Abstract
Background“Biomarker-driven targeted therapy,” the practice of tailoring patients’ treatment to the expression/activity levels of disease-specific genes/proteins, remains challenging. For example, while the anti-ERBB2 monoclonal antibody, trastuzumab, was first developed using well-characterized, diverse in vitro breast cancer models (and is now a standard adjuvant therapy for ERBB2-positive breast cancer patients), trastuzumab approval for ERBB2-positive gastric cancer was largely based on preclinical studies of a single cell line, NCI-N87. Ensuing clinical trials revealed only modest patient efficacy, and many ERBB2-positive gastric cancer (GC) patients failed to respond at all (i.e., were inherently recalcitrant), or succumbed to acquired resistance.MethodTo assess mechanisms underlying GC insensitivity to ERBB2 therapies, we established a diverse panel of GC cells, differing in ERBB2 expression levels, for comprehensive in vitro and in vivo characterization. For higher throughput assays of ERBB2 DNA and protein levels, we compared the concordance of various laboratory quantification methods, including those of in vitro and in vivo genetic anomalies (FISH and SISH) and xenograft protein expression (Western blot vs. IHC), of both cell and xenograft (tissue-sectioned) microarrays.ResultsThe biomarker assessment methods strongly agreed, as did correlation between RNA and protein expression. However, although ERBB2 genomic anomalies showed good in vitro vs. in vivo correlation, we observed striking differences in protein expression between cultured cells and mouse xenografts (even within the same GC cell type). Via our unique pathway analysis, we delineated a signaling network, in addition to specific pathways/biological processes, emanating from the ERBB2 signaling cascade, as a potential useful target of clinical treatment. Integrated analysis of public data from gastric tumors revealed frequent (10 – 20 %) amplification of the genes NFKBIE, PTK2, and PIK3CA, each of which resides in an ERBB2-derived subpathway network.ConclusionOur comprehensive bioinformatics analyses of highly heterogeneous cancer cells, combined with tumor “omics” profiles, can optimally characterize the expression patterns and activity of specific tumor biomarkers. Subsequent in vitro and in vivo validation, of specific disease biomarkers (using multiple methodologies), can improve prediction of patient stratification according to drug response or nonresponse.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-016-2232-2) contains supplementary material, which is available to authorized users.
Highlights
A promising approach for the treatment of cancer is the use of “targeted” therapies for patients possessing specific genomic anomalies or overexpressing certain oncoproteins, resulting in attenuation of mitogenic signal pathways comprised of such targeted biomolecules [1]
Characteristics of a 220-GC tumor cohort and epidermal growth factor receptor-2 (ERBB2)-positive cell lines While ERBB2 expression is well correlated with poor breast cancer prognosis [27, 28], similar studies in gastric cancer (GC) have been inconsistent [29, 30]
While it is approved for GC in many nations, a phase III trastuzumab trial revealed only a modest clinical benefit for ERBB2-positive GC patients [20]
Summary
A promising approach for the treatment of cancer is the use of “targeted” therapies for patients possessing specific genomic anomalies or overexpressing certain oncoproteins, resulting in attenuation of mitogenic signal pathways comprised of such targeted biomolecules [1]. Other barriers to successful personalized medicine include inadequate “clinical utility,” referring to knowledge that a biomarker statistically segregates two patient populations (“analytical validation”), but that it does so in a clinical meaningful manner (“clinical validation”) [8]. Toward this objective, Hayes et al assert that an individual biomarker test must be “accurate, reproducible and reliable” and that regulatory bodies have lagged in vetting biomarkers to the same extent as new pharmaceuticals [8]. High-quality preclinical studies, using assays relevant to the clinical question at hand, are greatly needed
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