Significance of STAT3 in Immune Infiltration and Drug Response in Cancer

Signal transducer and activator of transcription 3 (STAT3) is a transcription factor and regulates tumorigenesis. However, the functions of STAT3 in immune and drug response in cancer remain elusive. Hence, we aim to reveal the impact of STAT3 in immune infiltration and drug response comprehensively by bioinformatics analysis. The expression of STAT3 and its relationship with tumor stage were explored by Tumor Immune Estimation Resource (TIMER), Human Protein Altas (HPA), and UALCAN databases. The correlations between STAT3 and immune infiltration, gene markers of immune cells were analyzed by TIMER. Moreover, the association between STAT3 and drug response was evaluated by the Cancer Cell Line Encyclopedia (CCLE) and Cancer Therapeutics Response Portal (CTRP). The results suggested that the mRNA transcriptional level of STAT3 was lower in tumors than normal tissues and mostly unrelated to tumor stage. Besides, the protein expression of STAT3 decreased in colorectal and renal cancer compared with normal tissues. Importantly, STAT3 was correlated with immune infiltration and particularly regulated tumor-associated macrophage (TAM), M2 macrophage, T-helper 1 (Th1), follicular helper T (Treg), and exhausted T-cells. Remarkably, STAT3 was closely correlated with the response to specified inhibitors and natural compounds in cancer. Furthermore, the association between STAT3 and drug response was highly cell line type dependent. Significantly, the study provides thorough insight that STAT3 is associated with immunosuppression, as well as drug response in clinical treatment.

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CDCA3 Is a Novel Prognostic Biomarker Associated with Immune Infiltration in Hepatocellular Carcinoma

BioMed Research International ◽

10.1155/2021/6622437 ◽

2021 ◽

Vol 2021 ◽

pp. 1-19

Author(s):

Zhihuai Wang ◽

Shuai Chen ◽

Gaochao Wang ◽

Sun Li ◽

Xihu Qin

Keyword(s):

Hepatocellular Carcinoma ◽

T Cells ◽

Immune Cell ◽

Disease Free Survival ◽

In Silico Analysis ◽

Gene Markers ◽

Free Survival ◽

Immune Infiltration ◽

Normal Tissues ◽

Tumor Tissues

Cell division cycle-associated protein-3 (CDCA3) contributes to the regulation of the cell cycle. CDCA3 plays an important role in the carcinogenesis of various cancers; however, the association between CDCA3 expression, prognosis of patients, and immune infiltration in the tumor microenvironment is still unknown. Here, we demonstrated that CDCA3 was differentially expressed between the tumor tissues and corresponding normal tissues using in silico analysis in the ONCOMINE and Tumor Immune Estimation Resource (TIMER) databases. We analyzed the relationship between the expression of CDCA3 and prognosis of patients with hepatocellular carcinoma (HCC) using the Kaplan–Meier plotter database and Gene Expression Profiling Interactive Analysis (GEPIA). Furthermore, we determined the prognostic value of CDCA3 expression using univariate and multivariate analyses. We observed that CDCA3 expression closely correlated with immune infiltration and gene markers of infiltrating immune cells in the TIMER database. CDCA3 was highly expressed in the tumor tissues than in the adjacent normal tissues in various cancers, including HCC. Increased expression of CDCA3 was accompanied by poorer overall survival (OS), relapse-free survival (RFS), progression-free survival (PFS), and disease-specific survival (DSS). The correlation between CDCA3 expression and OS and disease-free survival (DFS) was also studied using GEPIA. CDCA3 expression was associated with the levels of immune cell infiltration and was positively correlated with tumor purity. Moreover, CDCA3 expression was associated with gene markers such as PD-1, CTLA4, LAG3, and TIM-3 from exhausted T cells, CD3D, CD3E, and CD2 from T cells, and TGFB1 and CCR8 located on the surface of Tregs. Thus, we demonstrated that CDCA3 may be a potential target and biomarker for the management and diagnosis of HCC.

