scholarly journals Analysis of genetic signatures of tumor microenvironment yields insight into mechanisms of resistance to immunotherapy

2020 ◽  
Author(s):  
Ben Wang ◽  
Mengmeng Liu ◽  
Zhujie Ran ◽  
Xin Li ◽  
Jie Li ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Signaling Pathways ◽  
Tumor Patients ◽  
Multiple Tumor ◽  
Ppar Signaling ◽  
Tumor Types ◽  
Genetic Signatures ◽  
Chemotherapy Agents ◽  
Multiple Signaling ◽  
Insight Into

AbstractBackgroundTherapeutic intervention targeting immune cells have led to remarkable improvements in clinical outcomes of tumor patients. However, responses are not universal. The inflamed tumor microenvironment has been reported to correlate with response in tumor patients. However, due to the lack of appropriate experimental methods, the reason why the immunotherapeutic resistance still existed on the inflamed tumor microenvironment remains unclear.Materials and methodsHere, based on integrated single-cell RNA sequencing technology, we classified tumor microenvironment into inflamed immunotherapeutic responsive and inflamed non-responsive. Then, phenotype-specific genes were identified to show mechanistic differences between distant TME phenotypes. Finally, we screened for some potential favorable TME phenotypes transformation drugs to aid current immunotherapy.ResultsMultiple signaling pathways were phenotypes-specific dysregulated. For example, Interleukin signaling pathways including IL-4 and IL-13 were activated in inflamed TME across multiple tumor types. PPAR signaling pathways and multiple epigenetic pathways were respectively inhibited and activated in inflamed immunotherapeutic non-responsive TME, suggesting a potential mechanism of immunotherapeutic resistance and target for therapy. We also identified some genetic markers of inflamed non-responsive or responsive TME, some of which have shown its potentials to enhance the efficacy of current immunotherapy.ConclusionThese results may contribute to the mechanistic understanding of immunotherapeutic resistance and guide rational therapeutic combinations of distant targeted chemotherapy agents with immunotherapy.

scholarly journals CCL2: An Important Mediator Between Tumor Cells and Host Cells in Tumor Microenvironment

2021 ◽  
Vol 11 ◽  
Author(s):  
Jiakang Jin ◽  
Jinti Lin ◽  
Ankai Xu ◽  
Jianan Lou ◽  
Chao Qian ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Cell Types ◽  
Host Cells ◽  
Specific Cell ◽  
Tumor Patients ◽  
Multiple Tumor ◽  
Inflammatory Monocytes ◽  
Immunosuppressive Cell ◽  
Tumor Types

Tumor microenvironment (TME) formation is a major cause of immunosuppression. The TME consists of a considerable number of macrophages and stromal cells that have been identified in multiple tumor types. CCL2 is the strongest chemoattractant involved in macrophage recruitment and a powerful initiator of inflammation. Evidence indicates that CCL2 can attract other host cells in the TME and direct their differentiation in cooperation with other cytokines. Overall, CCL2 has an unfavorable effect on prognosis in tumor patients because of the accumulation of immunosuppressive cell subtypes. However, there is also evidence demonstrating that CCL2 enhances the anti-tumor capability of specific cell types such as inflammatory monocytes and neutrophils. The inflammation state of the tumor seems to have a bi-lateral role in tumor progression. Here, we review works focusing on the interactions between cancer cells and host cells, and on the biological role of CCL2 in these processes.

Evaluation of tumor microenvironment and biomarkers of immune checkpoint inhibitor (ICI) response in metastatic renal cell carcinoma (mRCC).

2019 ◽  
Vol 37 (8_suppl) ◽  
pp. 63-63
Author(s):  
Jason Zhu ◽  
Sarabjot Pabla ◽  
Matthew Labriola ◽  
Rajan T. Gupta ◽  
Shannon McCall ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Standard Of Care ◽  
Reference Population ◽  
Gene Signature ◽  
Multiple Tumor ◽  
Markers Of Inflammation ◽  
Expert Radiologist ◽  
Chi Squared ◽  
Ffpe Tumor ◽  
Tumor Types

