ADAM12 expression is upregulated in cancer cells upon radiation and constitutes a prognostic factor in rectal cancer patients following radiotherapy.

Radiotherapy is one of the most common cancer treatments, yet, some patients require high doses to respond. Therefore, the development of new strategies leans toward personalizing therapy to avoid unnecessary burden on cancer patients. This approach prevents the administration of ineffective treatments or uses combination strategies to increase the sensitivity of cancer cells. ADAM12 has been shown to be upregulated in many cancers and correlate with poor survival and chemoresistance, thus making it a potential candidate responsible for radioresistance. Here, we show that ADAM12 expression is upregulated in response to irradiation in both mouse and human cancer cells in vitro, as well as in tumor tissues from rectal cancer patients. Interestingly, the expression of ADAM12 following radiotherapy correlates with the initial disease stage and predicts the response of rectal cancer patients to the treatment. While we found no cell-autonomous effects of ADAM12 on the response of colon cancer cells to irradiation in vitro, depletion of ADAM12 expression markedly reduced the tumor growth of irradiated cancer cells when subcutaneously transplanted in syngeneic mice. Interestingly, loss of cancer cell-derived ADAM12 expression increased the number of CD31+FAP- cells in murine tumors. Moreover, conditioned medium from ADAM12-/- colon cancer cells led to increased tube formation when added to endothelial cell cultures. Thus, it is tempting to speculate that altered tumor vascularity may be implicated in the observed effect of ADAM12 on response to radiotherapy in rectal cancer. We conclude that ADAM12 represents a promising prognostic factor for stratification of rectal cancer patients receiving radiotherapy and suggest that targeting ADAM12 in combination with radiotherapy could potentially improve the treatment response.

Identification of Atypical Circulating Tumor Cells with Prognostic Value in Metastatic Breast Cancer Patients.

Circulating tumor cells have a strong potential as a quasi-non-invasive tool for setting up a precision medicine strategy for cancer patients. Using a second-generation "filtration-based" technology to isolate CTCs, the Screencell™ technology (Sarcelles, France), we performed a large and simultaneous analysis of all atypical circulating tumor cells (aCTCs) isolated from the blood of metastatic breast cancer (mBC) patients. We correlated their presence with clinicopathological and survival data. We included 91 mBC patients from the PERMED-01 study. The median number of aCTCs was 8.3 per mL of blood. Three subsets of aCTCs, absent from controls, were observed in patients: single (s-aCTCs), circulating tumor micro-emboli (CTM), and giant-aCTCs (g-aCTCs). The presence of g-aCTCs was associated with shorter progression free survival and overall survival. This study highlights the heterogeneity of aCTCs in mBC patients both at the cytomorphological and molecular levels. In addition, it suggests the usefulness of the g-aCTC subset as a prognostic factor and a potential stratification tool to treat late-stage mBC patients and improve their chances of benefiting from early clinical trials.

Sensitive and easy screening for circulating tumor cells by flow cytometry.

Circulating Tumor Cells (CTCs) represent an easy, repeatable and representative access to information regarding solid tumors. However, their detection remains difficult because of their paucity, their short half-life, and the lack of reliable surface biomarkers. Flow cytometry (FC) is a fast, sensitive and affordable technique, ideal for rare cells detection. Adapted to CTCs detection (i.e. extremely rare cells), most FC-based techniques require a time-consuming pre-enrichment step, followed by a 2-hours staining procedure, impeding on the efficiency of CTCs detection. We overcame these caveats and reduced the procedure to less than one hour, with minimal manipulation. First, cells were simultaneously fixed, permeabilized, then stained. Second, using low-speed FC acquisition conditions and two discriminators (cell size and pan-cytokeratin expression), we suppressed the pre-enrichment step. Applied to blood from donors with or without known malignant diseases, this protocol ensures a high recovery of the cells of interest independently of their epithelial-mesenchymal plasticity and can predict which samples are derived from cancer donors. This proof-of-concept study lays the bases of a sensitive tool to detect CTCs from a small amount of blood upstream of in-depth analyses.

A 25-gene classifier predicts overall survival in resectable pancreatic cancer.

