A recent validation study of an existing CDST for PDAC suggests it may over predict cancer risk in certain groups including older patients.
The benefit of such an approach lies in the possibility that differences in carcinogen metabolism may more accurately predict cancer risk.
Reduced forced vital capacity and pulmonary fibrosis are associated with an increased risk of developing lung cancer, suggesting that the extent of lung damage may predict subsequent cancer development [ 7].
This observation suggests that pSTAT5 levels in histopathologically 'normal' breast epithelia may predict breast cancer risk in women.
In the present study using human tumor specimens we show for the first time that DNA repair competence may predict breast cancer sensitivity to DNA damage-inducing chemotherapy.
Thus we reasoned that dyslipidemia-associated nucleotide polymorphisms (SNPs) on the APOA1/ C3/ A5 gene cluster may predict breast cancer risk and tumor progression.
One study has, furthermore, suggested that MUC-1 expression may predict prostate cancer recurrence after prostatectomy (Lapointe et al, 2004), although these results have been challenged by others (O'Connor et al, 2005; Zellweger et al, 2005).
Therefore, it is crucial to identify biomarkers that may be used to predict cancer cell sensitivity to molecular targeted agents to recognise a molecular profile of patient's tumour to guide appropriate therapeutic choices (Downward, 2006).
