A review of prognostic and predictive biomarkers in breast cancer.

Breast cancer (BC) is a common cancer all over the world that affects women. BC is one of the leading causes of cancer mortality in women, which today has decreased with the advancement of technology and new diagnostic and therapeutic methods. BCs are histologically divided into in situ and invasive carcinoma, and both of them can be divided into ductal and lobular. The main function after the diagnosis of invasive breast cancer is which patient should use chemotherapy, which patient should receive adjuvant therapy, and which should not. If the decision is for adjuvant therapy, the next challenge is to identify the most appropriate treatment or combination of treatments for a particular patient. Addressing the first challenge can be helped by prognostic biomarkers, while addressing the second challenge can be done by predictive biomarkers. Among the molecular markers related to BC, ER, PR, HER2, and the Mib1/Ki-67 proliferation index are the most significant ones and are tightly confirmed in the standard care of all primary, recurrent, and metastatic BC patients. CEA and CA-15-3 antigens are the most valuable markers of serum tumors in BC patients. Determining the series of these markers helps monitor response to the treatment and early detection of recurrence or metastasis. miRNAs have been demonstrated to be intricate in mammary gland growth, proliferation, and formation of BC known to be incriminated in BC biology. By combining established prognostic factors with valid prognostic/predicted biomarkers, we can start the journey to personalized treatment for every recently diagnosed BC patient.

Assessment of Imprecise Small Photon Beam Modeling by Two Treatment Planning System Algorithms.

BACKGROUND: Dosimetric accuracy in intensity-modulated radiation therapy (IMRT) is the main part of quality assurance program. Improper beam modeling of small fields by treatment planning system (TPS) can lead to inaccuracy in treatment delivery. This study aimed to evaluate of the dose delivery accuracy at small segments of IMRT technique using two-dimensional (2D) array as well as evaluate the capability of two TPSs algorithm in modeling of small fields. METHODS: Irradiation were performed using 6 MV photon beam of Siemens Artiste linear accelerator. Dosimetric behaviors of two dose calculation algorithms, namely, collapsed cone convolution/superposition (CCCS) and full scatter convolution (FSC) in small segments of IMRT plans were analyzed using a 2D diode array and gamma evaluation. RESULTS: Comparisons of measurements against TPSs calculations showed that percentage difference of output factors of small fields were 2% and 15% for CCCS and FSC algorithm, respectively. Gamma analysis of calculated dose distributions by TPSs against those measured by 2D array showed that in passing criteria of 3 mm/3%, the mean pass rate for all segment sizes is higher than 95% except for segment sizes below 3 cm × 3 cm optimized by TiGRT TPS. CONCLUSIONS: High pass rate of gamma index (95%) achieved in planned small segments by Prowess relative to results obtained with TiGRT. This study showed that the accuracy of small field modeling differs between two dose calculation algorithms.