Gene Expression Profiling of Tumors From Heavily Pretreated Patients With Metastatic Cancer for the Selection of Therapy

Rebollo, Joseba; Sureda, Manuel; Martı́nez, Emili; Fernández-Morejón, Francisco J.; Farre, J.; Muñoz, Vicente; Fernández-Latorre, Francisco; Manzano, Ramón González; Brugarolas, Antonio

doi:10.1097/coc.0000000000000116

Cited by 10 publications

(7 citation statements)

References 24 publications

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“…In addition, the companion diagnostics to detect targets are complicated and require confirmation using prospective clinical trials. Although several pilot studies using traditional molecular profiling methods, such as polymerase chain reaction (PCR), immunohistochemistry (IHC), fluorescent in situ hybridization (FISH), and microarrays demonstrate that patients could benefit from targeted therapy (19,20), these methods have limited coverage of oncogenes and oncoproteins, and thus, the prognostic benefits of molecular profiling-based therapy have been underestimated.…”

Section: Introductionmentioning

confidence: 99%

Molecular Profiling–Based Precision Medicine in Cancer: A Review of Current Evidence and Challenges

Zhang

Bai

et al. 2020

Front. Oncol.

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Matched therapy based on next-generation sequencing is now a part of routine care to guide the treatment of patients with advanced solid tumors. However, whether and to what extent patients can benefit from this strategy on a large scale remains uncertain. In the past decade, several clinical studies were performed in this field, among which only one was a randomized trial. We reviewed the literature on this topic and summarize the existing data about the efficacy of this treatment strategy. Currently, the evidence is promising but not solid. Multiple ongoing trials are also summarized. We also discuss the limitations of this treatment strategy and certain unsolved important problems, including how to select the sample and target level, how to interpret the results, and the problem of drug accessibility. All these issues should receive more attention in future clinical trial design and the application of target therapy in cancer treatment.

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Section: Introductionmentioning

confidence: 99%

Molecular Profiling–Based Precision Medicine in Cancer: A Review of Current Evidence and Challenges

Zhang

Bai

et al. 2020

Front. Oncol.

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“…The protocol followed for the obtention of the matched biopsies is the usual one at our institution and has been previously published [ 17 ]. Total RNA extraction was done with RNAeasy columns (QIAGEN), and the amount obtained was measured with the Nanodrop spectrophotometer (ND-1000).…”

Section: Patients and Methodsmentioning

confidence: 99%

A novel genomic signature predicting FDG uptake in diverse metastatic tumors

et al. 2018

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BackgroundBuilding a universal genomic signature predicting the intensity of FDG uptake in diverse metastatic tumors may allow us to understand better the biological processes underlying this phenomenon and their requirements of glucose uptake.MethodsA balanced training set (n = 71) of metastatic tumors including some of the most frequent histologies, with matched PET/CT quantification measurements and whole human genome gene expression microarrays, was used to build the signature. Selection of microarray features was carried out exclusively on the basis of their strong association with FDG uptake (as measured by SUVmean35) by means of univariate linear regression. A thorough bioinformatics study of these genes was performed, and multivariable models were built by fitting several state of the art regression techniques to the training set for comparison.ResultsThe 909 probes with the strongest association with the SUVmean35 (comprising 742 identifiable genes and 62 probes not matched to a symbol) were used to build the signature. Partial least squares using three components (PLS-3) was the best performing model in the training dataset cross-validation (root mean square error, RMSE = 0.443) and was validated further in an independent validation dataset (n = 13) obtaining a performance within the 95% CI of that obtained in the training dataset (RMSE = 0.645). Significantly overrepresented biological processes correlating with the SUVmean35 were identified beyond glycolysis, such as ribosome biogenesis and DNA replication (correlating with a higher SUVmean35) and cytoskeleton reorganization and autophagy (correlating with a lower SUVmean35).ConclusionsPLS-3 is a signature predicting accurately the intensity of FDG uptake in diverse metastatic tumors. FDG-PET might help in the design of specific targeted therapies directed to counteract the identified malignant biological processes more likely activated in a tumor as inferred from the SUVmean35 and also from its variations in response to antineoplastic treatments.Electronic supplementary materialThe online version of this article (10.1186/s13550-017-0355-3) contains supplementary material, which is available to authorized users.

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“…Meta-analysis of Phase I clinical trials completed during 2011-2013 showed that overall, trials that used molecular biomarker information to influence treatment plans gave better results than trials that did not 6 . However, most precision oncology treatments utilize only one or two medicines, and resistant clones frequently emerge, emphasizing the need to deliver personalized medicine as multiple agents combined [6][7][8][9][10][11] .…”

Section: Introductionmentioning

confidence: 99%

The Landscape of Receptor-Mediated Precision Cancer Combination Therapy: A Single-Cell Perspective

Ahmadi

Sukprasert

Vegesna

et al. 2021

Preprint

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The availability of single-cell transcriptomics data opens new opportunities for rational design of combination cancer treatments. Mining such data, we employed combinatorial optimization techniques to explore the landscape of optimal combination therapies in solid tumors including brain, head and neck, melanoma, lung, breast and colon cancers. We assume that each individual therapy can target any one of 1269 genes encoding cell surface receptors, which may be targets of CAR-T, conjugated antibodies or coated nanoparticle therapies. As a baseline case, we studied the killing of at least 80% of the tumor cells while sparing more than 90% of the non-tumor cells in each patient, as a putative regimen. We find that in most cancer types, personalized combinations composed of at most four targets are then sufficient. However, the number of distinct targets that one would need to assemble to treat all patients in a cohort accordingly would be around 10 in most cases. Further requiring that the target genes be also lowly expressed in healthy tissues uncovers qualitatively similar trends. However, as one asks for more stringent and selective killing beyond the baseline regimen we focused on, we find that the number of targets needed rises rapidly. Emerging individual promising receptor targets include PTPRZ1, which is frequently found in the optimal combinations for brain and head and neck cancers, and EGFR, a recurring target in multiple tumor types. In sum, this systematic single-cell based characterization of the landscape of combinatorial receptor-mediated cancer treatments establishes first of their kind estimates on the number of targets needed, identifying promising ones for future development.

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Gene Expression Profiling of Tumors From Heavily Pretreated Patients With Metastatic Cancer for the Selection of Therapy

Abstract: MP-guided therapy is feasible and seems to improve the clinical outcome of extensively pretreated patients but prospective and confirmatory trials are needed.

Cited by 10 publications

References 24 publications

Molecular Profiling–Based Precision Medicine in Cancer: A Review of Current Evidence and Challenges

Molecular Profiling–Based Precision Medicine in Cancer: A Review of Current Evidence and Challenges

A novel genomic signature predicting FDG uptake in diverse metastatic tumors

The Landscape of Receptor-Mediated Precision Cancer Combination Therapy: A Single-Cell Perspective

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