Last update 01 Nov 2024

FAP x TGFBR2

Last update 01 Nov 2024

Basic Info

Related Targets

FAPTGFBR2

Drugs associated with FAP x TGFBR2

Anti-FAP/TGF-PRII bispecific antibody(Merus)

Target

FAP x TGFBR2

Mechanism

FAP antagonists [+1]

Active Org.

Incyte Corp. [+1]

Originator Org.

Incyte Corp. [+1]

Active Indication

Neoplasms

Inactive Indication-

Drug Highest PhasePreclinical

First Approval Ctry. / Loc.-

First Approval Date20 Jan 1800

100 Clinical Results associated with FAP x TGFBR2

100 Translational Medicine associated with FAP x TGFBR2

0 Patents (Medical) associated with FAP x TGFBR2

Literatures (Medical) associated with FAP x TGFBR2

01 Feb 2020·iScience

Comprehensive Proteomic Characterization Reveals Subclass-Specific Molecular Aberrations within Triple-negative Breast Cancer

Article

Author: Boon Huat Bay ; Max Kosok ; Asfa Alli-Shaik ; Jayantha Gunaratne

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer lacking targeted therapies. This is attributed to its high heterogeneity that complicates elucidation of its molecular aberrations. Here, we report identification of specific proteome expression profiles pertaining to two TNBC subclasses, basal A and basal B, through in-depth proteomics analysis of breast cancer cells. We observed that kinases and proteases displayed unique expression patterns within the subclasses. Systematic analyses of protein-protein interaction and co-regulation networks of these kinases and proteases unraveled dysregulated pathways and plausible targets for each TNBC subclass. Among these, we identified kinases AXL, PEAK1, and TGFBR2 and proteases FAP, UCHL1, and MMP2/14 as specific targets for basal B subclass, which represents the more aggressive TNBC cell lines. Our study highlights intricate mechanisms and distinct targets within TNBC and emphasizes that these have to be exploited in a subclass-specific manner rather than a one-for-all TNBC therapy.

01 May 2014·JNCI: Journal of the National Cancer InstituteQ1 · MEDICINE

Risk Prediction for Late-Stage Ovarian Cancer by Meta-analysis of 1525 Patient Samples

Q1 · MEDICINE

Article

Author: Riester, Markus ; Michor, Franziska ; Birrer, Michael J ; Culhane, Aedin C ; Trippa, Lorenzo ; Huttenhower, Curtis ; Wei, Wei ; Parmigiani, Giovanni ; Oliva, Esther ; Waldron, Levi ; Kim, Sung-Hoon

BACKGROUNDOvarian cancer causes more than 15000 deaths per year in the United States. The survival of patients is quite heterogeneous, and accurate prognostic tools would help with the clinical management of these patients.METHODSWe developed and validated two gene expression signatures, the first for predicting survival in advanced-stage, serous ovarian cancer and the second for predicting debulking status. We integrated 13 publicly available datasets totaling 1525 subjects. We trained prediction models using a meta-analysis variation on the compound covariable method, tested models by a "leave-one-dataset-out" procedure, and validated models in additional independent datasets. Selected genes from the debulking signature were validated by immunohistochemistry and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) in two further independent cohorts of 179 and 78 patients, respectively. All statistical tests were two-sided.RESULTSThe survival signature stratified patients into high- and low-risk groups (hazard ratio = 2.19; 95% confidence interval [CI] = 1.84 to 2.61) statistically significantly better than the TCGA signature (P = .04). POSTN, CXCL14, FAP, NUAK1, PTCH1, and TGFBR2 were validated by qRT-PCR (P < .05) and POSTN, CXCL14, and phosphorylated Smad2/3 were validated by immunohistochemistry (P < .001) as independent predictors of debulking status. The sum of immunohistochemistry intensities for these three proteins provided a tool that classified 92.8% of samples correctly in high- and low-risk groups for suboptimal debulking (area under the curve = 0.89; 95% CI = 0.84 to 0.93).CONCLUSIONSOur survival signature provides the most accurate and validated prognostic model for early- and advanced-stage high-grade, serous ovarian cancer. The debulking signature accurately predicts the outcome of cytoreductive surgery, potentially allowing for stratification of patients for primary vs secondary cytoreduction.

01 Feb 2001·Journal of Medical Genetics

Germline mutation analysis of the transforming growth factor beta receptor type II (TGFBR2) and E-cadherin (CDH1) genes in early onset and familial colorectal cancer

Letter

Author: Verma, L ; Maher, E R ; Evans, D G ; Richards, F M ; Porter, T R ; Macdonald, F ; Rajpar, M H

Editor—Genetic factors are clearly implicated in colorectal cancer (CRC) susceptibility, with 10% of all cases having an affected first degree relative and suggestions that up to 20% of all colorectal cancers occur in susceptible people. Identification of the molecular basis for familial adenomatous polyposis (FAP) and hereditary non-polyposis colon cancer syndrome (HNPCC) has provided insights into the mechanisms of colorectal cancer susceptibility and illustrated how somatic mutations in familial cancer genes are frequently implicated in sporadic cancers. FAP has a characteristic phenotype with profuse colorectal polyposis, and although variant attenuated forms of FAP are described, germline APC gene mutations are a rare cause of colorectal cancer. HNPCC is characterised by early onset CRC and, in some kindreds, endometrial, gastric, ovarian, pancreatic, and urinary tract cancers.1 Germline mutations in mismatch repair genes (MMR) such as MSH2 , MLH1 , PMS1 , PMS2 , and MSH6 account for many, but not all, HNPCC kindreds. Most (>90%) HNPCC kindreds with germline MMR mutations have a MSH2 or MLH1 mutation. Germline MMR gene mutations have also been described in isolated early onset colorectal cancer (EOCRC) or familial non-HNPCC CRC.2-4 However, it is estimated that FAP and HNPCC only account for ∼3% of CRC cases and studies of early onset and non-HNPCC familial cases have indicated that most such cases do not have germline MMR gene mutations or evidence of tumour microsatellite instability (MSI) (the hallmark of tumour MMR gene inactivation).2 4-6 Candidate gene approaches to identify further …

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