Inhibition of the membrane repair protein annexin-A2 prevents tumor invasion and metastasis.

Cancer cells are exposed to major compressive and shearing forces during invasion and metastasis, leading to extensive plasma membrane damage. To survive this mechanical stress, they need to repair membrane injury efficiently. Targeting the membrane repair machinery is thus potentially a new way to prevent invasion and metastasis. We show here that annexin-A2 (ANXA2) is required for membrane repair in invasive breast and pancreatic cancer cells. Mechanistically, we show by fluorescence and electron microscopy that cells fail to reseal shear-stress damaged membrane when ANXA2 is silenced or the protein is inhibited with neutralizing antibody. Silencing of ANXA2 has no effect on proliferation in vitro, and may even accelerate migration in wound healing assays, but reduces tumor cell dissemination in both mice and zebrafish. We expect that inhibiting membrane repair will be particularly effective in aggressive, poor prognosis tumors because they rely on the membrane repair machinery to survive membrane damage during tumor invasion and metastasis. This could be achieved either with anti-ANXA2 antibodies, which have been shown to inhibit metastasis of breast and pancreatic cancer cells, or with small molecule drugs.

An immunological signature to predict outcome in patients with triple-negative breast cancer with residual disease after neoadjuvant chemotherapy.

BACKGROUND: When triple-negative breast cancer (TNBC) patients have residual disease after neoadjuvant chemotherapy (NACT), they have a high risk of metastatic relapse. With immune infiltrate in TNBC being prognostic and predictive of response to treatment, our aim was to develop an immunologic transcriptomic signature using post-NACT samples to predict relapse. MATERIALS AND METHODS: We identified 115 samples of residual tumors from post-NACT TNBC patients. We profiled the expression of 770 genes related to cancer microenvironment using the NanoString PanCancer IO360 panel to develop a prognostic transcriptomic signature, and we describe the immune microenvironments of the residual tumors. RESULTS: Thirty-eight (33%) patients experienced metastatic relapse. Hierarchical clustering separated patients into five clusters with distinct prognosis based on pathways linked to immune activation, epithelial-to-mesenchymal transition and cell cycle. The immune microenvironment of the residual disease was significantly different between patients who experienced relapse compared to those who did not, the latter having significantly more effector antitumoral immune cells, with significant differences in lymphoid subpopulations. We selected eight genes linked to immunity (BLK, GZMM, CXCR6, LILRA1, SPIB, CCL4, CXCR4, SLAMF7) to develop a transcriptomic signature which could predict relapse in our cohort. This signature was validated in two external cohorts (KMplot and METABRIC). CONCLUSIONS: Lack of immune activation after NACT is associated with a high risk of distant relapse. We propose a prognostic signature based on immune infiltrate that could lead to targeted therapeutic strategies to improve patient prognosis.

Specific immune landscapes and immune checkpoint expressions in histotypes and molecular subtypes of sarcoma.

Soft tissue sarcomas are a group of rare and aggressive connective tissue neoplasms for which curative therapeutic opportunities are limited in advanced phase. Clinical trials assessing immunotherapy in these tumors have so far reported limited efficacy. The objective of this study is to provide a description of the immunologic landscape of sarcomas to guide the next clinical trials of immunotherapy in these diseases. The gene expression profile of 93 immune checkpoint (ICP) and membrane markers (MM) of immune cells was analyzed in a series of 253 soft tissue sarcoma (synovial sarcoma, myxoid liposarcoma, sarcoma with complex genomic and GIST) using Agilent Whole Human Genome Microarrays. The unsupervised hierarchical clustering of gene expression level was found able to properly group patients according to the histological subgroup of sarcoma, indicating that each sarcoma subgroup is associated with a specific immune signature defined by its gene expression pattern. Using the prognostic impact of CIBERSORT signature on metastatic-free survival in each subgroup, specific target could be proposed for each of the four groups: Treg through ICOS and GITR in GIST, M0 macrophages in all four sarcoma subtypes, OX40 in SS, CD40 in GIST and SS. The immune landscape of sarcoma was found to be as heterogeneous as the histotypes and molecular subtypes, but strongly correlated to the histotype. Histotype adapted immunotherapeutic approaches in each sarcoma subtypes must be considered in view of these results, consistently with the already reported specific response of histotypes of ICPs.