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Cloning of the complete gene for carcinoembryonic antigen: analysis of its promoter indicates a region conveying cell type-specific expression

Molecular and Cellular Biology ◽

10.1128/mcb.10.6.2738-2748.1990 ◽

1990 ◽

Vol 10 (6) ◽

pp. 2738-2748

Author(s):

H Schrewe ◽

J Thompson ◽

M Bona ◽

L J Hefta ◽

A Maruya ◽

...

Keyword(s):

Carcinoembryonic Antigen ◽

Cell Line ◽

Transcriptional Level ◽

Cell Type ◽

Coding Region ◽

Specific Expression ◽

Normal Tissues ◽

Cell Type Specific Expression ◽

Cell Type Specific ◽

Cea Gene

Carcinoembryonic antigen (CEA) is a widely used tumor marker, especially in the surveillance of colonic cancer patients. Although CEA is also present in some normal tissues, it is apparently expressed at higher levels in tumorous tissues than in corresponding normal tissues. As a first step toward analyzing the regulation of expression of CEA at the transcriptional level, we have isolated and characterized a cosmid clone (cosCEA1), which contains the entire coding region of the CEA gene. A close correlation exists between the exon and deduced immunoglobulin-like domain borders. We have determined a cluster of transcriptional starts for CEA and the closely related nonspecific cross-reacting antigen (NCA) gene and have sequenced their putative promoters. Regions of sequence homology are found as far as approximately 500 nucleotides upstream from the translational starts of these genes, but farther upstream they diverge completely. In both cases we were unable to find classic TATA or CAAT boxes at their expected positions. To characterize the CEA and NCA promoters, we carried out transient transfection assays with promoter-indicator gene constructs in the CEA-producing adenocarcinoma cell line SW403, as well as in nonproducing HeLa cells. A CEA gene promoter construct, containing approximately 400 nucleotides upstream from the translational start, showed nine times higher activity in the SW403 than in the HeLa cell line. This indicates that cis-acting sequences which convey cell type-specific expression of the CEA gene are contained within this region.

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Integrated Analysis of the Expression, Prognostic Value, and Relationship with Immune Infiltration of CMTMs in Human Hepatocellular Carcinoma

10.21203/rs.3.rs-891032/v1 ◽

2021 ◽

Author(s):

shitao jiang ◽

Junwei Zhang ◽

Yaoge Liu ◽

Ting Zhang ◽

Lei Zhang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Prognostic Value ◽

Transmembrane Domain ◽

Bioinformatic Analysis ◽

Tumor Stage ◽

Integrated Analysis ◽

Immune Infiltration ◽

Normal Tissues ◽

Precision Therapy ◽

High Level

Abstract The chemokine-like factor (CKLF)-like MARVEL transmembrane domain-containing (CMTM) family refers to an updated gene family involved in diverse pathophysiological processes. However, the effect exerted by CMTM family members (CMTMs) in hepatocellular carcinoma (HCC) is still elusive. Herein, to elucidate the expression, prognostic value, and immune roles of CMTMs in HCC, a comprehensive bioinformatic analysis was carried out. Our findings showed that CKLF, CMTM1, CMTM3-4, and CMTM7-8 displayed higher mRNA expression levels in HCC tissues than in normal tissues, yet CMTM2, CMTM5, and CMTM6 were lower in HCC tissues. The levels of CMTM1, CMTM2, and CMTM4 were related to tumor stage. Survival analysis showed that high levels of CKLF, CMTM1, CMTM4, and CMTM6-7 were associated with shorter overall survival (OS). Conversely, a high level of CMTM5 in HCC patients was associated with improved OS. We also found that CKLF, CMTM1-4, and CMTM6-7 were closely correlated with immune infiltration in the HCC microenvironment. In conclusion, this study indicates that CMTMs exert a crucial effect on HCC microenvironment remodeling. CKLF, CMTM1, CMTM4, and CMTM6-7 are potential targets of precision therapy, and CMTM5 is a tumor-suppressive gene that was associated with improved survival in HCC patients.

