The mammary gland is composed of a complex cellular hierarchy with unusual postnatal plasticity. The identities of stem/progenitor cell populations, as well as tumour-initiating cells that give rise to breast cancer, are incompletely understood. Here we show that Lgr6 marks rare populations of cells in both basal and luminal mammary gland compartments in mice. Lineage tracing analysis showed that Lgr6 cells are unipotent progenitors, which expand clonally during puberty but diminish in adulthood. In pregnancy or following stimulation with ovarian hormones, adult Lgr6 cells regained proliferative potency and their progeny formed alveoli over repeated pregnancies. Oncogenic mutations in Lgr6 cells resulted in expansion of luminal cells, culminating in mammary gland tumours. Conversely, depletion of Lgr6 cells in the MMTV-PyMT model of mammary tumorigenesis significantly impaired tumour growth. Thus, Lgr6 marks mammary gland progenitor cells that can initiate tumours, and cells of luminal breast tumours required for efficient tumour maintenance.

No abstract

Metastasis-Associated in Colon Cancer 1 (MACC1) is a strong prognostic biomarker inducing proliferation, migration, invasiveness, and metastasis of cancer cells. The context of MACC1 dysregulation in cancers is, however, still poorly understood. Here, we investigated whether chromosomal instability and somatic copy number alterations (SCNA) frequently occurring in CRC contribute to MACC1 dysregulation, with prognostic and predictive impacts. Using the Oncotrack and Charité CRC cohorts of CRC patients, we showed that elevated MACC1 mRNA expression was tightly dependent on increased MACC1 gene SCNA and was associated with metastasis and shorter metastasis free survival. Deep analysis of the COAD-READ TCGA cohort revealed elevated MACC1 expression due to SCNA for advanced tumors exhibiting high chromosomal instability (CIN), and predominantly classified as CMS2 and CMS4 transcriptomic subtypes. For that cohort, we validated that elevated MACC1 mRNA expression correlated with reduced disease-free and overall survival. In conclusion, this study gives insights into the context of MACC1 expression in CRC. Increased MACC1 expression is largely driven by CIN, SCNA gains, and molecular subtypes, potentially determining the molecular risk for metastasis that might serve as a basis for patient-tailored treatment decisions.

No abstract

Pancreatic cancer (PC) is the 12th most common cancer worldwide. Despite a large panel of chemo- and targeted therapeutics options, patient prognosis remains poor with a 5-years overall survival below 10%. Thus, there is still a critical need to develop more efficient therapeutic alternatives. Antibody drug conjugates (ADC) and small molecule drug conjugates (SMDC) combine the oncolytic activity of highly potent chemotherapies with the target specificity of an antibody or a small molecule. Both ADC and SMDC are of increasing interest for cancer treatment, as they allow more specific delivery of chemotherapies to the tumor site. Facing the clinical needs for PC treatment, here we present an in-silico analysis to reveal specific targets for further ADC/SMDC development. 4HF Biotec has developed a proprietary platform connecting large clinical, OMICS and drug sensitivity data from various sources. It includes annotation for more than 1,800 preclinical models (cell lines, cell line-derived xenografts, and patient-derived xenografts), up to 11,000 patient tumors and 22,000 normal tissues (TCGA, GTEx and various GEO datasets). For tumor target discovery purposes, we designed and implemented the platform with specific analytics tools. To identify specific targets for PC, we first decided to analyze preclinical models, to focus on genes expressed by tumor cells and not by stroma cells. This aspect is particularly important in the context of PC which often have a high stroma content. Differential gene expression analysis of 113 PC preclinical models versus 1,737 tumor models from up to 30 tumor entities revealed 327 PC specific genes potentially targetable. Then, a similar analysis was performed by testing TCGA patient tumors (179 pancreatic tumors vs 9,521 patient tumors from other entities) and revealed 1,292 pancreatic specific genes. Finally, PC patient tumors were compared to 709 samples from various normal organs allowing to identify 1,156 tumor specific genes. At the intersection of these three analyses, we identified 56 PC-specific target candidates for ADC/SMDC development. Among the top candidates, MUCL3 (mucin like 3) was one of the most promising genes. Its mRNA expression is almost exclusively restricted to pancreatic and stomach samples in both preclinical models and TCGA patient tumors. It is overall not frequently expressed by normal tissues, and restricted to subsets of stomach, esophagus, and lung samples. The gene encodes for a transmembrane protein with a long weakly glycosylated extracellular part. A detailed analysis of the protein characteristics and expression modalities will be shown. The present work demonstrates that our in silico platform helps to identify promising targets for PC treatment using ADC/SMDC approaches. Our analyses revealed MUCL3 as one of the top candidates, further analyses will be needed to determine its druggability using small molecules or antibodies. Citation Format: Anne-Lise Peille, Alexandra Musch, Hoor Al-Hasani, Heinz-Herbert Fiebig, Vincent Vuaroqueaux. Identification of novel targets for the treatment of pancreatic cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1173.