Cancer Science & Therapy

Lung cancer is the leading cause of cancer related death globally, accounting for approximately. Prognosis used to be generally very poor, with 5-year survival rates ranging between different countries. Numerous prognostic factors have been investigated which include tumorrelated but also patient-related factors, as well as smoking status and cancer treatment. For example, a later stage at diagnosis, male gender and current smoking at diagnosis have been shown to predict particularly poor prognosis in lung cancer patients. Social inequalities in lung cancer survival have been reported for countries with and without universal health care systems. Irrespective of the type of socioeconomic measurement, studies reported lower survival for lower socioeconomic groups. Stage at diagnosis, comorbidity, cancer therapy and smoking status has been found to at least partly explain the association between socioeconomic status and lung cancer survival. A study including lung cancer patients resident in Denmark reported smaller hazard ratio estimates when additionally adjusting for stage at diagnosis, first-line treatment and comorbidities.

Pancreatic ductal adenocarcinoma (PDAC), the more common form of pancreatic cancer (PC), is dominated by mutations in four well-known cancer genes (KRAS, TP53, CDKN2A, and SMAD4). Pancreatic cancer (PC) has recently overtaken breast cancer to become the third leading cause of cancer death in the United States1, and it is predicted to become the second leading cause within a decade. Biomarkers that predict response to novel and established treatments are urgently needed and must extend beyond the detection of point mutations in coding genes and low-prevalence actionable genomic events in order to better select patients for clinical trials. This diversity may explain the lack of progress with targeted therapies because actionable genomic events being targeted therapeutically are present in only a small proportion of unselected participants in clinical trials. To better select patients for clinical trials, biomarkers that predict response to novel and established treatments must extend beyond the detection of point mutation