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A Pan-cancer Analysis Reveals the Abnormal Expression and Drug Sensitivity of CSF1

Anti-Cancer Agents in Medicinal Chemistry ◽

10.2174/1871520621666210608105357 ◽

2021 ◽

Vol 21 ◽

Author(s):

Xiaoshuo Dai ◽

Xinhuan Chen ◽

Wei Chen ◽

Yihuan Chen ◽

Jun Zhao ◽

...

Keyword(s):

Dna Methylation ◽

Tumor Progression ◽

Drug Sensitivity ◽

Tumor Stage ◽

Response Analysis ◽

Immune Infiltration ◽

Normal Tissues ◽

Abnormal Expression ◽

Promoter Dna ◽

Pan Cancer

Background: Colony-stimulating factor-1 (CSF1) is a cytokine that is closely related to normal organ growth and development as well as tumor progression. Objective: We aimed to summarize and clarify the reasons for the abnormal expression of CSF1 in tumors and explore the role of CSF1 in tumor progression. Furthermore, drug response analysis may provide a reference for clinical medication. Methods: The expression of CSF1 was analyzed by TCGA and CCLE. Besides, cBioPortal and MethSurv databases were used to conduct mutation and DNA methylation analyses. Further, correlations between CSF1 expression and tumor stage, survival, immune infiltration, drug sensitivity and enrichment analyses were validated via UALCAN, Kaplan-Meier plotter, TIMER, CTRP and Coexperia databases. Results: CSF1 is expressed in a variety of tissues, meaningfully, it can be detected in blood. Compared with normal tissues, CSF1 expression was significantly decreased in most tumors. The missense mutation and DNA methylation of CSF1 may cause the downregulated expression. Moreover, decreased CSF1 expression was related with higher tumor stage and worse survival. Further, the promoter DNA methylation level of CSF1 was prognostically significant in most tumors. Besides, CSF1 was closely related to immune infiltration, especially macrophages. Importantly, CSF1 expression was associated with a good response to VEGFRs inhibitors, which may be due to the possible involvement of CSF1 in tumor angiogenesis and metastasis processes. Conclusion: The abnormal expression of CSF1 could serve as a promising biomarker of tumor progression and prognosis in pan-cancer. Significantly, angiogenesis and metastasis inhibitors may show a good response to CSF1-related tumors.

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The evolving role of cancer cell line-based screens to define the impact of cancer genomes on drug response

Current Opinion in Genetics & Development ◽

10.1016/j.gde.2013.12.002 ◽

2014 ◽

Vol 24 ◽

pp. 114-119 ◽

Cited By ~ 20

Author(s):

Mathew J Garnett ◽

Ultan McDermott

Keyword(s):

Cell Line ◽

Cancer Cell ◽

Drug Response ◽

Cancer Cell Line ◽

Cancer Genomes ◽

The Impact

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FCGR1A Serves as a Novel Biomarker and Correlates With Immune Infiltration in Four Cancer Types

10.21203/rs.3.rs-38062/v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Jili Xu ◽

Yong Guo

Keyword(s):

