Molecular biology of breast cancer metastasis: The use of mathematical models to determine relapse and to predict response to chemotherapy in breast cancer

Breast cancer mortality rates have shown only modest improvemen despite the advent of effective chemotherapeutic agents which have been administered to a large percentage of women with breast cancer. In an effort to improve breast cancer treatment strategies, a variety of mathematical models have been developed that describe the natural history of breast cancer and the effects of treatment on the cancer. These models help researchers to develop, quantify, and test various treatment hypotheses quickly and efficiently. The present review discusses several of these models, with a focus on how they have been used to predict the initiation time of metastatic growth, the effect of operative therapy on the growth of metastases, and the optimal administration strategy for chemotherapy

Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals.

Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the TERT and CLPTM1L genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis

Predictors of early relapse in postmenopausal women with hormone receptor-positive breast cancer in the BIG 1-98 trial

BACKGROUND: Aromatase inhibitors are considered standard adjuvant endocrine treatment of postmenopausal women with hormone receptor-positive breast cancer, but it remains uncertain whether aromatase inhibitors should be given upfront or sequentially with tamoxifen. Awaiting results from ongoing randomized trials, we examined prognostic factors of an early relapse among patients in the BIG 1-98 trial to aid in treatment choices. PATIENTS AND METHODS: Analyses included all 7707 eligible patients treated on BIG 1-98. The median follow-up was 2 years, and the primary end point was breast cancer relapse. Cox proportional hazards regression was used to identify prognostic factors. RESULTS: Two hundred and eighty-five patients (3.7%) had an early relapse (3.1% on letrozole, 4.4% on tamoxifen). Predictive factors for early relapse were node positivity (P < 0.001), absence of both receptors being positive (P < 0.001), high tumor grade (P < 0.001), HER-2 overexpression/amplification (P < 0.001), large tumor size (P = 0.001), treatment with tamoxifen (P = 0.002), and vascular invasion (P = 0.02). There were no significant interactions between treatment and the covariates, though letrozole appeared to provide a greater than average reduction in the risk of early relapse in patients with many involved lymph nodes, large tumors, and vascular invasion present. CONCLUSION: Upfront letrozole resulted in significantly fewer early relapses than tamoxifen, even after adjusting for significant prognostic factors