Neoadjuvant chemoimmunotherapy (NACI) has shown promise in the treatment of resectable esophageal squamous cell carcinoma (ESCC). The microbiomes of patients can impact therapy response, and previous studies have demonstrated that intestinal microbiota influences cancer immunotherapy by activating gut immunity. Here, we investigated the effects of intratumoral microbiota on the response of patients with ESCC to NACI. Intratumoral microbiota signatures of β-diversity were disparate and predicted the treatment efficiency of NACI. The enrichment of Streptococcus positively correlated with GrzB+ and CD8+ T-cell infiltration in tumor tissues. The abundance of Streptococcus could predict prolonged disease-free survival in ESCC. Single-cell RNA sequencing demonstrated that responders displayed a higher proportion of CD8+ effector memory T cells but a lower proportion of CD4+ regulatory T cells. Mice that underwent fecal microbial transplantation or intestinal colonization with Streptococcus from responders showed enrichment of Streptococcus in tumor tissues, elevated tumor-infiltrating CD8+ T cells, and a favorable response to anti-PD-1 treatment. Collectively, this study suggests that intratumoral Streptococcus signatures could predict NACI response and sheds light on the potential clinical utility of intratumoral microbiota for cancer immunotherapy. Significance: Analysis of intratumoral microbiota in patients with esophageal cancer identifies a microbiota signature that is associated with chemoimmunotherapy response and reveals that Streptococcus induces a favorable response by stimulating CD8+ T-cell infiltration. See related commentary by Sfanos, p. 2985

Background: The accuracy of lymph node ratio (LNR) as a prognostic index remains to be proven for gastric cancer patients after neoadjuvant chemotherapy (NACT). This study sought to investigate the prognostic value of LNR in locally advanced gastric cancer (LAGC) patients after NACT.Methods: LAGC patients with clinical TNM stages 2–3, Her2(−), and Eastern Cooperative Oncology Group, scores 0–2 are routinely scheduled with NACT. Patients with LAGC after NACT and surgical operation between January 2012 and October 2020 were retrospectively reviewed. The correlation between LNR and survival was investigated.Results: Overall, 148 patients were enrolled: 103 with low-LNR (LNR ≤ 30%) and 45 with high-LNR (LNR > 30%). Approximately, 50.5% and 24.4% patients responded to NACT at the primary site in the low-LNR and high-LNR groups, respectively. The overall survival (OS) and progression-free survival (PFS) of low-LNR group were considerably better than those of high-LNR group (3-year OS: 81.9% vs 18.5%,P< 0.001; 3-year PFS: 72.6% vs 13.5%,P< 0.001). In the low-LNR group, OS and PFS were superior in patients with tumor regression grade (TRG) 0–2 than in those with TRG 3 (3-year OS: 89.2% vs 73.2%,P= 0.086; 3-year PFS: 80.3% vs 66.5%,P= 0.036). In association with OS and PFS, the degree of tumor differentiation, TRG, and LNR were identified as predictive factors, and LNR was identified as the independent prognostic factor in univariate and multivariate analyses, respectively.Conclusions: LNR is a prospective index of prognosis in patients with LAGC after NACT.

Bacterial transcription by RNA polymerase (RNAP) is spatially organized. RNAPs transcribing highly expressed genes locate in the nucleoid periphery, and form clusters in rich medium, with several studies linking RNAP clustering and transcription of rRNA (rrn). However, the nature of RNAP clusters and their association with rrn transcription remains unclear. Here we address these questions by using single-molecule tracking to monitor the subcellular distribution of mobile and immobile RNAP in strains with a heavily reduced number of chromosomal rrn operons (Δrrn strains). Strikingly, we find that the fraction of chromosome-associated RNAP (which is mainly engaged in transcription) is robust to deleting five or six of the seven chromosomal rrn operons. Spatial analysis in Δrrn strains showed substantial RNAP redistribution during moderate growth, with clustering increasing at cell endcaps, where the remaining rrn operons reside. These results support a model where RNAPs in Δrrn strains relocate to copies of the remaining rrn operons. In rich medium, Δrrn strains redistribute RNAP to minimize growth defects due to rrn deletions, with very high RNAP densities on rrn genes leading to genomic instability. Our study links RNAP clusters and rrn transcription, and offers insight into how bacteria maintain growth in the presence of only 1–2 rrn operons.