Impact of preoperative chemoradiotherapy (CRT) on the rectal tumor microenvironment (TME) and associated patient outcomes.
Authors: Mohamed E. Salem, Hsih-Te Yang, Wei Sha, James Thomas Symanowski, Alberto Puccini, Jimmy J. Hwang, Kunal C. Kadakia, Laura W. Musselwhite, Edward S. Kim, Thomas J. George, David Foureau
Journal: Journal of Clinical Oncology (2022)

157 Background: Pembrolizumab did not improve neoadjuvant rectal score when added to neoadjuvant CRT in the NRG-GI002 study. The impact of CRT on TME in patients (pts) with rectal cancer (RC) has not been well characterized. Methods: We performed a paired analysis on RC tissue taken pre- and post-CRT from pts undergoing long course CRT with a fluoropyrimidine followed by surgery. Samples underwent next-generation sequencing (NGS) and whole transcriptome RNAseq. Ingenuity Pathway Analysis (IPA), Molecular Signature Database (MSigDB), and xCell algorithm were used to dissect TME changes pre/post-CRT. Results: Specimens from 61 pts with MSS-RC were identified: median age, 61y, 75% white, 18% black, and 57% male. Tumor samples from 57 pts underwent NGS: 43 pre-CRT, 48 post-CRT, and 34 paired. A total of 2,642 differentially expressed genes (DEGs) were identified between pre/post CRT tumors and then grouped into 3 main gene sets (GS): “higher eukaryotes transcription factor (E2F) target”, “G2/M cell cycle checkpoint”, and “Immune/Stress”. The 3 GS are mutually exclusive, indicating different cellular processes in response to CRT. E2F and G2/M gene signatures were specifically enriched pre-CRT (p &lt; 0.0001), indicating that treatment alters cell survival, proliferation, and tumor growth. Cell death and apoptosis (p &lt; 0.0001) and the Immune/Stress set, including stromal stress response (p = 0.0004), tissue repair (p = 0.0025), and leukocyte production (p &lt; 0.008), were significantly enriched post-CRT. The xCell algorithm used to assess alteration stromal vs immune response by CRT; Stromal scores increased by 0.100 ± 0.016-fold, while Immune scores increased by 0.047 ± 0.017 (P = 0.015), suggesting a rise in Immune/Stress GS is driven mainly by stromal stress response. The 5 most common gene types upregulated post-CRT were smooth muscle cells, fibroblasts, interstitial dendritic cells, pericytes, and hepatic stellate cells. However, immune alterations trended downward (NK, Th1, and gamma delta T cells) or rose heterogeneously, e.g., a rise in intra-tumoral CD8 T cell subsets (effector, effector memory, or central memory) occurred for 8/35 pts. Fifteen pts (42%) relapsed and/or died after surgery. While CD8 T cell infiltration tends to be associated with better prognosis, it was not statistically significant (p = 0.2277; HR 2.709). CD8 T cell infiltrates were associated with higher prevalence of immune checkpoint transcripts LAG3 (p = &lt; 0.0001) and to a lesser extend PD1 (p = 0.0186) in the tumor, indicating an anergic state of CD8 T cell infiltrates post-CRT. Conclusions: TME of RC tumors mainly identified stress/ wound healing response to CRT. Immune response was heterogeneous among pts; a subset showed a significant rise in CD8 T cell infiltration, indicating an anergic state mainly driven by LAG3. The potential of this pt subset to respond to anti-LAG3 immunotherapy is worthy of further study.