scholarly journals Identification and Validation of a Novel Immune-Related lncRNA Signature for Bladder Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Shan Hua ◽  
Zhiwen Xie ◽  
Wenhao Wang ◽  
Zhong Wan ◽  
Min Chen ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Survival Time ◽  
Cancer Patients ◽  
Checkpoint Inhibitors ◽  
Univariate Analysis ◽  
Risk Groups ◽  
The Cancer Genome Atlas ◽  
Receiver Operating Curve ◽  
Multiple Perspectives ◽  
Pathological Characteristics

PurposeWe aimed to construct an immune-related long noncoding ribonucleic acids (irlncRNA) signature to evaluate the prognosis of patients without specific expression level of these irlncRNA.MethodsThe raw transcriptome data were downloaded from The Cancer Genome Atlas (TCGA), irlncRNAs were filtered out using an online immune related gene database and coexpression analysis, differently expressed irlncRNA (DEirlncRNA) pairs were identified by univariate analysis. The areas under curve (AUC) were compared and the Akaike information criterion (AIC) values of receiver operating curve (ROC) was counted, the most optimal model was constructed to divide bladder cancer patients into high- and low-risk groups usingõ the cut-off point of ROC. Then, we evaluated them from multiple perspectives, such as survival time, clinic-pathological characteristics, immune-related cells infiltrating, chemotherapeutics efficacy and immune checkpoint inhibitors.Results14 DEirlncRNA pairs were included in this signature. Patients in high-risk groups demonstrated apparent shorter survival time, more aggressive clinic-pathological characteristics, different immune-related cells infiltrating status, lower chemotherapeutics efficacy.ConclusionThe irlncRNA signature demonstrated a promising prediction value for bladder cancer patients and was important in guiding clinical treatment.

scholarly journals MMP-7 Serum and Tissue Levels Are Associated with Poor Survival in Platinum-Treated Bladder Cancer Patients

Diagnostics ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 48
Author(s):  
Tibor Szarvas ◽  
Michèle J. Hoffmann ◽  
Csilla Olah ◽  
Eszter Szekely ◽  
Andras Kiss ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Cancer Patients ◽  
Cell Lines ◽  
Checkpoint Inhibitors ◽  
Serum Concentrations ◽  
Serum Samples ◽  
Poor Overall Survival ◽  
Platinum Sensitivity ◽  
Therapeutic Decisions ◽  
Platinum Based Chemotherapy

Chemotherapy resistance is a main cause of therapeutic failure and death in bladder cancer. With the approval of immune checkpoint inhibitors, prediction of platinum treatment became of great clinical importance. Matrix metalloproteinase-7 (MMP-7) was shown to be involved in cisplatin resistance. Therefore, tissue and circulating MMP-7 levels were evaluated in 124 bladder cancer patients who received postoperative platinum-based chemotherapy. Tissue MMP-7 levels were analyzed by immunohistochemistry in 72 formalin-fixed, paraffin-embedded chemo-naïve tumor samples, while MMP-7 serum concentrations were determined in 132 serum samples of an independent cohort of 52 patients. MMP-7 tissue and serum levels were correlated with clinicopathological and follow-up data. MMP-7 gene expression was determined by RT-qPCR in 20 urothelial cancer cell lines and two non-malignant urothelial cell lines. MMP-7 was overexpressed in RT-112 and T-24 cells by stable transfection, to assess its functional involvement in platinum sensitivity. High MMP-7 tissue expression and pretreatment serum concentrations were independently associated with poor overall survival (tissue HR = 2.296, 95%CI = 1.235–4.268 and p = 0.009; serum HR = 2.743, 95%CI = 1.258–5.984 and p = 0.011). Therefore, MMP-7 tissue and serum analysis may help to optimize therapeutic decisions. Stable overexpression in RT-112 and T-24 cells did not affect platinum sensitivity.

scholarly journals The Prognostic Value of the New Combined Hemo-Eosinophil Inflammation Index (HEI Index): A Multicenter Analysis of Anal Cancer Patients Treated with Concurrent Chemo-Radiation

