SCCA1/SERPINB3 suppresses antitumor immunity and blunts therapy-induced T cell responses via STAT-dependent chemokine production.

Patients with cancer who have high serum levels of squamous cell carcinoma antigen 1 (SCCA1, now referred to as SERPINB3) commonly experience treatment resistance and have a poor prognosis. Despite being a clinical biomarker, the modulation of SERPINB3 in tumor immunity is poorly understood. We found positive correlations of SERPINB3 with CXCL1, CXCL8 (CXCL8/9), S100A8, and S100A9 (S100A8/A9) myeloid cell infiltration through RNA-Seq analysis of human primary cervical tumors. Induction of SERPINB3 resulted in increased CXCL1/8 and S100A8/A9 expression, which promoted monocyte and myeloid-derived suppressor cell (MDSC) migration in vitro. In mouse models, Serpinb3a tumors showed increased MDSC and tumor-associated macrophage (TAM) infiltration, contributing to T cell inhibition, and this was further augmented upon radiation. Intratumoral knockdown (KD) of Serpinb3a resulted in tumor growth inhibition and reduced CXCL1 and S100A8/A expression and MDSC and M2 macrophage infiltration. These changes led to enhanced cytotoxic T cell function and sensitized tumors to radiotherapy (RT). We further revealed that SERPINB3 promoted STAT-dependent expression of chemokines, whereby inhibition of STAT activation by ruxolitinib or siRNA abrogated CXCL1/8 and S100A8/ A9 expression in SERPINB3 cells. Patients with elevated pretreatment SCCA levels and high phosphorylated STAT3 (p-STAT3) had increased intratumoral CD11b+ myeloid cells compared with patients with low SCCA levels and p-STAT3, who had improved overall survival after RT. These findings provide a preclinical rationale for targeting SERPINB3 in tumors to counteract immunosuppression and improve the response to RT.

p38MAPKα Stromal Reprogramming Sensitizes Metastatic Breast Cancer to Immunotherapy.

Metastatic breast cancer is an intractable disease that responds poorly to immunotherapy. We show that p38MAPKα inhibition (p38i) limits tumor growth by reprogramming the metastatic tumor microenvironment in a CD4+ T cell-, IFNγ-, and macrophage-dependent manner. To identify targets that further increased p38i efficacy, we utilized a stromal labeling approach and single-cell RNA sequencing. Thus, we combined p38i and an OX40 agonist that synergistically reduced metastatic growth and increased overall survival. Intriguingly, patients with a p38i metastatic stromal signature had better overall survival that was further improved by the presence of an increased mutational load, leading us to ask if our approach would be effective in antigenic breast cancer. The combination of p38i, anti-OX40, and cytotoxic T-cell engagement cured mice of metastatic disease and produced long-term immunologic memory. Our findings demonstrate that a detailed understanding of the stromal compartment can be used to design effective antimetastatic therapies. SIGNIFICANCE: Immunotherapy is rarely effective in breast cancer. We dissected the metastatic tumor stroma, which revealed a novel therapeutic approach that targets the stromal p38MAPK pathway and creates an opportunity to unleash an immunologic response. Our work underscores the importance of understanding the tumor stromal compartment in therapeutic design. This article is highlighted in the In This Issue feature, p. 1275.

DANSR: A Tool for the Detection of Annotated and Novel Small RNAs.

Existing small noncoding RNA analysis tools are optimized for processing short sequencing reads (17-35 nucleotides) to monitor microRNA expression. However, these strategies under-represent many biologically relevant classes of small noncoding RNAs in the 36-200 nucleotides length range (tRNAs, snoRNAs, etc.). To address this, we developed DANSR, a tool for the detection of annotated and novel small RNAs using sequencing reads with variable lengths (ranging from 17-200 nt). While DANSR is broadly applicable to any small RNA dataset, we applied it to a cohort of matched normal, primary, and distant metastatic colorectal cancer specimens to demonstrate its ability to quantify annotated small RNAs, discover novel genes, and calculate differential expression. DANSR is available as an open source tool.

Pan-Cancer Analysis Reveals Recurrent BCAR4 Gene Fusions across Solid Tumors.

Chromosomal rearrangements often result in active regulatory regions juxtaposed upstream of an oncogene to generate an expressed gene fusion. Repeated activation of a common downstream partner-with differing upstream regions across a patient cohort-suggests a conserved oncogenic role. Analysis of 9,638 patients across 32 solid tumor types revealed an annotated long noncoding RNA (lncRNA), Breast Cancer Anti-Estrogen Resistance 4 (BCAR4), was the most prevalent, uncharacterized, downstream gene fusion partner occurring in 11 cancers. Its oncogenic role was confirmed using multiple cell lines with endogenous BCAR4 gene fusions. Furthermore, overexpressing clinically prevalent BCAR4 gene fusions in untransformed cell lines was sufficient to induce an oncogenic phenotype. We show that the minimum common region to all gene fusions harbors an open reading frame that is necessary to drive proliferation. IMPLICATIONS: BCAR4 gene fusions represent an underappreciated class of gene fusions that may have biological and clinical implications across solid tumors.

HPV-EM: an accurate HPV detection and genotyping EM algorithm.

Accurate HPV genotyping is crucial in facilitating epidemiology studies, vaccine trials, and HPV-related cancer research. Contemporary HPV genotyping assays only detect < 25% of all known HPV genotypes and are not accurate for low-risk or mixed HPV genotypes. Current genomic HPV genotyping algorithms use a simple read-alignment and filtering strategy that has difficulty handling repeats and homology sequences. Therefore, we have developed an optimized expectation-maximization algorithm, designated HPV-EM, to address the ambiguities caused by repetitive sequencing reads. HPV-EM achieved 97-100% accuracy when benchmarked using cell line data and TCGA cervical cancer data. We also validated HPV-EM using DNA tiling data on an institutional cervical cancer cohort (96.5% accuracy). Using HPV-EM, we demonstrated HPV genotypic differences in recurrence and patient outcomes in cervical and head and neck cancers.