The Tumor Microenvironment: Focus on Extracellular Matrix

Rigoglio, Nathia Nathaly; Rabêlo, Ana Carolina Silveira; Borghesi, Jéssica; Matias, Gustavo de Sá Schiavo; Fratini, Paula; Prazeres, Pedro H. D. M.; Pimentel, Concepta Margaret McManus; Birbrair, Alexander; Miglino, María Angélica

doi:10.1007/978-3-030-40146-7_1

Cited by 15 publications

(10 citation statements)

References 443 publications

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“…For the first time, we used multiple online databases to comprehensively investigate the expression levels of the LOX family genes in KIRC at the levels of tumor tissue mRNA, tumor tissue protein and RCC cell lines mRNA, and further explored their significance on prognosis and molecular mechanism in KIRC. LOX family genes have been shown to play key roles in the formation and remodeling of ECM, which could affect biological processes such as cell differentiation, proliferation, adhesion, morphogenesis and phenotypic expression 31,32 . Finally, we found that LOX and LOXL2 were significantly upregulated and predicted poor survival in KIRC.…”

Section: Discussionmentioning

confidence: 59%

“…LOX family genes have been shown to play key roles in the formation and remodeling of ECM, which could affect biological processes such as cell differentiation, proliferation, adhesion, morphogenesis and phenotypic expression. 31,32 Finally, we found that LOX and LOXL2 were significantly upregulated and predicted poor survival in KIRC. Furthermore, enrichment analyses of LOX, LOXL2 and their co-expressed genes revealed that they were closely correlated with extracellular matrix, extracellular space and ECM structuration.…”

Section: Discussionmentioning

confidence: 67%

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Comprehensive analysis on the expression levels and prognostic values of LOX family genes in kidney renal clear cell carcinoma

Lin

Zheng

et al. 2020

Cancer Medicine

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Section: Discussionmentioning

confidence: 59%

Section: Discussionmentioning

confidence: 67%

Comprehensive analysis on the expression levels and prognostic values of LOX family genes in kidney renal clear cell carcinoma

Lin

Zheng

et al. 2020

Cancer Medicine

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“…It usually defines transitional events in metastasis and tumor progression. 62 The identified 41 features from HNSC data by SPLSN, including some have been verified by researchers, including CXCR1, CXCR4, and FGFR1. CXCR1 was expressed in the vast majority of the cell lines, and plays an important role in HNSC progression.…”

Section: Biological Analysis For the Genes Selected By Splsn In Neck And Head Squamous Cell Carcinoma Datamentioning

confidence: 70%

SPLSN: An efficient tool for survival analysis and biomarker selection

2021

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In genome research, it is a fundamental issue to identify few but important survival-related biomarkers. The Cox model is a widely used survival analysis technique, which is used to study the relationship between characteristics and survival response. However, limitations of the existing Cox methods for genomic data are as follows: (1) a typical gene expression data set consists of tens of thousands of genes, and the result of current methods may not be sparse enough; (2) a wealth of structural information about many biological processes, such as regulatory networks and pathways, has often been ignored; (3) genomic data is usually considered as high noise, which is usually ignored in current methods. To alleviate the above problems, in this paper, we study a novel sparse Cox regression model, called SPLSN, which combines self-paced learning (SPL) and a log-sum absolute network-based penalty (Logsum-Net), especially for biomarker selection in survival analysis. SPL is embedded in curriculum design, and the model is trained by gradually increasing samples from low noise to high noise during the training process. The Logsum-Net encourages smoothness among the coefficients of adjacent genes on a specific biological network. We compare the proposed method with five alternative approaches in various experimental scenarios, including a comprehensive simulation, seven benchmark gene expression data sets, and one large validation data set. Results show that the SPLSN can identify fewer meaningful biomarkers and obtain the best or equivalent prediction performance. Moreover, the biological analysis shows that the genes selected by the SPLSN might be helpful to tumor treatment.

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“…Compelling evidence support that tumor-associated ECM remodeling and stiffening, are key elements behind the TME of highly invasive phenotypes of several neoplastic cells[ 77 - 79 ]. Strikingly, tumor-associated ECM remodeling and the subsequent stiffening play a critical role in the behavior of cancer cells in the TME[ 80 ], and thus, supporting cancer cell survival, progression, and metastatic invasion[ 81 ].…”

Section: The Contribution Of Dm In Remodeling the Tme In Gcmentioning

confidence: 99%

Diabetes mellitus contribution to the remodeling of the tumor microenvironment in gastric cancer

Rojas¹,

Lindner²,

Schneider³

et al. 2021

WJGO

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Compelling pieces of evidence derived from both clinical and experimental research has demonstrated the crucial contribution of diabetes mellitus (DM) as a risk factor associated with increased cancer incidence and mortality in many human neoplasms, including gastric cancer (GC). DM is considered a systemic inflammatory disease and therefore, this inflammatory status may have profound effects on the tumor microenvironment (TME), particularly by driving many molecular mechanisms to generate a more aggressive TME. DM is an active driver in the modification of the behavior of many cell components of the TME as well as altering the mechanical properties of the extracellular matrix (ECM), leading to an increased ECM stiffening. Additionally, DM can alter many cellular signaling mechanisms and thus favoring tumor growth, invasion, and metastatic potential, as well as key elements in regulating cellular functions and cross-talks, such as the microRNAs network, the production, and cargo of exosomes, the metabolism of cell stroma and resistance to hypoxia. In the present review, we intend to highlight the mechanistic contributions of DM to the remodeling of TME in GC.

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The Tumor Microenvironment: Focus on Extracellular Matrix

Cited by 15 publications

References 443 publications

Comprehensive analysis on the expression levels and prognostic values of LOX family genes in kidney renal clear cell carcinoma

Comprehensive analysis on the expression levels and prognostic values of LOX family genes in kidney renal clear cell carcinoma

SPLSN: An efficient tool for survival analysis and biomarker selection

Diabetes mellitus contribution to the remodeling of the tumor microenvironment in gastric cancer

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