Regorafenib 40mg tablets
Requires a prescription from a doctor or prescriber
Regorafenib is an orally-administered inhibitor of multiple kinases.
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Stivarga 40mg tablets
WHO defined daily dose (DDD)
120 mg
Not a recommended dose. The DDD is the assumed average maintenance dose per day for a drug used for its main indication in adults. It is a statistical measure used for research and comparison purposes only.
Source: WHO Collaborating Centre for Drug Statistics Methodology, distributed via the NHS dm+d supplementary mapping files (NHSBSA). Contains public sector information licensed under the Open Government Licence v3.0.
Therapeutically similar medicines
Similarity is based on WHO Anatomical Therapeutic Chemical (ATC) classification and on a factual NHS dm+d therapeutic-grouping code prefix. Source data: NHS dm+d via TRUD (OGL v3.0), WHO ATC/DDD Index.
NHS prescribing volume and spending trends
Guidelines from the National Institute for Health and Care Excellence
NICE clinical guidance(14)
Regorafenib for previously treated metastatic colorectal cancer (TA866)
Regorafenib for previously treated advanced hepatocellular carcinoma (TA555)
Regorafenib for previously treated unresectable or metastatic gastrointestinal stromal tumours (TA488)
Regorafenib for metastatic colorectal cancer after treatment for metastatic disease (terminated appraisal) (TA334)
Cabozantinib for previously treated advanced hepatocellular carcinoma (TA849)
Fruquintinib for previously treated metastatic colorectal cancer (TA1079)
Trifluridine–tipiracil with bevacizumab for treating metastatic colorectal cancer after 2 systemic treatments (TA1008)
Ripretinib for treating advanced gastrointestinal stromal tumours after 3 or more kinase inhibitors (TA1146)
Lenvatinib for untreated advanced hepatocellular carcinoma (TA551)
Trifluridine–tipiracil for previously treated metastatic colorectal cancer (TA405)
Selective internal radiation therapies for treating hepatocellular carcinoma (TA688)
Pembrolizumab for previously treated endometrial, biliary, colorectal, gastric or small intestine cancer with high microsatellite instability or mismatch repair deficiency (TA914)
Bevacizumab (originator and biosimilars) with fluoropyrimidine-based chemotherapy for metastatic colorectal cancer (TA1136)
Nivolumab with ipilimumab for previously treated metastatic colorectal cancer with high microsatellite instability or mismatch repair deficiency (TA716)
Source: National Institute for Health and Care Excellence (NICE). Contains public sector information licensed under the Open Government Licence v3.0.
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Codes for healthcare professionals and prescribing systems
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NHS UK identifiers
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SNOMED CT and dm+d codes from NHS TRUD (Technology Reference data Update Distribution), licensed under the Open Government Licence v3.0. ATC codes from the WHO Collaborating Centre for Drug Statistics Methodology (whocc.no).
Active and completed clinical studies from ClinicalTrials.gov
Source: ClinicalTrials.gov, a database of the U.S. National Library of Medicine (NLM), National Institutes of Health (NIH). Data accessed via ClinicalTrials.gov API v2. Trial information is provided for research purposes and does not constitute medical advice.
Academic studies and reviews for this medicine's active substance
Showing the 50 most relevant studies.
Reviews & meta-analyses: 15 · Randomised trials: 5 · 2017–2026
Showing the 50 most relevant studies, sorted by most relevant.
Zhao Li, Jie Wang, Jingbing Zhao, et al.
Oncology Letters, 2024
Yu X, Zan H, Deng W, et al.
2026
BackgroundRegorafenib is a standard second-line therapy for advanced hepatocellular carcinoma (HCC), but its efficacy as a monotherapy is limited. Combining regorafenib with immune checkpoint inhibitors (ICIs) may enhance antitumor activity through synergistic modulation of the tumor microenvironment. This study synthesizes real-world evidence from comparative cohorts by summarizing arm-level efficacy and safety outcomes reported for regorafenib plus ICIs and for regorafenib monotherapy.MethodsA systematic search of PubMed, Embase, The Cochrane Library, and Web of Science was conducted up to January 10, 2026, to identify comparative real-world studies. Outcomes were synthesized primarily at the arm level: ORR was pooled as a single-arm proportion, and mPFS/mOS were summarized using reported medians. Random-effects models and exploratory meta-regression were used to examine differences in pooled arm-level summaries across cohort types rather than within-study head-to-head comparative effect estimates.ResultsSix studies involving 921 patients were included. Because adjusted within-study comparative estimates were inconsistently reported, findings should be interpreted as non-comparative arm-level summaries. In arm-level pooling, cohorts receiving regorafenib plus ICIs had a higher pooled ORR (0.28, 95% CI: 0.23-0.32) than cohorts receiving regorafenib monotherapy (0.10, 95% CI: 0.06-0.14). The pooled mPFS summary was longer in the combination cohorts (7.34 months; 95% CI: 6.09-8.59) than in the monotherapy cohorts (3.97 months; 95% CI: 3.16-4.77). The pooled mOS summary was numerically longer with the combination (16.87 months) versus monotherapy (11.07 months). The incidence of grade ≥3 adverse events was broadly similar between cohort types.ConclusionIn this arm-level synthesis of real-world comparative cohorts, regorafenib plus ICIs was associated with numerically higher pooled response and longer pooled mPFS summaries than regorafenib monotherapy, while severe adverse event incidence appeared broadly similar across cohort types. Because these results are based on non-comparative pooled arm-level estimates and heterogeneous observational cohorts, they should be considered hypothesis-generating rather than definitive evidence of superiority. Prospective comparative trials and well-adjusted real-world analyses are needed to clarify comparative effectiveness and identify patients most likely to benefit.RegistrationPROSPERO CRD 420261290236.
