Challenges in Pharmacology of Anti-Cancer Drugs – The Search for Addictions

The goals of cancer therapy are easy to summarize: to identify patients at the earliest stage possible of the disease and to eradicate tumors without altering the overall health condition of the patients. The identification of cancer biomark-ers and tumor-selective drugs therefore represent obvious challenges for the next decades. In the genomics and proteomics era, the temptation is thus enormous to claim that the detection of oncogenes or oncoproteins participating in the progres-sion of a given cancer represents the main avenue to diagnose the disease at early stages and to subsequently target these genes or proteins in order to block tumor growth. However, although the last 30 years have been rich in grasping information about genetic features distinguishing cancer cells from normal cells through the identification of oncogenes and tumor suppressor genes (Hahn and Weinberg, 2002), the translation of this information in new drugs is limited to very few examples. Worse yet, old demons of conventional chemotherapy, namely tox-icity and resistance, are now dampening the original enthusiasm (Force et al., 2007; Knight et al., 2010). Imatinib/Gleevec, as an inhibitor of the bcr-abl fusion protein (Druker et al., 2001) and trastuzumab/Herceptin as inhibitor of the human epidermal growth factor receptor 2 (HER2) (Baselga et al., 1998) are two of the very first examples of the development of molecularly targeted therapies. These drugs have represented breakthroughs in the treatment of chronic myelogenous leukemia (CML) and breast cancers, respectively. The identification of patients who may benefit from these treatments was guided by the detection of corresponding genetic alterations: the Philadelphia chromosome consistently found in CML patients, formed by a recip-rocal translocation of DNA leading to a fusion gene between cABL (chromosome 9) and BCR (chromosome 22) (Bartram et al., 1983), and the overexpression of HER-2/neu as observed in 20–25% inva-sive breast cancers (Slamon et al., 1987). No doubt that these drugs administered to the right population of patients have increased response rates and survival. Still, we know today that the disease can find a way to advance despite the treatments: patients with BCR-ABL or HER2-positive cancers can still progress after receiving the above targeting drugs (often despite encourag-ing first responses). Potential mechanisms of resistance to oncogene-targeting drugs include bypass mechanisms and mutations of the targets (Gorre et al., 2001; Jones and Buzdar, 2009). In addition, potentially fatal cardiac toxicity is reported with trastuzu-mab (Telli et al., 2007) and although better tolerated, hematological (neutropenia), and non-hematological (skin rashes, edema, muscle cramps) toxicities are reported with imatinib (Deininger et al., 2005). The responses to these frustrating obser-vations may be of two kinds. The obvi-ous one is to understand the reasons for the heterogeneity in responses to a given drug, i.e., between patients but also for a given patient, between the early beneficial phases of a treatment and the late devel-opment of resistance. This should lead to rapid results with the apparition of second and third generations of drugs. Some are already making their way to the clinics. Drugs such as nilotinib and so-called ABL allosteric inhibitors may now for instance overcome resistance caused by some BCR-ABL mutations responsible for relapse after initial imatinib treatment (Weisberg et al., 2007; Zhang et al., 2010). This better under-standing should also stimulate the search for new predictive biomarkers to tailor the treatment to a patient’s individual genetic profile (for review, see Hanash et al., 2008; Sawyers, 2008). The need in this matter is so acute that there is an increasing consen-sus to integrate promising biomarkers, even if not clinically qualified, into early phase trials as exploratory and intermediary end-points (Yap et al., 2010). The second and non-exclusive option to tackle the limited amounts of safe and effi-cient drugs issued from our genetic knowl-edge of cancers is to identify additional filter(s) which should be implemented to select for better anticancer drugs. It is now clear that