The consumption of antidepressants, especially selective serotonine reuptake inhibitors (SSRI) has been increasing. Because a large fraction of the population is exposed, even a small excess of risk with respect to cancer should be considered. We carried out a record linkage study in Finland utilizing nationwide databases of reimbursed medication and cancer. The study population included all antidepressant drug (AD) users in Finland who had purchased at least 1 prescription between 1998 and 2005, and who had no cancer diagnosis at the date of first purchase. A control population without AD usage (matched by age and sex) was also included. Data consisted of 418,588 pairs of individuals that cumulated 3.3 million person‐years with an average of 4.0 years of follow‐up. 19,365 cancer cases were observed. The most frequent cancers were breast, prostate, lung, colon, and brain cancer. In general, only few associations between the utilization of AD and cancer could be detected. Over four years exposure to AD showed a weak association with increased colon and breast cancer incidence, which could have been caused by bias. As conclusion, no clear evidence of neither beneficial nor harmful association between usage of antidepressant and cancer was found.

Multiple myeloma (MM) is a heterogeneous hematologic malignancy involving the proliferation of plasma cells derived by different genetic events contributing to the development, progression, and prognosis of this disease. Despite improvement in treatment strategies of MM over the last decade, the disease remains incurable. All efforts are currently focused on understanding the prognostic markers of the disease hoping to incorporate the new therapeutic modalities to convert the disease into curable one. We present this comprehensive review to summarize the current standard prognostic markers used in MM along with novel techniques that are still in development and highlight their implications in current clinical practice.

There is unmet need for prediction of treatment response for chronic myeloid leukemia (CML) patients. The present study aims to identify disease-specific/disease-associated protein biomarkers detectable in bone marrow and peripheral blood for objective prediction of individual’s best treatment options and prognostic monitoring of CML patients. Bone marrow plasma (BMP) and peripheral blood plasma (PBP) samples from newly-diagnosed chronic-phase CML patients were subjected to expression-proteomics using quantitative two-dimensional gel electrophoresis (2-DE) and label-free liquid chromatography tandem mass spectrometry (LC-MS/MS). Analysis of 2-DE protein fingerprints preceding therapy commencement accurately predicts 13 individuals that achieved major molecular response (MMR) at 6 months from 12 subjects without MMR (No-MMR). Results were independently validated using LC-MS/MS analysis of BMP and PBP from patients that have more than 24 months followed-up. One hundred and sixty-four and 138 proteins with significant differential expression profiles were identified from PBP and BMP, respectively and only 54 proteins overlap between the two datasets. The protein panels also discriminates accurately patients that stay on imatinib treatment from patients ultimately needing alternative treatment. Among the identified proteins are TYRO3, a member of TAM family of receptor tyrosine kinases (RTKs), the S100A8, and MYC and all of which have been implicated in CML. Our findings indicate analyses of a panel of protein signatures is capable of objective prediction of molecular response and therapy choice for CML patients at diagnosis as ‘personalized-medicine-model’.

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