The role of extreme phenotype selection studies in the identification of clinically relevant genotypes in cancer research

Abstract

The investigation of genetic alterations that may be related to the prognosis of patients with malignant disease has become a frequently used strategy in recent years. Although some conclusions have been reached in certain studies, the complexity and the multifactorial nature of most neoplastic diseases makes it difficult to identify clinically relevant information, and the results of some studies have been of borderline significance or have been conflicting. In contrast, the identification and the study of patients or families with very characteristic phenotypes have yielded outstanding results in the identification of the genetic characteristics underlying such phenotypes. Although, in most cases, the individuals who are selected for these types of studies are characterized by a negative phenotype (i.e., individuals who are at increased risk for developing a specific disease), a few studies have been directed toward individuals with phenotypes that imply an unusually good prognosis (i.e., individuals who present with a decreased risk for developing specific diseases despite an important exposure to well-known risk factors). Therefore, it seems logical to develop this strategy further as a valid methodology for the study of other diseases, such as cancer. The study of individuals with phenotypes that imply an extremely good prognosis, such as long-term survivors of theoretically incurable malignancies or individuals who seem to be protected against a certain neoplastic disorder despite having a markedly increased risk for its development, may unveil genetic alterations that explain such characteristic phenotypes and may provide potentially useful therapeutic targets against these diseases. Cancer 2002;95:1605-10.

Identification of TNF-α and MMP-9 as potential baseline predictive serum markers of sunitinib activity in patients with renal cell carcinoma using a human cytokine array

“…The methodology of extreme phenotype selection was used for this study (Perez-Gracia et al, 2002). Three patients with very marked clinical responses to sunitinib and three with clear progressions, despite adequate performance status, absence of comorbidities and correct treatment administration, were selected by the attending clinicians.…”

“…Highthroughput techniques have the advantage of being able to evaluate several molecular factors at one time, but their interpretation and their translation into clinical practice is somewhat cumbersome. The selection and study of individuals with very characteristic and clinically relevant phenotypes has been proposed as a methodology that may help to characterize the factors underlying such phenotypes (Perez-Gracia et al, 2002). This strategy consists of selecting and screening with highthroughput techniques of those patients presenting the most informative clinical features, rather than whole unselected series of patients, to improve the probability of finding factors that might be linked with such phenotypes.…”

Crude phenolic extracts from extra virgin olive oil circumvent de novo breast cancer resistance to HER1/HER2-targeting drugs by inducing GADD45-sensed cellular stress, G2/M arrest and hyperacetylation of Histone H3

“…because of the lack of appropriate model systems, one can anticipate that this issue could be difficult to study and, accordingly, the precise molecular mechanisms underlying de novo non-sensitivity to trastuzumab remain largely obscure. It is well established that the identification and the study with high-throughput techniques of phenotypes such as long-term survivors of untreatable malignancies, individuals protected against certain cancer diseases despite having a markedly risk for their development, or cancer patients displaying striking responses following a specific treatment, not only may unveil specific genetic/molecular alterations ultimately causing such characteristic phenotypes but may provide further innovative and clinically valuable therapeutic targets against these disease (11,12). We recently hypothesized that, in a counterintuitive manner, we could take advantage of extreme phenotype selection studies in the identification of clinically relevant molecular features explaining breast cancer resistance to HER2-targeted therapies ab initio.…”

Extreme clinical chemistry

“…Biomarkers can be used to quantify extreme phenotypes and improve the efficiency of gene discovery [17,18]. Recent studies have applied this gene discovery approach by using extremes in various biomarkers such as: HDL [19,20]; apoA-I [19]; TNF-alpha [21]; CK-MB [22]; and CD4 cell count [23].…”

“…The integration of extremes in biomarker levels with genomic approaches has created a new field of extreme phenotype study design [17,18]. Biomarkers can be used to quantify extreme phenotypes and improve the efficiency of gene discovery [17,18].…”