Co-clinical trials demonstrate predictive biomarkers for dovitinib, an FGFR inhibitor, in lung squamous cell carcinoma

Kim, H.R.; Kang, Han Sol; Shim, Hyo Sup; Kim, E.Y.; Kim, J.; Kim, D.J.; Lee, J.G.; Lee, C.Y.; Hong, Min Hee; Kim, S.-M.; Kim, H.; Pyo, Kyoung‐Ho; Yun, Mi Ran; Park, H.J.; Han, Jing; Youn, HyeSook; Ahn, Myung Ju; Paik, Soonmyung; Kim, T.-M.; Cho, Byoung Chul

doi:10.1093/annonc/mdx098

Cited by 46 publications

(43 citation statements)

References 24 publications

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“…T-cells developing in this system seldom experience central tolerance induction, have not been previously exposed to the hostile tumor microenvironment, and are seldom matched to the engrafted tumor. Also, erroneously trained T-cells and other cells from the hematopoietic system frequently cause graft-vs-host disease [28]. Although these preclinical models can be informative, they lack a tumor-primed, autologous immune component that may better predict patient-specific responses in a heterogeneous disease such as HGSOC.…”

Section: Discussionmentioning

confidence: 99%

“…These models recapitulate the biology of the original patient tumor, mimic drug response to that of the patient, and can better recapitulate the tumor microenvironment than historic cell line models for HGSOC [24e26]. Preclinical studies using PDX models developed from patient tumors, performed in parallel to clinical trials, have shown that PDX models reliably reproduce clinical outcomes [27,28]. However, these models of engrafted human tumors generally rely on immunodeficient mice that lack a human immune system, making it difficult to test immunomodulating therapies in vivo.…”

Section: Introductionmentioning

confidence: 99%

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An autologous humanized patient-derived-xenograft platform to evaluate immunotherapy in ovarian cancer

Gitto

Kim

Rafail

et al. 2020

Gynecologic Oncology

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An autologous humanized patient-derived-xenograft platform to evaluate immunotherapy in ovarian cancer

Gitto

Kim

Rafail

et al. 2020

Gynecologic Oncology

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“…Additionally, genetic alterations in other signaling pathways may impact dovitinib activity. Patient-derived xenograft models have demonstrated the association between FGF3 and FGF19 upregulation and response to dovitinib [20]. The presence of additional mutations in related signaling pathways may not be reflected in the dataset in this study due to the length of time between tumor biopsy and dovitinib treatment.…”

Section: Discussionmentioning

confidence: 94%

A mutation-specific, single-arm, phase 2 study of dovitinib in patients with advanced malignancies

et al. 2020

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Background: Receptor tyrosine kinases (RTKs) play key roles in tumorigenesis. The multi-RTK inhibitor dovitinib has demonstrated promising antitumor activity in multiple cancers. Patients and Methods: In this phase 2, open-label, single-arm study, patients with advanced malignancies with RTK-pathway genetic aberrations whose disease progressed on/following standard treatment received dovitinib (500 mg/day; 5-dayson/2-days-off). The primary endpoint was clinical benefit rate (CBR; complete response, partial response [PR], or stable disease [SD] for ≥ 16 weeks). Results: Of 80 patients enrolled, common tumors included gastrointestinal stromal tumors (GIST; 20.0%), colorectal cancer (CRC; 18.8%), and ovarian cancer (10.0%). Patients were heavily pretreated (median prior lines = 4; 67.5% had ≥ 3 prior lines). Genetic aberrations included cKIT (28.8%), FGFR3 (15.0%), and RET (15.0%). The CBR was 13.8%; one PR (GIST) and 10 SD (adenoid cystic [n = 3]; ovarian [n = 3]; GIST [n = 2]; CRC [n = 1]; gastroesophageal junction [n = 1]). The most common treatment-related adverse events were fatigue, diarrhea, nausea, and vomiting. Conclusions: In this heterogeneous patient population, the safety profile was acceptable for dovitinib therapy. A subset of patients with RTK pathway-activated tumors experienced clinical benefit. However, the primary endpoint was not met, suggesting further refinement of predictive biomarkers is required.

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“…Authors report correlation between clinical results and PDX models. Kim et al conducted co-clinical trial to identify predictive biomarkers for the multikinase inhibitor Dovitinib in lung squamous cell carcinoma (LSCC) and revealed that FGFR gene expression signatures were predictors for the response to Dovitinib in LSCC [139]. Stebbing et al provided data that supported the use of the personalized TumorGraft model as an investigational platform for therapeutic decision-making that could guide treatment for rare tumors such as sarcomas [140].…”

Section: In Vivo Modelsmentioning

confidence: 99%

Recent Approaches Encompassing the Phenotypic Cell Heterogeneity for Anticancer Drug Efficacy Evaluation

Stulpinas¹,

Imbrasaitė²,

Krestnikova³

et al. 2020

Tumor Progression and Metastasis

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Despite the advancements in biomarker-based personalized cancer therapy, the inadequacy of molecular and genetic profiling in identifying effective drug combinations was defined in most cases. Drug resistance remains a major limitation of the current predictive oncology. Emerging reports indicate that the success of anticancer therapy is usually limited by intratumoral heterogeneity which is not captured by the existing cancer cell biomarker-based approaches. Cell heterogeneity, not only genetic but also phenotypic, is considered to be the root cause of resistance to anticancer treatment, cancer progression, and the presence of cancer stem cells. Therefore, functional testing of live cells representing various cell types within the tumor exposed to potential therapies is needed for identification of effective drug combinations. Here we look at the different existing model systems, including ex vivo models of the patient's tumor cells, 2D/3D in vitro cultures/cocultures, patient-derived cellular organoids, single-cell models, ex vivo tumor platforms containing tumor microenvironment and extracellular matrix, etc., scoping at drug efficacy evaluation and solving the problem of cancer resistance.

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Co-clinical trials demonstrate predictive biomarkers for dovitinib, an FGFR inhibitor, in lung squamous cell carcinoma

Abstract: FGFR gene expression signatures are predictors for the response to dovitinib in LSCC.

Cited by 46 publications

References 24 publications

An autologous humanized patient-derived-xenograft platform to evaluate immunotherapy in ovarian cancer

An autologous humanized patient-derived-xenograft platform to evaluate immunotherapy in ovarian cancer

A mutation-specific, single-arm, phase 2 study of dovitinib in patients with advanced malignancies

Recent Approaches Encompassing the Phenotypic Cell Heterogeneity for Anticancer Drug Efficacy Evaluation

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