ligands on their surface and its expression level is often correlated with an unfavorable prognosis in particular for such tumors as melanoma, kidney cancer and non-small cell lung cancer. It is relevant to evaluate the correlation between overexpression of PD-L1 and overall survival in patients with malignant tumors of the oral mucosa.

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