Abstract licence: CC BY-NC
Sapapsap B, Champarhorm S, Pongpun A, et al.
2026
- Colorectal Neoplasms
- Phenylurea Compounds
- Pyridines
BackgroundTrifluridine/tipiracil (TAS-102) and regorafenib are approved and widely utilized as later-line treatment options for patients with metastatic colorectal cancer (mCRC). However, the optimal sequence between these agents remains unclear. We conducted a systematic review and meta-analysis to compare the efficacy and safety of two treatment sequences: TAS-102 followed by regorafenib (TR) versus regorafenib followed by TAS-102 (RT) in patients with mCRC who had previously failed chemotherapy.MethodsThis study was registered with PROSPERO (CRD42024622437). We systematically searched six databases (PubMed, Scopus, CINAHL, ScienceDirect, medRXiv, and OpenGrey) up to June 1, 2025. Risk of bias was assessed using the ROBINS-I tool. Pooled estimates with 95% confidence intervals (CIs) were calculated using a random-effects model. For studies lacking hazard ratios (HRs), we estimated the HRs using the ratio of median survival times. Publication bias was evaluated with a funnel plot.ResultsThirteen observational studies with moderate to critical risk of bias were included. No significant difference was found in overall survival (OS) (HR =1.04, 95% CI: 0.86-1.25, I2=72%) or progression-free survival (PFS) (HR =1.34, 95% CI: 0.77-2.34, I2=92%) between the TR and RT groups. The RT group had a higher disease control rate (DCR) (33.1% vs. 28.0%) and tended to have more adverse events (AEs).ConclusionsOS and PFS outcomes were comparable between patients treated with TAS-102 followed by regorafenib and those receiving the reverse sequence. Although the RT group was associated with a slightly higher DCR, this was accompanied by a trend toward increased AEs.
Abstract licence: CC BY-NC-ND
Giuliani J, Durante E, Mangiola D, et al.
2026
Objectives: To evaluate and indirectly compare overall survival (OS) and safety of regorafenib, fruquintinib, and trifluridine/tipiracil (TAS-102) monotherapy in refractory metastatic colorectal cancer (mCRC) beyond the third line. Methods: A systematic review and meta-analysis of phase II/III randomized controlled trials was conducted according to PRISMA guidelines. PubMed/MEDLINE, Embase, and Cochrane CENTRAL were searched from inception. Eligible studies included patients with mCRC previously treated with standard chemotherapy and biologic agents, receiving regorafenib, fruquintinib, or TAS-102 as monotherapy in the fourth line or later. OS data were reconstructed from published Kaplan-Meier curves. Pooled median and mean OS were estimated using a random-effects model, and heterogeneity was assessed using the I2 statistic. Safety outcomes were descriptively summarized. Results: Four RCTs were included. The pooled median OS was 7.83 months (95% CI: 6.98-8.80), and the pooled mean OS was 8.90 months (95% CI: 8.00-9.81), with no heterogeneity (I2 = 0%). Survival gains versus placebo ranged from 1.4 to 2.6 months. Survival curves largely overlapped, with differences below one month. Safety was consistent with known profiles. Conclusions: These agents provide comparable efficacy with modest survival benefit in late-line mCRC, highlighting the need for improved strategies and better treatment sequencing.
Abstract licence: CC BY
Akkus E, Hobeika C, Edeline J, et al.