Overall Survival ◽

T Cell ◽

Differential Expression Analysis ◽

Renal Clear Cell Carcinoma ◽

High Expression ◽

Immune Gene ◽

Gene Markers ◽

Immune Infiltration ◽

Normal Tissues ◽

Cancer Types

Abstract Background: FCGR1A encodes a protein that plays an important role in the immune response. The prognosis and tumor immune infiltration of FCGR1A in heterogeneous tumors remains unclear.Methods: Differential expression analysis of FCGR1A between tumor and normal tissues and the difference in overall survival (OS) among different cancer types were performed by Gene Expression Profiling Interactive Analysis (GEPIA). The correlation between FCGR1A and cancer immune infiltration or immue gene markers was completed through Tumor Immune Estimation Resource (TIMER) site. Results: FCGR1A exhibited high expression in various cancer types. FCGR1A was significantly correlated with the overall survival (OS) of cervical and endocervical cancer (CESC), cholangiocarcinoma (CHOL), kidney renal clear cell carcinoma (KIRC) and skin cutaneous melanoma (SKCM) (P<.05). High expression of FCGR1A meant a better prognosis except for KIRC. FCGR1A showed significant differences at different stages of KIRC and SKCM (P<.05). Furthermore, FCGR1A was notably associated with immune infiltrating levels of CD4+ T cell, CD8+ T cell, B cell, macrophage, neutrophil, and dendritic cell in the four cancers (P<.05). FCGR1A also showed close relevance with different immune gene markers. The copy number variation (CNV) of FCGR1A significantly influenced the abundance of immune infiltration in KIRC and SKCM. Conclusion: FCGR1A may be a potential prognostic biomarker and related to immune infiltration levels in diverse cancers, especially in CESC, CHOL, KIRC, and SKCM. Besides, FCGR1A may be involved in the activation, regulation or induction of immune cells.

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Cloning of the complete gene for carcinoembryonic antigen: analysis of its promoter indicates a region conveying cell type-specific expression.

Molecular and Cellular Biology ◽

10.1128/mcb.10.6.2738 ◽

1990 ◽

Vol 10 (6) ◽

pp. 2738-2748 ◽

Cited By ~ 108

Author(s):

H Schrewe ◽

J Thompson ◽

M Bona ◽

L J Hefta ◽

A Maruya ◽

...

Keyword(s):

Carcinoembryonic Antigen ◽

Cell Line ◽

Transcriptional Level ◽

Cell Type ◽

Coding Region ◽

Specific Expression ◽

Normal Tissues ◽

Cell Type Specific Expression ◽

Cell Type Specific ◽

Cea Gene

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CTHRC1 Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Kidney Renal Papillary Cell Carcinoma and Kidney Renal Clear Cell Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2020.570819 ◽

2021 ◽

Vol 10 ◽

Author(s):

Fenfang Zhou ◽

Dexin Shen ◽

Yaoyi Xiong ◽

Songtao Cheng ◽

Huimin Xu ◽

...

Keyword(s):

Cell Carcinoma ◽

Immune Cells ◽

Clear Cell ◽

Clear Cell Carcinoma ◽

Renal Clear Cell Carcinoma ◽

Extracellular Matrix Protein ◽

Gene Markers ◽

Clinical Prognosis ◽

Immune Infiltration ◽

Normal Tissues

Kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP) are the most common RCC types. RCC has high immune infiltration levels, and immunotherapy is currently one of the most promising treatments for RCC. Collagen triple helix repeat containing 1 (CTHRC1) is an extracellular matrix protein that regulates tumor invasion and modulates the tumor microenvironment. However, the association of CTHRC1 with the prognosis and tumor-infiltrating lymphocytes of KIRP and KIRC has not been reported. We examined the CTHRC1 expression differences in multiple tumor tissues and normal tissues via exploring TIMER, Oncomine, and UALCAN databases. Then, we searched the Kaplan-Meier plotter database to evaluate the correlation of CTHRC1 mRNA level with clinical outcomes. Subsequently, the TIMER platform and TISIDB website were chosen to assess the correlation of CTHRC1 with tumor immune cell infiltration level. We further explored the causes of aberrant CTHRC1 expression in tumorigenesis. We found that CTHRC1 level was significantly elevated in KIRP and KIRC tissues relative to normal tissues. CTHRC1 expression associates with tumor stage, histology, lymph node metastasis, and poor clinical prognosis in KIRP. The CTHRC1 level correlates to tumor grade, stage, nodal metastasis, and worse survival prognosis. Additionally, CTHRC1 is positively related to different tumor-infiltrating immune cells in KIRP and KIRC. Moreover, CTHRC1 was closely correlated with the gene markers of diverse immune cells. Also, high CTHRC1 expression predicted a worse prognosis in KIRP and KIRC based on immune cells. Copy number variations (CNV) and DNA methylation might contribute to the abnormal upregulation of CTHRC1 in KIRP and KIRC. In conclusion, CTHRC1 can serve as a biomarker to predict the prognosis and immune infiltration in KIRP and KIRC.