BACKGROUND: Pancreatic carcinoma is one of the most lethal human cancers. In patients with resectable tumors, surgery followed by adjuvant chemotherapy is the only curative treatment. However, the 5-year survival is 20%. Because of a strong metastatic propensity, neoadjuvant chemotherapy is being tested in randomized clinical trials. In this context, improving the selection of patients for immediate surgery or neoadjuvant chemotherapy is crucial, and high-throughput molecular analyses may help; the present study aims to address this. METHODS: Clinicopathological and gene expression data of 695 pancreatic carcinoma samples were collected from nine datasets and supervised analysis was applied to search for a gene expression signature predictive for overall survival (OS) in the 601 informative operated patients. The signature was identified in a learning set of patients and tested for its robustness in a large independent validation set. RESULTS: Supervised analysis identified 1400 genes differentially expressed between two selected patient groups in the learning set, namely 17 long-term survivors (LTS; ≥ 36 months after surgery) and 22 short-term survivors (STS; dead of disease between 2 and 6 months after surgery). From these, a 25-gene prognostic classifier was developed, which identified two classes ("STS-like" and "LTS-like") in the independent validation set (n = 562), with a 25% (95% CI 18-33) and 48% (95% CI 42-54) 2-year OS (P = 4.33 × 10-9), respectively. Importantly, the prognostic value of this classifier was independent from both clinicopathological prognostic features and molecular subtypes in multivariate analysis, and existed in each of the nine datasets separately. The generation of 100,000 random gene signatures by a resampling scheme showed the non-random nature of our prognostic classifier. CONCLUSION: This study, the largest prognostic study of gene expression profiles in pancreatic carcinoma, reports a 25-gene signature associated with post-operative OS independently of classical factors and molecular subtypes. This classifier may help select patients with resectable disease for either immediate surgery (the LTS-like class) or neoadjuvant chemotherapy (the STS-like class). Its assessment in the current prospective trials of adjuvant and neoadjuvant chemotherapy trials is warranted, as well as the functional analysis of the classifier genes, which may provide new therapeutic targets.

Lactate Detection in Tumor Cell Cultures Using Organic Transistor Circuits.

A biosensing platform based on an organic transistor circuit for metabolite detection in highly complex biological media is introduced. The sensor circuit provides inherent background subtraction allowing for highly specific, sensitive lactate detection in tumor cell cultures. The proposed sensing platform paves the way toward rapid, label-free, and cost-effective clinically relevant in vitro diagnostic tools.

Prognostic value of PDL1 expression in pancreatic cancer.

Pancreatic cancer is one of the most aggressive human cancers. PD1/PDL1-inhibitors recently showed promising results in different cancers with correlation between PDL1 tumor expression and responses. Expression of programmed cell death receptor ligand 1 (PDL1) has been scarcely studied in pancreatic cancer. In this retrospective study, we analyzed PDL1 mRNA expression in 453 clinical pancreatic cancer samples profiled using DNA microarrays and RNASeq. Compared to normal pancreatic samples, PDL1 expression was upregulated in 19% of cancer samples. Upregulation was not associated with clinicopathological features such as patients' age and sex, pathological type, tumor size, lymph node status, and grade, but was associated with shorter disease-free survival and overall survival in multivariate analyses. Analysis of correlations with biological parameters showed that PDL1 upregulation was associated with some degree of lymphocyte infiltration and signs of anti-tumor T-cell response, but to a lesser extent than what has been reported in breast cancer and GIST. PDL1-up pancreatic cancers displayed profiles of lymphocyte exhaustion, were more enriched in inhibitory molecules and pro-tumor populations (Tregs with upregulation of FOXP3 and IL10, myeloid-derived suppressor cells with upregulation of CD33 and S100A8/A9), and demonstrated a down-modulation of most MHC class I members (HLA-A/B/C, HLA-E/F/G) suggestive of a defect in antigen processing and presentation. In conclusion, our results suggest that PDL1 expression might refine the prediction of metastatic relapse in operated pancreatic cancer, and that PD1/PDL1 inhibitors might reactivate inhibited T-cells to increase the anti-tumor immune response in PDL1-upregulated tumors.