2026
BackgroundThe efficacy of second-line tyrosine kinase inhibitors (TKIs) after first-line immunotherapy-based (IO) treatment in advanced hepatocellular carcinoma (HCC) is not well-established.MethodsA systematic search was conducted to identify studies reporting outcomes with second-line TKIs after progression on first-line IO-based treatment. This reconstructed individual patient data (IPD) meta-analysis used survival data reconstructed from published Kaplan-Meier curves. Studies presenting or combining third-line-or-beyond data were excluded. Overall survival (OS) (primary endpoint) and progression-free survival (PFS) were analyzed using restricted mean survival time (RMST), and random-effects univariable and adjusted meta-regression analyses were performed to account for heterogeneity and potential confounding.ResultsA total of 1,663 patients (16 studies) were included (sorafenib [n = 769], lenvatinib [n = 691], regorafenib [n = 105], and cabozantinib [n = 98]). Most patients received atezolizumab-bevacizumab in the first line. Cabozantinib was excluded from primary analyses as 83.7% of the data were derived from a single study, and baseline characteristics data were limited. The regorafenib group had significantly more Child-Pugh A and less macrovascular invasion. Median OS of all patients was 9.8 months (95% CI 9.4-10.2). The 12-month OS was significantly longer with lenvatinib or regorafenib compared with sorafenib (ΔRMST, 1.49 months [95% CI 1.10-1.88], p ConclusionsIn this reconstructed IPD meta-analysis of predominantly retrospective studies, survival outcomes with second-line TKIs after IO-based therapy were heterogeneous. Lenvatinib and regorafenib showed consistent survival compared with sorafenib; however, findings are exploratory, limited by the observational nature of the data and residual confounding. Prospective studies are needed to define optimal post-immunotherapy sequencing strategies.Impact and implicationsThis study addresses a critical evidence gap in advanced hepatocellular carcinoma by synthesizing available real-world data on second-line TKIs after IO-based first-line treatment, using reconstructed individual patient data and restricted mean survival time to accommodate non-proportional hazards and heterogeneous follow-up. The findings should not be interpreted as a recommendation for any specific TKI. Instead, they describe current survival patterns across heterogeneous retrospective cohorts and underscore the absence of robust comparative evidence in the post-immunotherapy setting. The results are relevant for clinicians and multidisciplinary teams caring for patients who progress after immunotherapy, as they may help contextualize expectations, support shared decision-making with patients and caregivers, and highlight areas of doubt in routine practice. This work highlights the unmet need for prospective randomized trials and high-quality real-world registries to define optimal treatment sequencing, inform regulatory decisions, and ensure equitable access to evidence-based therapies.Systematic review registrationThis study was registered with PROSPERO (Protocol No.: CRD420251133124).
Abstract licence: CC BY
Cheng Z, Yue AM
2026
Michelon I, do Rêgo Castro CE, Querino Belluco AP, et al.
2026
Background/Objectives: Standard treatment of multiply relapsed Ewing sarcoma remains to be established. Recent studies evaluating tyrosine kinase inhibitors (TKIs) with anti-angiogenic properties have shown encouraging results. Therefore, we conducted a systematic review and meta-analysis to explore the efficacy and safety of TKIs in patients with Ewing sarcoma. Methods: We comprehensively searched PubMed, Embase, and Cochrane databases for clinical trials (CTs) and cohort studies assessing TKIs in the treatment of advanced Ewing sarcoma patients who received at least one prior line of therapy. The main outcome was objective response rate (ORR). All analyses were conducted using R software (v.4.2.2), employing random effects models with 95% confidence intervals (CIs). Results: We included 14 studies (seven phase II CT and seven retrospective cohorts), comprising 257 patients. The following TKIs were evaluated: cabozantinib, regorafenib, apatinib, anlotinib, sorafenib, lenvatinib, sunitinib, fruquintinib, and imatinib. In a pooled analysis of all Ewing sarcoma patients treated with TKIs, the ORR was 23% (95% CI, 11.2-37.1%) and the DCR was 61.1% (95% CI, 47.3-74.2%). Responses were numerically higher but statistically nonsignificant between clinical trials and real-world studies. The analysis including only single-agent TKIs showed better responses for anlotinib and apatinib, yet these drugs are not available in Western countries. Among the FDA-approved TKIs, superior outcomes were noted with single-agent cabozantinib. (ORR: 21.6%) and regorafenib (ORR: 11.3%). Several studies did not report toxicity data exclusively for Ewing sarcoma patients; thus, conclusions about toxicity are mostly based on the general population of studies and may not be fully representative of Ewing sarcoma patients. Conclusions: Anti-angiogenic TKIs have shown important anti-tumoral activity in patients with Ewing sarcoma. Efficacy was consistently seen in both clinical trials and real-world studies. Nonetheless, there are important differences in study design and population that may limit our interpretation of efficacy and toxicity findings.
Abstract licence: CC BY
Al Namer Y, M. Al-Ahmad M, Said A, et al.
