更新于：2024-11-01

CNKSR1

更新于：2024-11-01

基本信息

别名

CNK、CNK homolog protein 1、CNK1

+ [6]

简介

May function as an adapter protein or regulator of Ras signaling pathways.

关联

项与 CNKSR1 相关的药物

PHT-7.3

靶点

CNKSR1

作用机制

CNKSR1 inhibitors

在研机构

Phusis Therapeutics, Inc.

原研机构

Phusis Therapeutics, Inc.

在研适应症

肿瘤

非在研适应症-

最高研发阶段临床前

首次获批国家/地区-

首次获批日期1800-01-20

100 项与 CNKSR1 相关的临床结果

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100 项与 CNKSR1 相关的转化医学

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0 项与 CNKSR1 相关的专利（医药）

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项与 CNKSR1 相关的文献（医药）

2024-04-01·Heliyon

Identification of CNKSR1 as a biomarker for “cold” tumor microenvironment in lung adenocarcinoma: An integrative analysis based on a novel workflow

Article

作者: Peng, Mou ; Cai, Qidong

BackgroundTherapies targeting PD1/PD-L1 pathway have revolutionized the treatment of lung cancer. However, anti-PD1/PD-L1 therapies have proven beneficial for only a select group of lung adenocarcinoma (LUAD) patients and generally do not work for immuno-cold tumors characterized by a lack of immune cell infiltration. Identifying novel biomarkers is vital to broad therapeutic options for LUAD patients with no response to anti-PD1/PD-L1 immunotherapies.MethodsOur study has developed a novel strategy to identify a promising biomarker that addresses the limitations of anti-PD1/PD-L1 immunotherapy in treating immunological cold tumors. We exacted LUAD RNA-seq data from the Cancer Genome Atlas database (TCGA). Using several machine learning methods, we identified the candidate biomarker. Based on the expression level of PD-L1 and the identified biomarker, samples were categorized into four groups. We further used ESTIMATE, ssGSEA, and CIBERSORT algorithms to calculate the immune infiltration level of each group. The results were validated in three independent bulk datasets and one scRNA-seq dataset. Immunohistochemistry (IHC) assessments were performed in clinical samples to further evaluate the coexpression of CNKSR1 and PD-L1, and to compare CD8 + T cell infiltration among groups.ResultsAfter comprehensive analyses, CNKSR1 was identified as a novel promising biomarker for immuno-cold LUAD. CNKSR1 mRNA expression levels exhibited a negative correlation with both PD-L1 mRNA expression and the extent of immune cell infiltration in LUAD. Besides, in contrast to the significant association between the expression of PD-L1 and the majority of other well-established or widely studied immune checkpoint molecules, a mutually exclusive expression pattern is observed between CNKSR1 and these molecules. The aforementioned results were consistent in validation datasets. The prognostic model built based on the CNKSR1 coexpression module also showed robust predictive performance. Additionally, IHC assessments have confirmed that the coexpression of CNKSR1 and PD-L1 is rare in LUAD samples. Notably, LUADs in the high-CNKSR1 group, characterized by high CNKSR1 but low PD- L1 expression, demonstrated reduced infiltration of CD8⁺ T cells.ConclusionsIn summary, CNKSR1 emerges as a promising biomarker for immune-cold LUADs, and the study into CNKSR1 modulating T-cell infiltration may lead to the identification of compensatory molecules to enhance the effectiveness of current immunotherapy for LUAD.

2024-01-01·microPublication biology

G.3.2 is a novel allele of the gene connector enhancer of ksr ( cnk ) in Drosophila melanogaster.

Article

作者: Newman, Emily R ; Adkins, Delia L ; Heininger, Lauren E ; Kochensparger, Sydney K ; Foor, Hannah J ; Rotem, Adam ; Beier, Elise L ; Sobh, Farah A ; Khan, Zayd ; Echeverry, Isabel L ; Gullapalli, Anika S ; Jeon, Yeowon ; Bolyard, Madison M ; Koria, Fadi J ; Shockney, Elizabeth ; Saho, Reese J ; Kagey, Jacob D ; Tollkuci, Antonia ; Al-Olimat, Aleece K ; Siders, Jamie L ; El Dana, Haya ; Hoeft, Emma G ; Jordan, Laine P ; Hakim, Sandro S ; Thackeray, Justin R ; Lilly, Veronica ; Brain, Olivia E ; Clum, Tyler R ; Mariano, Mikayla G ; Speiser, Isabelle F ; Altopp, Beatrice M ; Benton, Lane ; Selders, Ashley N ; MacCormack, Ian T ; Belisle, B Shafer ; Cruz, Autumn M ; DeGray, Meghan V ; Mentzer, Audrey C ; Vapenik, Megan A ; Chowdhury, Shria Roy ; Cleary, Liam ; Cifranic, Jennifer R ; Chammout, Hanadi ; Wagner, Erin M ; Sawaki, Kaname ; Bieser, Kayla L ; Krasnow, Ruby M ; Lim, Eileen ; Falke, Luke R ; Buckner, Eldon T ; Elkadri, Sarah K ; Myers, Katlyn C ; Amer, Tuqa ; Hazime, Hussein B ; James, Lauren M ; Trevino, Cassandra C ; Malesh, Andriy ; Bazzi, Isaac I ; Sproul, Breanna M ; Avery, Gwendolyn R ; Alsaad, Zeinab ; Sroufe, Veronica J ; Johnson, Megan R ; Beck, Emilia D ; Apampa, Feyi O ; Messner, Katelyn H ; Romero, Liliana ; Estep, Paige L ; Richters, Annie M

Genetic screens in Drosophila melanogaster have long been used to identify genes found in a variety of developmental, cellular, and behavioral processes. Here we describe the characterization and mapping of a mutation identified in a conditional screen for genetic regulators of cell growth and cell division. Within a Flp/FRT system, mutant G.3.2 results in a reduction of mutant tissue and a rough eye phenotype. We find that G.3.2 maps to the gene cnk , providing further support that cnk is a critical gene in Drosophila eye development. This mutant was characterized, mapped and sequenced by undergraduate students within the Fly-CURE consortium.

2023-08-01·Medical Microbiology and Immunology

Gene biomarkers and classifiers for various subtypes of HTLV-1-caused ATLL cancer identified by a combination of differential gene co‑expression and support vector machine algorithms

Article

作者: Afsaneh, Elaheh ; Emamzadeh, Rahman ; Zarei Ghobadi, Mohadeseh

Adult T-cell leukemia/lymphoma (ATLL) is pathogen-caused cancer that is progressed after the infection by human T-cell leukemia virus type 1. Four significant subtypes comprising acute, lymphoma, chronic, and smoldering have been identified for this cancer. However, there are no trustworthy prognostic biomarkers for these subtypes. We utilized a combination of two powerful network-based and machine-learning algorithms including differential co-expressed genes (DiffCoEx) and support vector machine-recursive feature elimination with cross-validation (SVM-RFECV) methods to categorize disparate ATLL subtypes from asymptomatic carriers (ACs). The results disclosed the significant involvement of CBX6, CNKSR1, and MAX in chronic, MYH10 and P2RY1 in acute, C22orf46 and HNRNPA0 in smoldering subtypes. These genes also can classify each ATLL subtype from AC carriers. The integration of the results of two powerful algorithms led to the identification of reliable gene classifiers and biomarkers for diverse ATLL subtypes.