63 Background: ICIs are now standard of care for mRCC; however, there are few biomarkers to predict ICI response. Recent data from atezolizumab/bevacizumab trials in mRCC suggest tumors with high Teffhigh/PD-L1+ are more likely to respond to ICI. Here, we use this Teff gene panel as well as other markers of inflammation in the tumor microenvironment to correlate with ICI responses. Methods: This multicenter study evaluated 69 pts with mRCC treated with ICIs. FFPE tumor samples were evaluated by RNA sequencing to measure transcript levels of genes related Teff status. Teff status was defined as the mRNA expression of 17 genes (CD8, CD27, IFNG, GZMA, GZMB, PRF1, EOMES, CXCL9, CXCL10, CXCL11, CD274, CTLA4, FOXP3, TIGIT, IDO1, PSMB9, TAP1), with Teffhigh/low separated at the median. PD-L1 positivity was defined as ≥1% TPS based on Dako 22C3 IHC assay, and TMB high as > 10 mutations per megabase. Inflamed tumors were defined as CD8 expression in the top 75th percentile compared to a large reference population of multiple tumor types. Best responses to ICI was determined by an expert radiologist using RECIST 1.1 criteria. Inflamed tumor status, Teff gene expression, PD-L1 positive, and TMB were associated with disease control (DC, defined as CR, PR, or stable disease). DC comparisons were tested using a chi-squared test with Yates’s continuity correction. Results: DC was 63% (5/8) amongst PD-L1 positive pts and 52% (31/60) in PD-L1 negative patients (p = 0.84). Only 2 pts were TMB high. The majority of mRCC tumors (97%, 67/69) were TMB low. 6-month DC in TMB high tumors was 50% (1/2) and 49.3% (33/67) in TMB low tumors (p = 1.0). 36 pts were classified as Teffhigh and 33 patients were classified as Tefflow. 6-month DC was 61% (22/36) in the Teffhigh cohort and 36% (12/33) in the Tefflow cohort (p = 0.069). 6-month DC was 64% of inflamed tumors (16/25) vs 41% of non-inflamed tumors (18/44) (p = 0.111). Conclusions: TMB high and PD-L1 expression do not reliably predict for DC in pts with mRCC. Utilizing a gene signature score may better predict ICI response.

scholarly journals Targeting Signaling Pathways in Cancer Stem Cells for Cancer Treatment

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Jeffrey Koury ◽  
Li Zhong ◽  
Jijun Hao
Keyword(s):  
Stem Cells ◽  
Cancer Stem Cells ◽  
Cancer Treatment ◽  
Signaling Pathways ◽  
Small Subset ◽  
Self Renewal ◽  
Multiple Tumor ◽  
Notch Pathways ◽  
Tumor Types ◽  
Heterogeneous Tumor

The Wnt, Hedgehog, and Notch pathways are inherent signaling pathways in normal embryogenesis, development, and hemostasis. However, dysfunctions of these pathways are evident in multiple tumor types and malignancies. Specifically, aberrant activation of these pathways is implicated in modulation of cancer stem cells (CSCs), a small subset of cancer cells capable of self-renewal and differentiation into heterogeneous tumor cells. The CSCs are accountable for tumor initiation, growth, and recurrence. In this review, we focus on roles of Wnt, Hedgehog, and Notch pathways in CSCs’ stemness and functions and summarize therapeutic studies targeting these pathways to eliminate CSCs and improve overall cancer treatment outcomes.

An insight into crosstalk among multiple signaling pathways contributing to epileptogenesis

2021 ◽  
Vol 910 ◽  
pp. 174469
Author(s):  
Vipasha Gautam ◽  
Kajal Rawat ◽  
Arushi Sandhu ◽  
Puja Kumari ◽  
Neha Singh ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Multiple Signaling ◽  
Insight Into

scholarly journals Transcriptome Analysis Reveals the Senescence Process Controlling the Flower Opening and Closure Rhythm in the Waterlilies (Nymphaea L.)

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhaoji Li ◽  
Weijuan Zhou ◽  
Peng Wang ◽  
Yanfu Chen ◽  
Shaojie Huo ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Cell Metabolism ◽  
Red Light ◽  
Cell Wall Modification ◽  
Flower Opening ◽  
Metabolism Regulation ◽  
Short Lifespan ◽  
Global Understanding ◽  
Multiple Signaling ◽  
Insight Into

Most waterlily flowers open at dawn and close after noon usually for three to four days, and thereafter wilt. The short lifespan of flowers restricts the development of the flower postharvest industry. The termination of flower movements is a key event during flower aging process. However, it is still unclear when the senescence process initiates and how it terminates the movement rhythm. In this study, we observed that the opening diameter of flowers was the smallest on the fourth (last) flowering day. Subsequent transcriptome profiles generated from petals at different flowering stages showed that the multiple signaling pathways were activated at the last closure stage (Time 3, T3) of the flowers, including Ca2+, reactive oxygen species and far red light signaling pathways, as well as auxin, ethylene and jasmonic acid signaling pathways. Moreover, In terms of cell metabolism regulation, the genes related to hydrolase (protease, phospholipase, nuclease) were upregulated at T3 stage, indicating that petals entered the senescence stage at that time; and the genes related to water transport and cell wall modification were also differentially regulated at T3 stage, which would affect the ability of cell expand and contract, and eventually lead to petal not open after the fourth day. Collectively, our data provided a new insight into the termination of flower opening in the waterlilies, and a global understanding of the senescence process of those opening-closure rhythm flowers.