2026
Objectives The aim of this systematic review is comparing the efficacy and safety of traditional chemotherapy with targeted therapy in managing lung cancer, colorectal cancer (CRC), and hepatocellular carcinoma (HCC). Materials and Methods Article search was conducted on PubMed, Cochrane, Google Scholar, EMBASE, and Web of Science for three weeks, including published or unpublished randomized articles comparing the two treatment modalities in adults. Non-randomized trials or trials comparing one therapy with a placebo or another in the same class were excluded. Eighteen articles were selected and assessed for their bias risk by the Cochrane Collaboration tool, demonstrating a low overall risk of bias. Their methodological quality was evaluated as high by Jadad Scale. Results Results were synthesized narratively, finding that in non-small cell lung cancer (NSCLC), targeted therapy of either afatinib or erlotinib significantly enhanced overall survival (OS) (LUX-Lung 3: p = 0·0015 ; LUX-Lung 6: p = 0·023 ) and progression-free survival (PFS) ( p < 0.0001 ), respectively, in comparison to chemotherapy with less incidence of grade 3 or greater adverse events. The efficacy of bevacizumab with chemotherapy showed a contradiction in enhancing OS in two studies conducted in the context of metastatic colorectal cancer (mCRC) with 10% more hypertension and diarrhea occurrence. Targeted therapy of aflibercept and regorafenib showed promising OS ( p = 0.0032 and p = 0.0052 , respectively) and PFS ( p < 0.0001 for both agents) results for refractory mCRC. Concerning HCC, sorafenib alone demonstrated OS benefits ( p < 0.001 ), while regorafenib and nivolumab were safe alternatives upon progression. Lenvatinib and pembrolizumab had promising results in unresectable HCC. Conclusion This paper was limited by exempting articles lacking a direct comparison with chemotherapy in HCC and for not conducting a meta-analysis of its results. It suggested validating targeted therapy in NSCLC and investigating gained resistance and optimal sequencing with it.
Abstract licence: CC BY
Pfeiffer P, Cremolini C, Ducreux M, et al.
2026
- Colorectal Neoplasms
- Neoplasm Metastasis
- Phenylurea Compounds
BackgroundGuideline-recommended nontargeted systemic therapies for previously treated metastatic colorectal cancer (mCRC) include regorafenib, trifluridine/tipiracil, and fruquintinib, but no consensus exists on the definition of clinically meaningful improvements for later-line mCRC treatments.Materials and methodsTrials were identified from systematic searches in MEDLINE, Embase, and the Cochrane Library. Meta-analyses were performed to characterize overall survival (OS) and progression-free survival (PFS) improvements with systemic therapy vs placebo in previously treated mCRC. Meta-analyses were conducted using fixed-effect and random-effects (RE) frequentist models of difference in medians, hazard ratios (HRs), and 12-month restricted mean survival time (RMST).ResultsSix randomized, placebo-controlled, phase III trials of 3277 patients comparing oral systemic monotherapies with placebo were analyzed. Using the RE model, the meta-analyzed OS estimate for oral systemic monotherapy vs placebo was 1.86 months (95% confidence interval [CI], 1.30-2.42) for the difference in medians, 0.69 (95% CI, 0.64-0.76) for HRs, and 1.25 months (95% CI, 0.69-1.82) for the difference in 12-month RMST. For PFS, meta-analyzed median improvement was 0.97 months (95% CI, 0.28-1.66), HR was 0.38 (95% CI, 0.30-0.47), and 12-month RMST difference was 1.90 months (95% CI, 1.41-2.39). Sensitivity analyses, excluding the FRESCO-2 trial due to prior treatment differences, confirmed the primary meta-analysis results.ConclusionWhen assessing the clinical benefit of later-line mCRC treatments, the broad clinical picture, including individualized treatment goals, should be evaluated. Considering multiple survival measures in the later-line mCRC context, an incremental survival improvement with oral systemic monotherapy vs no active therapy is clinically meaningful.
Abstract licence: CC BY
Yang F, Li D, Li B, et al.