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 671
Author(s):  
Margherita Rimini ◽  
Pierfrancesco Franco ◽  
Berardino De Bari ◽  
Maria Giulia Zampino ◽  
Stefano Vagge ◽  
...  
Keyword(s):  
High Risk ◽  
Cancer Patients ◽  
Anal Cancer ◽  
Prognostic Score ◽  
Univariate Analysis ◽  
External Validation ◽  
Risk Groups ◽  
Anal Squamous Cell Carcinoma ◽  
Predictors Of Response ◽  
Risk Patients

Anal squamous cell carcinoma (SCC) is a rare tumor, and bio-humoral predictors of response to chemo-radiation (CT-RT) are lacking. We developed a prognostic score system based on laboratory inflammation parameters. We investigated the correlation between baseline clinical and laboratory variables and disease-free (DFS) and overall (OS) survival in anal SCC patients treated with CT-RT in five institutions. The bio-humoral parameters of significance were included in a new scoring system, which was tested with other significant variables in a Cox’s proportional hazard model. A total of 308 patients was included. We devised a prognostic model by combining baseline hemoglobin level, SII, and eosinophil count: the Hemo-Eosinophils Inflammation (HEI) Index. We stratified patients according to the HEI index into low- and high-risk groups. Median DFS for low-risk patients was not reached, and it was found to be 79.5 months for high-risk cases (Hazard Ratio 3.22; 95% CI: 2.04–5.10; p < 0.0001). Following adjustment for clinical covariates found significant at univariate analysis, multivariate analysis confirmed the HEI index as an independent prognostic factor for DFS and OS. The HEI index was shown to be a prognostic parameter for DFS and OS in anal cancer patients treated with CT-RT. An external validation of the HEI index is mandatory for its use in clinical practice.

scholarly journals A machine learning approach for somatic mutation discovery

2018 ◽  
Vol 10 (457) ◽  
pp. eaar7939 ◽  
Author(s):  
Derrick E. Wood ◽  
James R. White ◽  
Andrew Georgiadis ◽  
Beth Van Emburgh ◽  
Sonya Parpart-Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cancer Patients ◽  
Somatic Mutation ◽  
Mutation Detection ◽  
Checkpoint Inhibitors ◽  
False Negative ◽  
The Cancer Genome Atlas ◽  
High Quality ◽  
Lung Cancer Patients ◽  
Mutation Discovery

Variability in the accuracy of somatic mutation detection may affect the discovery of alterations and the therapeutic management of cancer patients. To address this issue, we developed a somatic mutation discovery approach based on machine learning that outperformed existing methods in identifying experimentally validated tumor alterations (sensitivity of 97% versus 90 to 99%; positive predictive value of 98% versus 34 to 92%). Analysis of paired tumor-normal exome data from 1368 TCGA (The Cancer Genome Atlas) samples using this method revealed concordance for 74% of mutation calls but also identified likely false-positive and false-negative changes in TCGA data, including in clinically actionable genes. Determination of high-quality somatic mutation calls improved tumor mutation load–based predictions of clinical outcome for melanoma and lung cancer patients previously treated with immune checkpoint inhibitors. Integration of high-quality machine learning mutation detection in clinical next-generation sequencing (NGS) analyses increased the accuracy of test results compared to other clinical sequencing analyses. These analyses provide an approach for improved identification of tumor-specific mutations and have important implications for research and clinical management of cancer patients.

scholarly journals Effects of Arsenic (+3 Oxidation State) Methyltransferase Gene Polymorphisms and Expression on Bladder Cancer: Evidence from a Systematic Review, Meta-analysis and TCGA Dataset

2020 ◽  
Vol 177 (1) ◽  
pp. 27-40
Author(s):  
Yuxuan Song ◽  
Donghui Jin ◽  
Jingyi Chen ◽  
Wanfeng Liang ◽  
Xiaoqiang Liu
Keyword(s):  
Bladder Cancer ◽  
Survival Time ◽  
Oxidation State ◽  
Meta Analysis ◽  
The Cancer Genome Atlas ◽  
Related Factor ◽  
Genotype Distribution ◽  
Case Control Studies ◽  
Poor Overall Survival ◽  
Allele Distribution

