Response biomarkers: re-envisioning the approach to tailoring drug therapy for cancer

Amin, Shahil; Bathe, Oliver F.

doi:10.1186/s12885-016-2886-9

Cited by 27 publications

(26 citation statements)

References 75 publications

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“…Our results also may have been affected by the duration of treatment, although eight dogs did receive treatment for ≥3 weeks. As doxycycline would be predicted to alter cell signaling and thus have cytostatic rather than cytotoxic activity, clinical response criteria developed for the evaluation of cytotoxic drugs may not be the ideal way to monitor drug efficacy, and other biomarkers of response and efficacy should be considered in future research ( 51 ).…”

Section: Discussionmentioning

confidence: 99%

Metabolic Abnormalities Detected in Phase II Evaluation of Doxycycline in Dogs with Multicentric B-Cell Lymphoma

et al. 2018

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Doxycycline has antiproliferative effects in human lymphoma cells and in murine xenografts. We hypothesized that doxycycline would decrease canine lymphoma cell viability and prospectively evaluated its clinical tolerability in client-owned dogs with spontaneous, nodal, multicentric, substage a, B-cell lymphoma, not previously treated with chemotherapy. Treatment duration ranged from 1 to 8 weeks (median and mean, 3 weeks). Dogs were treated with either 10 (n = 6) or 7.5 (n = 7) mg/kg by mouth twice daily. One dog had a stable disease for 6 weeks. No complete or partial tumor responses were observed. Five dogs developed grade 3 and/or 4 metabolic abnormalities suggestive of hepatopathy with elevations in bilirubin, ALT, ALP, and/or AST. To evaluate the absorption of oral doxycycline in our study population, serum concentrations in 10 treated dogs were determined using liquid chromatography tandem mass spectrometry. Serum levels were variable and ranged from 3.6 to 16.6 µg/ml (median, 7.6 µg/ml; mean, 8.8 µg/ml). To evaluate the effect of doxycycline on canine lymphoma cell viability in vitro, trypan blue exclusion assay was performed on canine B-cell lymphoma cell lines (17-71 and CLBL) and primary B-cell lymphoma cells from the nodal tissue of four dogs. A doxycycline concentration of 6 µg/ml decreased canine lymphoma cell viability by 80%, compared to matched, untreated, control cells (mixed model analysis, p < 0.0001; Wilcoxon signed rank test, p = 0.0313). Although the short-term administration of oral doxycycline is not associated with the remission of canine lymphoma, combination therapy may be worthwhile if future research determines that doxycycline can alter cell survival pathways in canine lymphoma cells. Due to the potential for metabolic abnormalities, close monitoring is recommended with the use of this drug in tumor-bearing dogs. Additional research is needed to assess the tolerability of chronic doxycycline therapy.

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Section: Discussionmentioning

confidence: 99%

Metabolic Abnormalities Detected in Phase II Evaluation of Doxycycline in Dogs with Multicentric B-Cell Lymphoma

et al. 2018

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“…Since the concept of targeted therapeutics came in vogue, efforts were made to gain a better understanding of tumor biology and to identify tumor-specific therapeutic targets. In fact, most of these targets are also predictive biomarkers that give us information on whether a certain therapy would be beneficial to one patient but not to another [ 3 ]. Furthermore, acquiring a deep understanding of the signaling pathways in which critical targets are involved is fundamental to dig out molecular mechanisms that will likely inform us on response—or resistance—to therapy [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Bacteriophages as Therapeutic and Diagnostic Vehicles in Cancer

Foglizzo

Marchiò

2021

Pharmaceuticals

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Evolution of nanomedicine is the re-design of synthetic and biological carriers to implement novel theranostic platforms. In recent years, bacteriophage research favors this process, which has opened up new roads in drug and gene delivery studies. By displaying antibodies, peptides, or proteins on the surface of different bacteriophages through the phage display technique, it is now possible to unravel specific molecular determinants of both cancer cells and tumor-associated microenvironmental molecules. Downstream applications are manifold, with peptides being employed most of the times to functionalize drug carriers and improve their therapeutic index. Bacteriophages themselves were proven, in this scenario, to be good carriers for imaging molecules and therapeutics as well. Moreover, manipulation of their genetic material to stably vehiculate suicide genes within cancer cells substantially changed perspectives in gene therapy. In this review, we provide examples of how amenable phages can be used as anticancer agents, especially because their systemic administration is possible. We also provide some insights into how their immunogenic profile can be modulated and exploited in immuno-oncology for vaccine production.

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“…This could be applied to improve conventional biomarker and diagnostic measures, and provide better informed, personalized patient-specific recommendations. Using biomarkers to inform chemotherapeutic choices has remained difficult, even in cases where the measured marker is known to be related to a drug target [ 46 – 48 ]. This may be partly due to cancer heterogeneity, which limits the inferences that can be drawn from using a single, or a small number, of features.…”

Section: Discussionmentioning

confidence: 99%

A machine learning-based gene signature of response to the novel alkylating agent LP-184 distinguishes its potential tumor indications

Kathad¹,

Kulkarni²,

McDermott³

et al. 2021

BMC Bioinformatics

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Background Non-targeted cytotoxics with anticancer activity are often developed through preclinical stages using response criteria observed in cell lines and xenografts. A panel of the NCI-60 cell lines is frequently the first line to define tumor types that are optimally responsive. Open data on the gene expression of the NCI-60 cell lines, provides a unique opportunity to add another dimension to the preclinical development of such drugs by interrogating correlations with gene expression patterns. Machine learning can be used to reduce the complexity of whole genome gene expression patterns to derive manageable signatures of response. Application of machine learning in early phases of preclinical development is likely to allow a better positioning and ultimate clinical success of molecules. LP-184 is a highly potent novel alkylating agent where the preclinical development is being guided by a dedicated machine learning-derived response signature. We show the feasibility and the accuracy of such a signature of response by accurately predicting the response to LP-184 validated using wet lab derived IC50s on a panel of cell lines. Results We applied our proprietary RADR® platform to an NCI-60 discovery dataset encompassing LP-184 IC50s and publicly available gene expression data. We used multiple feature selection layers followed by the XGBoost regression model and reduced the complexity of 20,000 gene expression values to generate a 16-gene signature leading to the identification of a set of predictive candidate biomarkers which form an LP-184 response gene signature. We further validated this signature and predicted response to an additional panel of cell lines. Considering fold change differences and correlation between actual and predicted LP-184 IC50 values as validation performance measures, we obtained 86% accuracy at four-fold cut-off, and a strong (r = 0.70) and significant (p value 1.36e−06) correlation between actual and predicted LP-184 sensitivity. In agreement with the perceived mechanism of action of LP-184, PTGR1 emerged as the top weighted gene. Conclusion Integration of a machine learning-derived signature of response with in vitro assessment of LP-184 efficacy facilitated the derivation of manageable yet robust biomarkers which can be used to predict drug sensitivity with high accuracy and clinical value.

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Response biomarkers: re-envisioning the approach to tailoring drug therapy for cancer

Cited by 27 publications

References 75 publications

Metabolic Abnormalities Detected in Phase II Evaluation of Doxycycline in Dogs with Multicentric B-Cell Lymphoma

Metabolic Abnormalities Detected in Phase II Evaluation of Doxycycline in Dogs with Multicentric B-Cell Lymphoma

Bacteriophages as Therapeutic and Diagnostic Vehicles in Cancer

A machine learning-based gene signature of response to the novel alkylating agent LP-184 distinguishes its potential tumor indications

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