2026
- Colorectal Neoplasms
- Phenylurea Compounds
- Pyridines
BackgroundRegorafenib alone has shown limited efficacy in some cases of colorectal cancer (CRC), while the use of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors is becoming increasingly common in cancer treatment. Previous studies have indicated significant benefits of combining regorafenib with PD-1/PD-L1 inhibitors in patients with advanced or metastatic CRC. This study aimed to evaluate the efficacy and outcomes of combining regorafenib with PD-1/PD-L1 inhibitors in patients with advanced or metastatic CRC.MethodsWe systematically retrieved clinical trials from PubMed and Embase up to August 1, 2023. The quality of eligible clinical trials was assessed using the methodological index for non-randomized studies and the JBI critical appraisal checklist for case eeries. Efficacy metrics, such as objective response rate (ORR), disease control rate (DCR), median progression-free survival (mPFS), and median overall survival, were analyzed using STATA version 15.1, with results presented as 95% confidence intervals. Heterogeneity was assessed using the chi-square Q test and I² statistic, with I² > 50% indicating high heterogeneity, which was addressed using a random effects model.ResultsFourteen studies were included in this meta-analysis. The pooled ORR, DCR, and mPFS were 7%, 54%, and 2.99 months, respectively. Subgroup analysis revealed that for patients with liver metastasis (LM), the pooled ORR was 6%, DCR was 47%, and mPFS was 1.99 months. In contrast, for patients without LM, the pooled ORR was 21%, DCR was 61%, and mPFS was 3.48 months.ConclusionThese results indicate that combination therapy is more effective in patients without LM than in those with LM. This suggests that regorafenib plus PD-1/PD-L1 inhibitors may be a more suitable option for patients without liver metastases.
Abstract licence: CC BY
Sources: aggregated from Europe PMC (EMBL-EBI), OpenAlex, Crossref, PubMed and other open scholarly databases. Retracted articles are excluded. Study information is provided for research purposes and does not constitute medical advice.
Pharmacology and chemical data from DrugBank
Key facts
Drug status
Approved
Major interactions
None known
Half-life
28 hours
Mechanism
Regorafenib is a small molecule inhibitor of multiple membrane-bound and intrace…
Food interactions
4 warnings
Human targets
19 targets
Data: DrugBank · CC BY-NC 4.0
Pharmacokinetics at a glance
Absorption
2.5 μg/mL
Tmax = 4 hours;
AUC = 70.4 μg*h/mL;
Cmax, steady-state = 3.9…
Half-life
160 mg
M2 metabolite, 160 mg oral dose = 25 hours (14-32 hours);
M5 metabolite, 160 mg…
Protein binding
99.5%
Volume of distribution
24-hour
Metabolism
99.8%
Elimination
71%
Pharmacokinetic data: DrugBank · CC BY-NC 4.0
[L16835]
Known interactions with other medicines. Always consult a healthcare professional.
Showing 50 of 986 interactions
How the body processes this drug — absorption, distribution, metabolism, and elimination
Tmax = 4 hours;
AUC = 70.4 μg*h/mL;
Cmax, steady-state = 3.9 μg/mL;
AUC, steady-state = 58.3 μg*h/mL;
The mean relative bioavailability of tablets compared to an oral solution is 69% to 83%.
M2 metabolite, 160 mg oral dose = 25 hours (14-32 hours);
M5 metabolite, 160 mg oral dose = 51 hours (32-72 hours);
Regorafenib is an inhibitor of P-glycoprotein [FDA Label], while its active metabolites M-2 (N-oxide) and M-5 (N-oxide and N-desmethyl) are substrates of P-glycoprotein .
[A36336]
Proteins and enzymes this drug interacts with in the body
Can promote endothelial cell proliferation, survival and angiogenesis in adulthood. Its function in promoting cell proliferation seems to be cell-type specific. Promotes PGF-mediated proliferation of endothelial cells, proliferation of some types of cancer cells, but does not promote proliferation of normal fibroblasts (in vitro).
Has very high affinity for VEGFA and relatively low protein kinase activity; may function as a negative regulator of VEGFA signaling by limiting the amount of free VEGFA and preventing its binding to KDR. Modulates KDR signaling by forming heterodimers with KDR. Ligand binding leads to the activation of several signaling cascades.
Activation of PLCG leads to the production of the cellular signaling molecules diacylglycerol and inositol 1,4,5-trisphosphate and the activation of protein kinase C. Mediates phosphorylation of PIK3R1, the regulatory subunit of phosphatidylinositol 3-kinase, leading to activation of phosphatidylinositol kinase and the downstream signaling pathway. Mediates activation of MAPK1/ERK2, MAPK3/ERK1 and the MAP kinase signaling pathway, as well as of the AKT1 signaling pathway.
Phosphorylates SRC and YES1, and may also phosphorylate CBL. Promotes phosphorylation of AKT1 at 'Ser-473'. Promotes phosphorylation of PTK2/FAK1 PMID:16685275
Promotes reorganization of the actin cytoskeleton. Isoforms lacking a transmembrane domain, such as isoform 2 and isoform 3, may function as decoy receptors for VEGFA, VEGFC and/or VEGFD. Isoform 2 plays an important role as negative regulator of VEGFA- and VEGFC-mediated lymphangiogenesis by limiting the amount of free VEGFA and/or VEGFC and preventing their binding to FLT4.
