Immunogenomic features of pathologic response to neoadjuvant immune checkpoint blockade in esophageal cancer
| Autor: | Mara Lanis, Victor E. Velculescu, Stephen C. Yang, Vincent K. Lam, Kristen A. Marrone, Ronan J. Kelly, Heather Schneider, Richard J. Battafarano, Blair A. Jobe, Hanika Rodavia, Zineb Belcaid, Stephen R. Broderick, Archana Balan, Elizabeth D. Thompson, Ali H. Zaidi, Benjamin Levy, Christopher Cherry, Valsamo Anagnostou, Josephine Feliciano, Jinny Ha |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Journal of Clinical Oncology. 39:4042-4042 |
| ISSN: | 1527-7755 0732-183X |
| Popis: | 4042 Background: Improving immunotherapy efficacy remains an unmet need in esophagogastric cancer and a deeper understanding of tumor and immune system dynamics during therapy may tailor immuno-oncology approaches. Methods: We performed whole exome sequencing (WES) and bulk RNA sequencing (RNAseq) of 70 serial tumor samples from 23 patients with stage II/III esophageal/gastroesophageal junction (E/GEJ) cancer treated on a phase 1B clinical trial with neoadjuvant nivolumab with or without relatlimab (anti-LAG-3) and chemoradiation followed by surgery (NCT03044613; CA209-906). Pathologic response was measured by tumor regression at the time of resection. Median follow up was 23 months post-surgery. Serial tumor samples were collected prior to therapy, after 2 cycles of induction immune checkpoint blockade (ICB), and at the time of resection. Twenty-two baseline tumor/normal DNA pairs were analyzed by WES and 48 serial tumor samples were analyzed by RNAseq. WES data was analyzed to identify somatic mutations, generate tumor mutation burden (TMB) estimates and assess the fraction of expressed mutations in conjunction with RNAseq data. Immune cell subset composition was determined by RNAseq data deconvolution by CIBERSORT and gene set enrichment analyses were performed utilizing GSEA. B-cell density was inferred by immunoglobulin rearrangements detected by RNAseq. Results: Gene set enrichment expression analyses revealed an upregulation of effector pro-inflammatory cytokines after induction ICB. Interferon-gamma, interferon-alpha and TNF-alpha related genes were significantly upregulated after induction ICB compared to baseline (p < 0.0001). In contrast, significant downregulation of E2F targets (p = 0.002), G2M checkpoint genes (p = 0.005) and DNA damage repair genes (p = 0.004) was observed post ICB; enrichment analyses were independent of response to therapy and treatment arm. While TMB was not predictive of pathologic response (p = 0.22), patients with tumors harboring a higher number of expressed mutations were more likely to achieve a pathologic complete response (pCR; p = 0.026). RNAseq deconvolution analyses revealed a higher B-cell density post ICB induction in tumors with pCR (p = 0.018). Furthermore, an increased baseline content of intra-tumoral activated M1 macrophages differentiated tumors from patients achieving a pCR (p = 0.0034), which was further exemplified post induction ICB. Conclusions: Neoadjuvant immunotherapy induces an inflammatory immune response in the tumor microenvironment that is linked with tumor elimination and pathologic response. Our findings highlight the importance of nuanced multi-omics analyses to understand the wiring of response to immunotherapy and guide therapy for E/GEJ cancer. |
| Databáze: | OpenAIRE |
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