Phenotype-based variation as a biomarker of sensitivity to molecularly targeted therapy in melanoma

Senses, Kerem Mert; Ghasemi, Mehdi; Akbar, Muhammad Waqas; Isbilen, Murat; Fallacara, Anna Lucia; Frankenburg, Shoshana; Schenone, Silvia; Lotem, Michal; Botta, Maurizio; Gure, Ali Osmay

doi:10.1039/c6md00466k

Cited by 4 publications

(7 citation statements)

References 36 publications

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“…In line with our earlier findings 27 , we show here for the first time in vitro, that Lapatinib and Midostaurin are candidates for such combination therapy, as they target selectively either NS/E or CS/M cells, respectively. Even though EMT might be a signature shared among tumor types, combination treatment suggestions obtained for breast cancer in this study are different from those we found for other tumor types, such as colon cancer and melanoma 68,69 . One explanation for this can be that NS/E and CS/M cell types defined for tumors originating from different tissues actually define different phenotypes in the EMT or plasticity scale.…”

Section: Discussioncontrasting

confidence: 99%

A Stemness and EMT Based Gene Expression Signature Identifies Phenotypic Plasticity and is A Predictive but Not Prognostic Biomarker for Breast Cancer

et al. 2020

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Aims: Molecular heterogeneity of breast cancer results in variation in morphology, metastatic potential and response to therapy. We previously showed that breast cancer cell line sub-groups obtained by a clustering approach using highly variable genes overlapped almost completely with sub-groups generated by a drug cytotoxicity-profile based approach. Two distinct cell populations thus identified were CSC(cancer stem cell)-like and non-CSC-like. In this study we asked whether an mRNA based gene signature identifying these two cell types would explain variation in stemness, EMT, drug sensitivity, and prognosis in silico and in vitro. Main methods: In silico analyses were performed using publicly available cell line and patient tumor datasets. In vitro analyses of phenotypic plasticity and drug responsiveness were obtained using human breast cancer cell lines. Key findings: We find a novel gene list (CNCL) that can generate both categorical and continuous variables corresponding to the stemness/EMT (epithelial to mesenchymal transition) state of tumors. We are presenting a novel robust gene signature that unites previous observations related either to EMT or stemness in breast cancer. We show in silico, that this signature perfectly predicts behavior of tumor cells tested in vitro, and can reflect tumor plasticity. We thus demonstrate for the first time, that breast cancer subtypes are sensitive to either Lapatinib or Midostaurin. The same gene list is not capable of predicting prognosis in most cohorts, except for one that includes patients receiving neo-adjuvant taxene therapy. Significance: CNCL is a robust gene list that can identify both stemness and the EMT state of cell lines and tumors. It can be used to trace tumor cells during the course of phenotypic changes they undergo, that result in altered responses to therapeutic agents. The fact that such a list cannot be used to identify prognosis in most patient cohorts suggests that presence of factors other than stemness and EMT affect mortality.

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Section: Discussioncontrasting

confidence: 99%

A Stemness and EMT Based Gene Expression Signature Identifies Phenotypic Plasticity and is A Predictive but Not Prognostic Biomarker for Breast Cancer

et al. 2020

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“…On the other hand, resistant subgroups showed significant enrichments of gene sets related to epithelial-mesenchymal transition and multicancer invasiveness signatures, indicating an invasive/mesenchymal phenotype in resistant cells (Figure B). These results are concordant with previous findings where melanoma cells were classified into invasive, proliferative, and intermediate categories …”

supporting

confidence: 93%

“…These results are concordant with previous findings where melanoma cells were classified into invasive, proliferative, and intermediate categories. 14 To further investigate mechanisms behind resistance to 10a, we performed protein−chemical interaction network analysis with 46 genes using the NetworkAnalyst 16 online tool. This revealed that, out of 18 resistance associated proteins, 15 extensively interact with a pyrazolopyrimidine derivative and three histone deacetylase (HDAC) inhibitors, valproic acid, trichostatin A, and entinostat (Figure 3).…”

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confidence: 99%

Predictive Gene Signature for Pyrazolopyrimidine Derivative c-Src Inhibitor 10a Sensitivity in Melanoma Cells

Kucukkaraduman

Turk

Fallacara

et al. 2020

ACS Med. Chem. Lett.

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Melanoma is a highly aggressive cancer with poor prognosis. Although more than 80% of melanomas harbor an activating mutation in genes within the MAPK pathway, which are mutually exclusive, usefulness of therapies targeting MAPK pathway are impeded by innate and/or acquired resistance in most patients. In this study, using melanoma cells, we report the efficacy of a recently developed pyrazolo [3,4-d]pyrimidine derived c-Src inhibitor 10a and identify a molecular signature which is predictive of 10a chemosensitivity. We show that the expression of TMED7, PLOD2, XRCC5, and NSUN5 are candidate biomarkers for 10a sensitivity. Although an undifferentiated/mesenchymal/ invasive status of melanoma cells is associated with resistance to 10a, we show here for the first time that melanoma cells can be sensitized to 10a via treatment with valproic acid, a histone deacetylase inhibitor.

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“…The rationale for targeting HSP90 is supported not only by a high level of this protein in cancer cells, but also by cancer cellselective formation of HSP90 multi-chaperone complexes exerting a high ATPase activity [74]. In addition, HSP90 has been identified as a crucial regulator of melanoma cell phenotype, and inhibition of HSP90 has substantially affected both commercially available and primary melanoma cell lines [75], also those resistant to currently available therapeutics [76]. A number of natural and synthetic compounds of different chemical structures and binding sites have been identified as selective HSP90 inhibitors (Fig.…”

Section: Hsp90 Inhibitorsmentioning

confidence: 99%

Inhibitors of HSP90 in melanoma

Mielczarek-Lewandowska

Hartman

Czyż

2019

Apoptosis

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HSP90 (heat shock protein 90) is an ATP-dependent molecular chaperone involved in a proper folding and maturation of hundreds of proteins. HSP90 is abundantly expressed in cancer, including melanoma. HSP90 client proteins are the key oncoproteins of several signaling pathways controlling melanoma development, progression and response to therapy. A number of natural and synthetic compounds of different chemical structures and binding sites within HSP90 have been identified as selective HSP90 inhibitors. The majority of HSP90-targeting agents affect N-terminal ATPase activity of HSP90. In contrast to N-terminal inhibitors, agents interacting with the middle and C-terminal domains of HSP90 do not induce HSP70dependent cytoprotective response. Several inhibitors of HSP90 were tested against melanoma in pre-clinical studies and clinical trials, providing evidence that these agents can be considered either as single or complementary therapeutic strategy. This review summarizes current knowledge on the role of HSP90 protein in cancer with focus on melanoma, and provides an overview of structurally different HSP90 inhibitors that are considered as potential therapeutics for melanoma treatment.

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Phenotype-based variation as a biomarker of sensitivity to molecularly targeted therapy in melanoma

Cited by 4 publications

References 36 publications

A Stemness and EMT Based Gene Expression Signature Identifies Phenotypic Plasticity and is A Predictive but Not Prognostic Biomarker for Breast Cancer

A Stemness and EMT Based Gene Expression Signature Identifies Phenotypic Plasticity and is A Predictive but Not Prognostic Biomarker for Breast Cancer

Predictive Gene Signature for Pyrazolopyrimidine Derivative c-Src Inhibitor 10a Sensitivity in Melanoma Cells

Inhibitors of HSP90 in melanoma

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