Modulates FLT1 and FLT4 signaling by forming heterodimers. Binding of vascular growth factors to isoform 1 leads to the activation of several signaling cascades. Activation of PLCG1 leads to the production of the cellular signaling molecules diacylglycerol and inositol 1,4,5-trisphosphate and the activation of protein kinase C.
Mediates activation of MAPK1/ERK2, MAPK3/ERK1 and the MAP kinase signaling pathway, as well as of the AKT1 signaling pathway. Mediates phosphorylation of PIK3R1, the regulatory subunit of phosphatidylinositol 3-kinase, reorganization of the actin cytoskeleton and activation of PTK2/FAK1. Required for VEGFA-mediated induction of NOS2 and NOS3, leading to the production of the signaling molecule nitric oxide (NO) by endothelial cells.
Phosphorylates PLCG1. Promotes phosphorylation of FYN, NCK1, NOS3, PIK3R1, PTK2/FAK1 and SRC
Modulates KDR signaling by forming heterodimers. The secreted isoform 3 may function as a decoy receptor for VEGFC and/or VEGFD and play an important role as a negative regulator of VEGFC-mediated lymphangiogenesis and angiogenesis. Binding of vascular growth factors to isoform 1 or isoform 2 leads to the activation of several signaling cascades; isoform 2 seems to be less efficient in signal transduction, because it has a truncated C-terminus and therefore lacks several phosphorylation sites.
Mediates activation of the MAPK1/ERK2, MAPK3/ERK1 signaling pathway, of MAPK8 and the JUN signaling pathway, and of the AKT1 signaling pathway. Phosphorylates SHC1. Mediates phosphorylation of PIK3R1, the regulatory subunit of phosphatidylinositol 3-kinase.
Promotes phosphorylation of MAPK8 at 'Thr-183' and 'Tyr-185', and of AKT1 at 'Ser-473'
Activates the AKT1 signaling pathway by phosphorylation of PIK3R1, the regulatory subunit of phosphatidylinositol 3-kinase. Activated KIT also transmits signals via GRB2 and activation of RAS, RAF1 and the MAP kinases MAPK1/ERK2 and/or MAPK3/ERK1. Promotes activation of STAT family members STAT1, STAT3, STAT5A and STAT5B.
Activation of PLCG1 leads to the production of the cellular signaling molecules diacylglycerol and inositol 1,4,5-trisphosphate. KIT signaling is modulated by protein phosphatases, and by rapid internalization and degradation of the receptor. Activated KIT promotes phosphorylation of the protein phosphatases PTPN6/SHP-1 and PTPRU, and of the transcription factors STAT1, STAT3, STAT5A and STAT5B.
Promotes phosphorylation of PIK3R1, CBL, CRK (isoform Crk-II), LYN, MAPK1/ERK2 and/or MAPK3/ERK1, PLCG1, SRC and SHC1
Required for normal skeleton development and cephalic closure during embryonic development. Required for normal development of the mucosa lining the gastrointestinal tract, and for recruitment of mesenchymal cells and normal development of intestinal villi. Plays a role in cell migration and chemotaxis in wound healing.
Plays a role in platelet activation, secretion of agonists from platelet granules, and in thrombin-induced platelet aggregation. Binding of its cognate ligands - homodimeric PDGFA, homodimeric PDGFB, heterodimers formed by PDGFA and PDGFB or homodimeric PDGFC -leads to the activation of several signaling cascades; the response depends on the nature of the bound ligand and is modulated by the formation of heterodimers between PDGFRA and PDGFRB. Phosphorylates PIK3R1, PLCG1, and PTPN11.
Activation of PLCG1 leads to the production of the cellular signaling molecules diacylglycerol and inositol 1,4,5-trisphosphate, mobilization of cytosolic Ca(2+) and the activation of protein kinase C. Phosphorylates PIK3R1, the regulatory subunit of phosphatidylinositol 3-kinase, and thereby mediates activation of the AKT1 signaling pathway. Mediates activation of HRAS and of the MAP kinases MAPK1/ERK2 and/or MAPK3/ERK1.
Promotes activation of STAT family members STAT1, STAT3 and STAT5A and/or STAT5B. Receptor signaling is down-regulated by protein phosphatases that dephosphorylate the receptor and its down-stream effectors, and by rapid internalization of the activated receptor
Enzymes involved in drug metabolism — important for understanding drug interactions
Proteins that transport this drug across cell membranes
PMID:2897240 PMID:35970996 PMID:8898203 PMID:9038218 PMID:35507548
Catalyzes the flop of phospholipids from the cytoplasmic to the exoplasmic leaflet of the apical membrane. Participates mainly to the flop of phosphatidylcholine, phosphatidylethanolamine, beta-D-glucosylceramides and sphingomyelins .
