# Characterization of the metastatic TIME by subcellular spatial profiling > **NIH NIH K99** · BAYLOR COLLEGE OF MEDICINE · 2024 · $125,000 ## Abstract Increased macrophage infiltration is associated with poorest outcome following neoadjuvant chemotherapy (CTX) in patients with triple negative breast cancer (TNBC). In contrast patients with increased tumor infiltrating lymphocytes (TILs) and fewer macrophages achieve a favorable pathological complete response (pCR). In the metastatic setting macrophages continue to accumulate to promote tumor survival and play a key role in therapeutic resistance. In order to understand the synergism between macrophages and tumor cells within the Tumor Immune Microenvironment (TIME), it is essential to have appropriate immunocompetent preclinical TNBC models that represent the high Epithelial-to-Mesenchymal (EMT)/ Macrophage phenotype observed in patients with a poor prognosis. We have developed and extensively characterized several genetically engineered mouse models that lack the p53 tumor suppressor gene that is most frequently lost or mutated in TNBC. These “claudin low” models closely phenocopy the high EMT/macrophage subtype observed in patients. However, because metastasis is the cause of mortality in the vast majority of TNBC patients, the critical question remains of whether macrophage targeted therapies can alter the TIME leading to long-term antitumor immunity in lung and liver metastases. Therefore, we hypothesize that therapeutic pressures applied on tumor and immune cells cause alterations to the TIME of lung and liver metastases generating subclonal populations that can lead to resistance and recurrence via the presence of Intratumoral Heterogeneity (ITH). We propose to spatially profile the metastatic TIME of lung and liver metastases following, anti-CSF1R (SNDX-ms6352) with CTX and newly approved anti-PD1 in order to identify mechanisms of resistance that lead to ITH. Further we will explore if targeting existing metastasis can recruit TILs including antigen presenting dendritic, B and T cells and convert “cold” tumors “hot” leading to a durable antitumor long-term response. To perform these studies we will directly introduce unlabeled tumor cells into the lung via tail vein injection or into the liver via the portal vein. Mice will be randomized and administered 4 weekly treatments of CTX with anti-CSF1R and anti-PD1. BrdU will be injected to detect lung and liver metastases. Spatial transcriptomics, Imaging mass cytometry, single cell RNA- sequencing, and flow cytometry, will be utilized to confirm macrophage depletion and study mechanisms of resistance within the metastatic TIME. Characterization of the lung and liver TIME in these preclinical models will be compared to results from matched metastasis in the AURORA clinical trial. We will then interrogate newly identified signaling mechanisms via genetic manipulation (RNAi and CRISPR) and potential small molecule inhibitors and analyze downstream signaling pathways by immunoblotting and qPCR. Novel gene signatures observed will be used to identify potential resistant human breast cancer cell ... ## Key facts - **NIH application ID:** 10949934 - **Project number:** 1K99GM155594-01 - **Recipient organization:** BAYLOR COLLEGE OF MEDICINE - **Principal Investigator:** Diego A Pedroza - **Activity code:** K99 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $125,000 - **Award type:** 1 - **Project period:** 2024-08-01 → 2026-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10949934 ## Citation > US National Institutes of Health, RePORTER application 10949934, Characterization of the metastatic TIME by subcellular spatial profiling (1K99GM155594-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10949934. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*