Mutation of SIVA, a candidate metastasis gene identified from clonally related bilateral breast cancers, promotes breast cancer cell spread in vitro and in vivo.

Metastasis is the most dreaded outcome after a breast cancer diagnosis, and little is known regarding what triggers or promotes breast cancer to spread distally, or how to prevent or eradicate metastasis effectively. Bilateral breast cancers are an uncommon form of breast cancers. In our study, a percentage of bilateral breast cancers were clonally related based on copy number variation profiling. Whole exome sequencing and comparative sequence analysis revealed that a limited number of somatic mutations were acquired in this "breast-to-breast" metastasis that might promote breast cancer distant spread. One somatic mutation acquired was SIVA-D160N that displayed pro-metastatic phenotypes in vivo and in vitro. Over-expression of SIVA-D160N promoted migration and invasion of human MB-MDA-231 breast cancer cells in vitro, consistent with a dominant negative interfering function. When introduced via tail vein injection, 231 cells over-expressing SIVA-D160N displayed enhanced distant spread on IVIS imaging. Over-expression of SIVA-D160N promoted invasion and anchorage independent growth of mouse 4T1 breast cancer cells in vitro. When introduced orthotopically via mammary fat pad injection in syngeneic Balb/c mice, over-expression of SIVA-D160N in 4T1 cells increased orthotopically implanted mammary gland tumor growth as well as liver metastasis. Clonally related bilateral breast cancers represented a novel system to investigate metastasis and revealed a role of SIVA-D160N in breast cancer metastasis. Further characterization and understanding of SIVA function, and that of its interacting proteins, may elucidate mechanisms of breast cancer metastasis, providing clinically useful biomarkers and therapeutic targets.

Can strength training or tai ji quan training reduce frailty in postmenopausal women treated with chemotherapy? A secondary data analysis of the GET FIT trial.

PURPOSE: To determine whether strength training or tai ji quan can reduce frailty in older, postmenopausal women treated with chemotherapy for cancer. METHODS: We conducted a secondary data analysis from a 3-arm, single-blind, randomized controlled trial where older (50-75 years), postmenopausal women cancer survivors were randomized to supervised group exercise programs: tai ji quan, strength training, or stretching control for 6 months. We assessed frailty using a 4-criteria model consisting of weakness, fatigue, inactivity, and slowness. Using logistic regression, we determined whether the frailty phenotype (pre-frailty or frailty) decreased post-intervention, how many and which frailty criteria decreased, and what characteristics identified women most likely to reduce frailty. RESULTS: Data from 386 women who completed baseline and 6-month testing were used (mean age of 62.0 ± 6.4 years). The odds of reducing overall frailty over 6 months were significantly higher in the strength training group compared to controls (OR [95%CI] 1.86 [1.09, 3.17]) but not for tai ji quan (1.44 [0.84, 2.50]). Both strength training (OR 1.99 [1.10, 3.65]) and tai ji quan (OR 2.10 [1.16, 3.84]) led to significantly higher odds of reducing ≥ 1 frailty criterion compared to controls. Strength training led to a three-fold reduction in inactivity (p < 0.01) and tai ji quan to a two-fold reduction in fatigue (p = 0.08) versus control. Higher baseline BMI, comorbidity score, and frailty status characterized women were more likely to reduce frailty than other women. CONCLUSIONS: Strength training appears superior to tai ji quan and stretching with respect to reducing overall frailty phenotype among postmenopausal women treated with chemotherapy for cancer, but tai ji quan favorably reduced the number of frailty criteria. TRIAL REGISTRATION: ClinicalTrials.gov identifier: GET FIT was registered as a clinical trial in clinicaltrials.gov: NCT01635413. IMPLICATIONS FOR CANCER SURVIVORS: Supervised, group exercise training that emphasizes strength training and/or tai ji quan may help combat accelerated aging and reduce frailty after cancer treatment.

Grb7 Ablation in Mice Improved Glycemic Control, Enhanced Insulin Signaling, and Increased Abdominal fat Mass in Females.

OBJECTIVES: Growth factor receptor bound protein 7 (GRB7) is a multidomain signaling adaptor. Members of the Grb7/10/14 family, specifically Gbrb10/14, have important roles in metabolism. We ablated the Grb7 gene in mice to examine its metabolic function. METHODS: Global ablation of Grb7 in FVB/NJ mice was generated. Growth, organ weight, food intake, and glucose homeostasis were measured. Insulin signaling was examined by Western blotting. Fat and lean body mass was measured by nuclear magnetic resonance, and body composition after fasting or high-fat diet was assessed. Energy expenditure was measured by indirect calorimetry. Expression of adiposity and lipid metabolism genes was measured by quantitative PCR. RESULTS: Grb7-null mice were viable, fertile, and without obvious phenotype. Grb7 ablation improved glycemic control and displayed sensitization to insulin signaling in the liver. Grb7-null females but not males had increased gonadal white adipose tissue mass. Following a 12-week high-fat diet, Grb7-null female mice gained fat body mass and developed relative insulin resistance. With fasting, there was less decrease in fat body mass in Grb7-null female mice. Female mice with Grb7 ablation had increased baseline food intake, less energy expenditure, and displayed a decrease in the expression of lipolysis and adipose browning genes in gonadal white adipose tissue by transcript and protein analysis. CONCLUSION: Our study suggests that Grb7 is a negative regulator of glycemic control. Our results reveal a role for Grb7 in female mice in the regulation of the visceral adipose tissue mass, a powerful predictor of metabolic dysfunction in obesity.

Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program.

One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.