Abstract Inorganic arsenic (iAs) is a recognized environment-related factor for bladder cancer (BCa). Arsenic (+3 oxidation state) methyltransferase (AS3MT) gene might influence BCa by regulating iAs metabolism. The aim of the present study was to explore whether AS3MT polymorphisms could affect BCa susceptibility. We systematically reviewed eligible case-control studies about AS3MT polymorphisms and BCa and to further compare the genotype distribution and allele distribution between BCa patients and controls by meta-analysis for humans. Besides, to clarify the effects of AS3MT expression on BCa clinical outcomes and survival time, we also conducted a series of analyses based on The Cancer Genome Atlas dataset. Databases were systematically retrieved and we applied Stata software to perform meta-analysis. The registration of this study protocol is at PROSPERO and ID is CRD42019133947. Five articles were recruited and pooled results demonstrated that rs3740393 and rs11191438 polymorphisms were related to BCa risk in overall population (p &lt; .05) in the overall population. In addition, GG and GC genotypes in rs3740393 and GG genotype in rs11191438 might be the susceptibility genotypes for BCa. Results based on 168 BCa samples from TGCA indicated that patients with higher expression of AS3MT had poor overall survival time and AS3MT expression is an independent indicator for BCa survival. This study identified that AS3MT polymorphisms could affect BCa risk and AS3MT expression was pivotal in prognosis of BCa.

scholarly journals Development and Validation of A Seven-microRNA Signature as a Novel Prognostic Biomarker for Bladder Cancer

2020 ◽  
Author(s):  
Jin-Xing Lv ◽  
Fei Lin ◽  
Zhi-Bin Ke ◽  
Yun-Zhi Lin ◽  
Peng-Fei Zhuang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Cancer Patients ◽  
Mirna Expression ◽  
Prognostic Model ◽  
Cox Regression ◽  
Expression Profiles ◽  
Univariate Analysis ◽  
Test Group ◽  
Differential Analysis ◽  
Mirna Signature

Abstract Background The differential expression of miRNAs has played a significant role in bladder tumors. The aim of our study was to screen new biomarkers . Methods Through differential analysis of bladder cancer mRNA and miRNA expression data in the TCGA, differential genes and miRNAs were screened. Furthermore, Cox univariate analysis and multifactor analysis were used to establish a prognostic prediction model . The predictive ability of the prognostic model was then verified on the patient. The action mechanism of these miRNAs was analyzed.Results By the differential analysis and standardization of miRNA expression profiles. Differentially expressed miRNAs were screened, then all the patients were then randomly divided into train group and the test group. 23 miRNAs were revealed , then a Seven-miRNA signature prognostic biomarkers was constituting.Univariate cox regression and multivariate cox regression considering other clinical factors displayed that the seven-miRNA signature could serve as an independent prognostic factor.Target genes of these seven miRNAs were analyzed by KEGG signaling pathway and GO enrichment analysis. . Conclusion The prognostic model constructed by seven miRNAs has possessed certain degree of sensitivity and specificity for the prediction of the survival of bladder cancer patients, which can be used as a potential new clinical marker for bladder cancer patients.

Mortality within 30 days of immunotherapy (checkpoint inhibitors) in metastatic cancer patients treated at Australian tertiary cancer center.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 6600-6600
Author(s):  
Hiren A. Mandaliya ◽  
Sang Kim ◽  
Gaik Tin Quah ◽  
Sandy Tun Min ◽  
James Carlton ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Advanced Cancer ◽  
Checkpoint Inhibitors ◽  
Metastatic Cancer ◽  
Univariate Analysis ◽  
Cell Cancer ◽  
Small Sample ◽  
Cancer Center ◽  
Published Data ◽  
Cancer Type