PMID:8898203
Energy-dependent efflux pump responsible for decreased drug accumulation in multidrug-resistant cells PMID:2897240 PMID:35970996 PMID:9038218
PMID:11306452 PMID:12958161 PMID:19506252 PMID:20705604 PMID:28554189 PMID:30405239 PMID:31003562
Involved in porphyrin homeostasis, mediating the export of protoporphyrin IX (PPIX) from both mitochondria to cytosol and cytosol to extracellular space, it also functions in the cellular export of heme .
PMID:20705604 PMID:23189181
Also mediates the efflux of sphingosine-1-P from cells .
PMID:20110355
Acts as a urate exporter functioning in both renal and extrarenal urate excretion .
PMID:19506252 PMID:20368174 PMID:22132962 PMID:31003562 PMID:36749388
In kidney, it also functions as a physiological exporter of the uremic toxin indoxyl sulfate (By similarity). Also involved in the excretion of steroids like estrone 3-sulfate/E1S, 3beta-sulfooxy-androst-5-en-17-one/DHEAS, and other sulfate conjugates .
PMID:12682043 PMID:28554189 PMID:30405239
Mediates the secretion of the riboflavin and biotin vitamins into milk (By similarity). Extrudes pheophorbide a, a phototoxic porphyrin catabolite of chlorophyll, reducing its bioavailability (By similarity).
Plays an important role in the exclusion of xenobiotics from the brain (Probable). It confers to cells a resistance to multiple drugs and other xenobiotics including mitoxantrone, pheophorbide, camptothecin, methotrexate, azidothymidine, and the anthracyclines daunorubicin and doxorubicin, through the control of their efflux .
PMID:11306452 PMID:12477054 PMID:15670731 PMID:18056989 PMID:31254042
In placenta, it limits the penetration of drugs from the maternal plasma into the fetus (By similarity). May play a role in early stem cell self-renewal by blocking differentiation (By similarity).
In inflammatory macrophages, exports itaconate from the cytosol to the extracellular compartment and limits the activation of TFEB-dependent lysosome biogenesis involved in antibacterial innate immune response
ATC L01EX05
Chemical identifiers
CAS, UNII, InChI Key and database cross-references
Show
Chemical identifiers
CAS, UNII, InChI Key and database cross-references
Linked compound data from DrugBank Open Data (CC BY-NC 4.0)
Regorafenib
Additional database identifiers
Drugs Product Database (DPD)
22042
ChemSpider
9342697
BindingDB
50363397
ZINC
ZINC000006745272
HUGO Gene Nomenclature Committee (HGNC)
HGNC:3763
GenAtlas
FLT1
GeneCards
FLT1
GenBank Gene Database
X51602
GenBank Protein Database
31432
Guide to Pharmacology
1812
UniProt Accession
VGFR1_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:6307
GenAtlas
KDR
GeneCards
KDR
GenBank Gene Database
AF035121
GenBank Protein Database
2655412
Guide to Pharmacology
1813
UniProt Accession
VGFR2_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:3767
GenAtlas
FLT4
GeneCards
FLT4
GenBank Gene Database
X69878
GenBank Protein Database
297050
Guide to Pharmacology
1814
UniProt Accession
VGFR3_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:6342
GenAtlas
KIT
GeneCards
KIT
GenBank Gene Database
X06182
GenBank Protein Database
34085
Guide to Pharmacology
1805
UniProt Accession
KIT_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:8803
GenAtlas
PDGFRA
GeneCards
PDGFRA
GenBank Gene Database
M21574
GenBank Protein Database
189734
Guide to Pharmacology
1803
UniProt Accession
PGFRA_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:8804
GenAtlas
PDGFRB
GeneCards
PDGFRB
GenBank Gene Database
J03278
GenBank Protein Database
189732
Guide to Pharmacology
1804
UniProt Accession
PGFRB_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:3688
GenAtlas
FGFR1
GeneCards
FGFR1
GenBank Gene Database
X51803
GenBank Protein Database
31368
Guide to Pharmacology
1808
UniProt Accession
FGFR1_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:3689
GenAtlas
FGFR2
GenBank Gene Database
X52832
GenBank Protein Database
31374
Guide to Pharmacology
1809
UniProt Accession
FGFR2_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:11724
GenAtlas
TEK
GeneCards
TEK
GenBank Gene Database
L06139
Guide to Pharmacology
1842
UniProt Accession
TIE2_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:2731
GeneCards
DDR2
Guide to Pharmacology
1844
UniProt Accession
DDR2_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:8031
GenAtlas
NTRK1
GeneCards
