DR_MOMP delivers a system-based biomarker with significant potential as a prognostic tool for stage III CRC that significantly improves established histopathological risk factors.

3Purpose: Apoptosis is essential for chemotherapy responses. In this discovery and validation study, 4we evaluated the suitability of a mathematical model of apoptosis execution (APOPTO-CELL) as a 5 stand-alone signature and as a constituent of further refined prognostic stratification tools. 6Experimental Design: Apoptosis competency of primary tumor samples from n=120 stage III 7 colorectal cancer patients was calculated by APOPTO-CELL from measured protein concentrations of 35Among all clinicopathological, demographic, and molecular predictors analyzed, enriched-apoptosis 36 systems modeling delivered the highest ranking independent prognostic biomarker. Furthermore, 37 apoptosis modelling can be combined with molecular tumor subtyping to further refine risk 38 predictions. 39We report the clinical validation of diagnostic tools for stage III CRC patients that could deliver 40 superior quality of care by personalizing cancer treatment. 42Word count: 119.

Background: Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited therapeutic options. Epidermal growth factor receptor (EGFR) has been shown to be over-expressed in TNBC and represents a rational treatment target. Methods: We examined single agent and combination effects for afatinib and dasatinib in TNBC. We then determined IC50 and combination index values using Calcusyn. Functional analysis of single and combination treatments was performed using reverse phase protein array and cell cycle analysis. Finally, we determined the anticancer effects of the combination in vivo. Results: A total of 14 TNBC cell lines responded to afatinib with IC50 values ranging from 0.008 to 5.0 µM. Three cell lines, belonging to the basal-like subtype of TNBC, were sensitive to afatinib. The addition of afatinib enhanced response to the five other targeted therapies in HCC1937 and HDQP1 cells. The combination of afatinib with dasatinib caused the greatest growth inhibition in both cell lines. The afatinib/dasatinib combination was synergistic and/or additive in 13/14 TNBC cell lines. Combined afatinib/dasatinib treatment induced G1 cell cycle arrest. Reverse phase protein array results showed the afatinib/dasatinib combination resulted in efficient inhibition of both pERK(T202/T204) and pAkt(S473) signalling in BT20 cells, which was associated with the greatest antiproliferative effects. High baseline levels of pSrc(Y416) and pMAPK(p38) correlated with sensitivity to afatinib, whereas low levels of B-cell lymphoma 2 (Bcl2) and mammalian target of rapamycin (mTOR) correlated with synergistic growth inhibition by combined afatinib and dasatinib treatment. In vivo, the combination treatment inhibited tumour growth in a HCC1806 xenograft model. Conclusions: We demonstrate that afatinib combined with dasatinib has potential clinical activity in TNBC but warrants further preclinical investigation.

Background: An increasing number of anti-cancer therapeutic agents target specific mutant proteins that are expressed by many different tumor types. Successful use of these therapies is dependent on the presence or absence of somatic mutations within the patient's tumor that can confer clinical efficacy or drug resistance. Methods: The aim of our study was to determine the type, frequency, overlap and functional proteomic effects of potentially targetable recurrent somatic hotspot mutations in 47 cancer-related genes in multiple disease sites that could be potential therapeutic targets using currently available agents or agents in clinical development. Results: Using MassArray technology, of the 1300 patient tumors analysed 571 (43.9%) had at least one somatic mutation. Mutations were identified in 30 different genes. KRAS (16.5%), PIK3CA (13.6%) and BRAF (3.8%) were the most frequently mutated genes. Prostate (10.8%) had the lowest number of somatic mutations identified, while no mutations were identified in sarcoma. Ocular melanoma (90.6%), endometrial (72.4%) and colorectal (66.4%) tumors had the highest number of mutations. We noted high concordance between mutations in different parts of the tumor (94%) and matched primary and metastatic samples (90%). KRAS and BRAF mutations were mutually exclusive. Mutation co-occurrence involved mainly PIK3CA and PTPN11, and PTPN11 and APC. Reverse Phase Protein Array (RPPA) analysis demonstrated that PI3K and MAPK signalling pathways were more altered in tumors with mutations compared to wild type tumors. Conclusions: Hotspot mutational profiling is a sensitive, high-throughput approach for identifying mutations of clinical relevance to molecular based therapeutics for treatment of cancer, and could potentially be of use in identifying novel opportunities for genotype-driven clinical trials.