Evaluation of tumor microenvironment and biomarkers of immune checkpoint inhibitor (ICI) response in metastatic renal cell carcinoma (mRCC).

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 607-607 ◽  
Author(s):  
Jason Zhu ◽  
Sarabjot Pabla ◽  
Matthew Labriola ◽  
Rajan T. Gupta ◽  
Shannon McCall ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Standard Of Care ◽  
Reference Population ◽  
Gene Signature ◽  
Multiple Tumor ◽  
Markers Of Inflammation ◽  
Expert Radiologist ◽  
Chi Squared ◽  
Ffpe Tumor ◽  
Tumor Types

607 Background: ICIs are now standard of care for mRCC; however, there are few biomarkers to predict ICI response. Recent data from atezolizumab/bevacizumab trials in mRCC suggest tumors with high Teffhigh/PD-L1+ are more likely to respond to ICI. Here, we use this Teff gene panel as well as other markers of inflammation in the tumor microenvironment to correlate with ICI responses. Methods: This multicenter study evaluated 69 pts with mRCC treated with ICIs. FFPE tumor samples were evaluated by RNA sequencing to measure transcript levels of genes related Teff status. Teff status was defined as the mRNA expression of 17 genes (CD8, CD27, IFNG, GZMA, GZMB, PRF1, EOMES, CXCL9, CXCL10, CXCL11, CD274, CTLA4, FOXP3, TIGIT, IDO1, PSMB9, TAP1), with Teffhigh/low separated at the median. PD-L1 positivity was defined as ≥1% TPS based on Dako 22C3 IHC assay, and TMB high as > 10 mutations per megabase. Inflamed tumors were defined as CD8 expression in the top 75th percentile compared to a large reference population of multiple tumor types. Best responses to ICI was determined by an expert radiologist using RECIST 1.1 criteria. Inflamed tumor status, Teff gene expression, PD-L1 positive, and TMB were associated with disease control (DC, defined as CR, PR, or stable disease). DC comparisons were tested using a chi-squared test with Yates’s continuity correction. Results: DC was 63% (5/8) amongst PD-L1 positive pts and 52% (31/60) in PD-L1 negative patients (p = 0.84). Only 2 pts were TMB high. The majority of mRCC tumors (97%, 67/69) were TMB low. 6-month DC in TMB high tumors was 50% (1/2) and 49.3% (33/67) in TMB low tumors (p = 1.0). 36 pts were classified as Teffhigh and 33 patients were classified as Tefflow. 6-month DC was 61% (22/36) in the Teffhigh cohort and 36% (12/33) in the Tefflow cohort (p = 0.069). 6-month DC was 64% of inflamed tumors (16/25) vs 41% of non-inflamed tumors (18/44) (p = 0.111). Conclusions: TMB high and PD-L1 expression do not reliably predict for DC in pts with mRCC. Utilizing a gene signature score may better predict ICI response.

scholarly journals Could We Address the Interplay Between CD133, Wnt/β-Catenin, and TERT Signaling Pathways as a Potential Target for Glioblastoma Therapy?

2021 ◽  
Vol 11 ◽  
Author(s):  
Amir Barzegar Behrooz ◽  
Amir Syahir
Keyword(s):  
Stem Cells ◽  
Signaling Pathways ◽  
Tumor Development ◽  
Tumor Formation ◽  
Therapeutic Goals ◽  
Transmembrane Glycoprotein ◽  
Signaling Mechanisms ◽  
Therapeutic Value ◽  
Multiple Signaling ◽  
Insight Into

Glioblastoma multiforme (GBM) is one of the most lethal forms of primary brain tumors. Glioblastoma stem cells (GSCs) play an undeniable role in tumor development by activating multiple signaling pathways such as Wnt/β-catenin and PI3K/AKT/mTOR that facilitate brain tumor formation. CD133, a transmembrane glycoprotein, has been used to classify cancer stem cells (CSCs) in GBM. The therapeutic value of CD133 is a biomarker of the CSC in multiple cancers. It also leads to growth and recurrence of the tumor. More recent findings have confirmed the association of telomerase/TERT with Wnt/β-catenin and the PI3K/AKT/mTOR signaling pathways. Advance studies have shown that crosstalk between CD133, Wnt/β-catenin, and telomerase/TERT can facilitate GBM stemness and lead to therapeutic resistance. Mechanistic insight into signaling mechanisms downstream of surface biomarkers has been revolutionized by facilitating targeting of tumor-specific molecular deregulation. This review also addresses the importance of interplay between CD133, Wnt/β-catenin and TERT signaling pathways in GSCs and outlines the future therapeutic goals for glioblastoma treatment.

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