NTRK1
GenBank Gene Database
M23102
GenBank Protein Database
339918
Guide to Pharmacology
1817
UniProt Accession
NTRK1_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:3386
GenAtlas
EPHA2
GeneCards
EPHA2
GenBank Gene Database
M59371
GenBank Protein Database
181944
Guide to Pharmacology
1822
UniProt Accession
EPHA2_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:9829
GenAtlas
RAF1
GeneCards
RAF1
GenBank Gene Database
X03484
GenBank Protein Database
35842
Guide to Pharmacology
2184
UniProt Accession
RAF1_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:1097
GenAtlas
BRAF
GeneCards
BRAF
GenBank Gene Database
M95712
GenBank Protein Database
41387220
Guide to Pharmacology
1943
UniProt Accession
BRAF_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:6873
GenAtlas
MAPK11
GeneCards
MAPK11
GenBank Gene Database
U53442
Guide to Pharmacology
1500
UniProt Accession
MK11_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:3955
GeneCards
FRK
Guide to Pharmacology
2025
UniProt Accession
FRK_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:76
GenAtlas
ABL1
GeneCards
ABL1
GenBank Gene Database
X16416
GenBank Protein Database
28237
Guide to Pharmacology
1923
UniProt Accession
ABL1_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:9967
GenAtlas
RET
GeneCards
RET
GenBank Gene Database
X12949
Guide to Pharmacology
2185
UniProt Accession
RET_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:2433
GenAtlas
CSF1R
GeneCards
CSF1R
GenBank Gene Database
M25786
GenBank Protein Database
553224
Guide to Pharmacology
1806
UniProt Accession
CSF1R_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:2637
GenAtlas
CYP3A4
GeneCards
CYP3A4
GenBank Gene Database
M18907
Guide to Pharmacology
1337
UniProt Accession
CP3A4_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:12541
GeneCards
UGT1A9
GenBank Gene Database
S55985
GenBank Protein Database
7690346
UniProt Accession
UD19_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:2622
GenAtlas
CYP2C8
GeneCards
CYP2C8
GenBank Gene Database
M17397
Guide to Pharmacology
1325
UniProt Accession
CP2C8_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:2623
GenAtlas
CYP2C9
GeneCards
CYP2C9
GenBank Gene Database
AY341248
Guide to Pharmacology
1326
UniProt Accession
CP2C9_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:2615
GeneCards
CYP2B6
GenBank Gene Database
M29874
GenBank Protein Database
181296
Guide to Pharmacology
1324
UniProt Accession
CP2B6_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:12530
GeneCards
UGT1A1
GenBank Gene Database
M57899
GenBank Protein Database
184473
Guide to Pharmacology
2990
UniProt Accession
UD11_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:2621
GeneCards
CYP2C19
GenBank Gene Database
M61854
GenBank Protein Database
181344
Guide to Pharmacology
1328
UniProt Accession
CP2CJ_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:40
GenAtlas
ABCB1
GeneCards
ABCB1
GenBank Gene Database
M14758
GenBank Protein Database
307180
Guide to Pharmacology
768
UniProt Accession
MDR1_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:74
GenAtlas
ABCG2
GeneCards
ABCG2
GenBank Gene Database
AF103796
GenBank Protein Database
4185796
Guide to Pharmacology
792
UniProt Accession
ABCG2_HUMAN
DrugBank citations
If you use DrugBank data in your research, please cite:
- DrugBank 6.02024Recommended citationKnox C., Wilson M., Klinger C.M., et alDrugBank 6.0: the DrugBank Knowledgebase for 2024Nucleic Acids Res. 2024 Jan 552(D1):D1265-D1275
- DrugBank 5.02018Wishart D.S., Feunang Y.D., Guo A.C., et alDrugBank 5.0: a major update to the DrugBank database for 2018Nucleic Acids Res. 2017 Nov 846(D1):D1074-D1082
- DrugBank 4.02014Law V., Knox C., Djoumbou Y., et alDrugBank 4.0: shedding new light on drug metabolismNucleic Acids Res. 2014 Jan 142(1):D1091-7
- DrugBank 3.02011Knox C., Law V., Jewison T., et alDrugBank 3.0: a comprehensive resource for 'omics' research on drugsNucleic Acids Res. 2011 Jan39(Database issue):D1035-41
- DrugBank 2.02008Wishart D.S., Knox C., Guo A.C., et alDrugBank: a knowledgebase for drugs, drug actions and drug targets.Nucleic Acids Research2008 Jan36(Database issue):D901-6
- DrugBank 1.02006Wishart D.S., Knox C., Guo A.C., et alDrugBank: a comprehensive resource for in silico drug discovery and exploration.Nucleic Acids Research2006 Jan 134(Database issue):D668-72