NTHL1 is a recessive cancer susceptibility gene.

In search of novel breast cancer (BC) risk variants, we performed a whole-exome sequencing and variant analysis of 69 Finnish BC patients as well as analysed loss-of-function variants identified in DNA repair genes in the Finns from the Genome Aggregation Database. Additionally, we carried out a validation study of SERPINA3 c.918-1G>C, recently suggested for BC predisposition.

A search for modifying genetic factors in CHEK2:c.1100delC breast cancer patients.

The risk of breast cancer associated with CHEK2:c.1100delC is 2-threefold but higher in carriers with a family history of breast cancer than without, suggesting that other genetic loci in combination with CHEK2:c.1100delC confer an increased risk in a polygenic model.

The relationship between anger regulation, mood, pain, and pain-related disability in women treated for breast cancer.

Objective: Anger, depressive symptoms, and anxiety are known reactions to cancer and suggested to modulate pain experience. We examined the association between anger regulation, mood, and pain in 952 breast cancer patients followed for 3 years.

Methods: Preoperatively, the patients completed questionnaires about depressive symptoms (BDI), state anxiety (STAI), anger regulation (STAXI-2), and pains in the surgical and other areas.

Cancer Patients' Symptom Burden and Health-related Quality of Life (HRQoL) at Tertiary Cancer Center from 2006 to 2013: A Cross-sectional Study.

Background/aim: To observe changes in symptoms and health-related quality of life (HRQoL) over 7 years among cancer patients at different stages of the disease.

Patients And Methods: This prospective cross-sectional study at the Helsinki University Hospital Cancer Center, was carried out in 2006 and repeated in 2013. All participants filled in the EORTC-QLQ-C30 questionnaire.

Machine-learning-derived classifier predicts absence of persistent pain after breast cancer surgery with high accuracy.

Background: Prevention of persistent pain following breast cancer surgery, via early identification of patients at high risk, is a clinical need. Supervised machine-learning was used to identify parameters that predict persistence of significant pain.

Methods: Over 500 demographic, clinical and psychological parameters were acquired up to 6 months after surgery from 1,000 women (aged 28-75 years) who were treated for breast cancer.