6600 Background: Cancer treatment has evolved rapidly since the advent of immunotherapy (checkpoint inhibitors). As compared to chemotherapy, immunotherapy is associated with a more favourable but distinct side effect profile. Mortality within 30 days of chemotherapy in cancer patients has been accepted as a clinical indicator of preventable harm and used as an auditing tool for clinical practice and improving quality of life. This should be investigated in the current era of immunotherapy, as it has been the standard treatment for advanced melanoma, lung cancer, renal cell cancer and others. Methods: We conducted a retrospective study on patients with advanced cancer treated with immunotherapy and died within 30 days of treatment. Clinical data on patients treated with immunotherapy at Calvary Mater Newcastle between 2006 and 2018 was collected. Data were compared with 30-day mortality statistics of chemotherapy. Results: A total of 601 metastatic cancer patients received immunotherapy agents (Pembrolizumab, Nivolumab, Ipilimumab, Atezolizumab, Tislelizumab and MSB0011359C) on 5022 occasions. Seventy-six (12.6%) patients died within 30 days of receiving immunotherapy. Median age was 68 years (35-90). Melanoma was the most prevalent cancer type (63%) followed by lung (20%). Forty-seven (47%) of patients received immunotherapy as first-line treatment and 39% as second-line. Patients died within 30 days received an average 2 (1-16) immunotherapy doses. A quarter of patients had ECOG 3 and ECOG 4 before last dose. Majority of deaths were related to disease (86%). Nearly 80% of patients died in hospital. One patient died due to treatment-related pneumonitis. In univariate analysis, there was no association between mortality and patients’ demographic variables such as age, sex, BMI, cancer type, ECOG performance status, immunotherapy agent and prior treatment. Conclusions: To our knowledge, this is the first ever real-world data on 30-day mortality after immunotherapy in advanced cancer. Thirty-day mortality rates were comparable to published data on patients treated with chemotherapy. Results emphasise significance of careful selection of advanced cancer patient for immunotherapy. Due to small sample size, the power to detect a significant association between patients demographics and survival is reduced.

CD8A and HAPLN3 expression profiling to reveal an immunologic subtype of bladder cancer with favorable survival.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15193-e15193
Author(s):  
Jingjiao Ma ◽  
Ning He ◽  
Jianfei Wang ◽  
Lingyu Wang ◽  
Ge Jin ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Immune Checkpoint ◽  
Checkpoint Inhibitors ◽  
Pearson Correlation ◽  
Disease Free Survival ◽  
Correlation Coefficients ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Specific Gene ◽  
Checkpoint Genes

e15193 Background: At present, immune checkpoint inhibitors (ICI) have demonstrated robust anti-tumor activity with a favorable safety in bladder cancer (BLCA). However, less than half of BLCA patients respond to immunotherapy. We aimed to further delineate the immunologic subtype of BLCA to pick patients who might benefit from ICI treatment. Methods: The RNA-seq and clinical data were collected from The Cancer Genome Atlas (TCGA) data portal (n = 408) and Gene Expression Omnibus (GEO) (GSE48075, n = 142; GSE32894, n = 308). TCGA and GSE48075 cohort are the discovery datasets, and GSE32894 cohort is used for validation. According to the expression of every specific gene ( Gi), patients were divided into two groups using median FPKM as cutpoint value, namely Gi_high and Gi_low, respectively. Combined with CD8A expression, all the patients were divided to four groups as follows: CD8A_high/ Gi_high, CD8A_high/ Gi_low, CD8A_low/ Gi_high, and CD8A_low/ Gi_low. Then we calculated the pearson correlation coefficients between Gi and 13 immune checkpoint genes ( CD274, IDO1, CTLA4, LAG3, CD276, VTCN1, CD70, HAVCR2, CD40, CD47, TNFRSF18, TIGIT, and TNFSF14). Overall or disease free survival of the four groups were compared using the survfit function from the survival R package and P values from log-rank tests were reported. Results: In the discovery cohort, we found CD8A_high/ HAPLN3_low group showed the best overall survival, whereas the CD8A_low/ HAPLN3_high showed the worst (TCGA, p = 0.013; GSE48075, p = 0.012). Additionally, HAPLN3 was positively correlated with 5/13 immune-checkpoint genes: CD274, IDO1, CTLA4, LAG3, HAVCR2 (r > 0.6, p < 0.01). And the same observations were extended in the validation cohort (GSE32894): CD8A_high/ HAPLN3_low group exhibited a favorable survival (p = 0.00059), and HAPLN3 had a strong correlation with the same 5 immune-checkpoint genes (r > 0.6, p < 0.01). Conclusions: The combination of high CD8A and low HAPLN3 expression identified a subtype of BLCA patients with favorable survival and these findings may further help refining the selection of BLCA patients for immunotherapy.

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