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Karyotypic divergence confounds cellular phenotypes in large pharmacogenomic studies

10.1101/574350 ◽

2019 ◽

Author(s):

Rene Quevedo ◽

Nehme El-Hachem ◽

Petr Smirnov ◽

Zhaleh Safikhani ◽

Trevor J. Pugh ◽

...

Keyword(s):

Cell Line ◽

Cell Lines ◽

Copy Number ◽

Drug Response ◽

Drug Sensitivity ◽

Genomic Diversity ◽

Sensitivity Data ◽

Cellular Phenotypes ◽

The Impact ◽

Pharmacogenomic Studies

ABSTRACTBackgroundSomatic copy-number alterations that affect large genomic regions are a major source of genomic diversity in cancer and can impact cellular phenotypes. Clonal heterogeneity within cancer cell lines can affect phenotypic presentation, including drug response.MethodsWe aggregated and analyzed SNP and copy number profiles from six pharmacogenomic datasets encompassing 1,691 cell lines screened for 13 molecules. To look for sources of genotype and karyotype discordances, we compared SNP genotypes and segmental copy-ratios across 5 kb genomic bins. To assess the impact of genomic discordances on pharmacogenomic studies, we assessed gene expression and drug sensitivity data for compared discordant and concordant lines.ResultsWe found 6/1,378 (0.4%) cell lines profiled in two studies to be discordant in both genotypic and karyotypic identity, 51 (3.7%) discordant in genotype, 97 (7.0%) discordant in karyotype, and 125 (9.1%) potential misidentifications. We highlight cell lines REH, NCI-H23 and PSN1 as having drug response discordances that may hinge on divergent copy-number qConclusionsOur study highlights the low level of misidentification as evidence of effective cell line authentication standards in recent pharmacogenomic studies. However, the proclivity of cell lines to acquire somatic copy-number variants can alter the cellular phenotype, resulting in a biological and predictable effects on drug sensitivity. These findings highlight the need for verification of cell line copy number profiles to inform interpretation of drug sensitivity data in biomedical studies.

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Deep generative neural network for accurate drug response imputation

Nature Communications ◽

10.1038/s41467-021-21997-5 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Peilin Jia ◽

Ruifeng Hu ◽

Guangsheng Pei ◽

Yulin Dai ◽

Yin-Ying Wang ◽

...

Keyword(s):

Tumor Microenvironment ◽

Cell Line ◽

Drug Response ◽

Dimensional Space ◽

The Cancer Genome Atlas ◽

Data Sets ◽

Variational Autoencoder ◽

Cancer Genome Atlas ◽

Low Dimensional ◽

The Impact

AbstractDrug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outcome. In this study, we develop a deep variational autoencoder (VAE) model to compress thousands of genes into latent vectors in a low-dimensional space. We then demonstrate that these encoded vectors could accurately impute drug response, outperform standard signature-gene based approaches, and appropriately control the overfitting problem. We apply rigorous quality assessment and validation, including assessing the impact of cell line lineage, cross-validation, cross-panel evaluation, and application in independent clinical data sets, to warrant the accuracy of the imputed drug response in both cell lines and cancer samples. Specifically, the expression-regulated component (EReX) of the observed drug response achieves high correlation across panels. Using the well-trained models, we impute drug response of The Cancer Genome Atlas data and investigate the features and signatures associated with the imputed drug response, including cell line origins, somatic mutations and tumor mutation burdens, tumor microenvironment, and confounding factors. In summary, our deep learning method and the results are useful for the study of signatures and markers of drug response.

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