Checkpoint blockade with antibodies against CTLA-4 or PD-1 elicits durable tumor regressions in metastatic cancer, but these dramatic responses are confined to a minority of patients1–3. This suboptimal outcome is likely due in part to the complex network of immunosuppressive pathways present in advanced tumors, which are unlikely to be overcome by intervention at a single signaling checkpoint4–8. Here we demonstrate a combination immunotherapy that recruits a variety of innate and adaptive immune cells to eliminate large tumor burdens in syngeneic tumor models and a genetically engineered mouse melanoma model; to our knowledge tumors of this size have not previously been curable by treatments relying on endogenous immunity. Maximal anti-tumor efficacy required four components: a tumor antigen targeting antibody, an extended half-life recombinant IL-29, anti-PD-1, and a powerful T-cell vaccine10. Depletion experiments revealed that CD8+ T-cells, cross-presenting DCs, and several other innate immune cell subsets were required for tumor regression. Effective treatment induced infiltration of immune cells and production of inflammatory cytokines in the tumor, enhanced antibody-mediated tumor antigen uptake, and promoted antigen spreading. These results demonstrate the capacity of an elicited endogenous immune response to destroy large, established tumors and elucidate essential characteristics of combination immunotherapies capable of curing a majority of tumors in experimental settings typically viewed as intractable.

No abstract

Background Currently, over half of breast cancer cases are unrelated to known risk factors, highlighting the importance of discovering other cancer-promoting factors. Since crosstalk between gut microbes and host immunity contributes to many diseases, we hypothesized that similar interactions could occur between the recently described breast microbiome and local immune responses to influence breast cancer pathogenesis. Methods Using 16S rRNA gene sequencing, we characterized the microbiome of human breast tissue in a total of 221 patients with breast cancer, 18 individuals predisposed to breast cancer, and 69 controls. We performed bioinformatic analyses using a DADA2-based pipeline and applied linear models with White’s t or Kruskal–Wallis H-tests with Benjamini–Hochberg multiple testing correction to identify taxonomic groups associated with prognostic clinicopathologic features. We then used network analysis based on Spearman coefficients to correlate specific bacterial taxa with immunological data from NanoString gene expression and 65-plex cytokine assays. Results Multiple bacterial genera exhibited significant differences in relative abundance when stratifying by breast tissue type (tumor, tumor adjacent normal, high-risk, healthy control), cancer stage, grade, histologic subtype, receptor status, lymphovascular invasion, or node-positive status, even after adjusting for confounding variables. Microbiome–immune networks within the breast tended to be bacteria-centric, with sparse structure in tumors and more interconnected structure in benign tissues. Notably, Anaerococcus, Caulobacter, and Streptococcus, which were major bacterial hubs in benign tissue networks, were absent from cancer-associated tissue networks. In addition, Propionibacterium and Staphylococcus, which were depleted in tumors, showed negative associations with oncogenic immune features; Streptococcus and Propionibacterium also correlated positively with T-cell activation-related genes. Conclusions This study, the largest to date comparing healthy versus cancer-associated breast microbiomes using fresh-frozen surgical specimens and immune correlates, provides insight into microbial profiles that correspond with prognostic clinicopathologic features in breast cancer. It additionally presents evidence for local microbial–immune interplay in breast cancer that merits further investigation and has preventative, diagnostic, and therapeutic potential.

The purpose of this study was to determine rates of pneumonia and hospitalization for patients receiving oxygen therapy, patients having indwelling tracheostomy tubes, and those using tracheostomy or noninvasive methods of home mechanical ventilation. Six hundred eighty-four users of assisted ventilation for 13,751 patient-years or 19.8 years per patient were surveyed by mail and twice by telephone over a span of four years. Pneumonia and hospitalization rates were significantly higher for ventilator users with chronic obstructive pulmonary disease or with neuromuscular ventilatory insufficiency and gastrostomy tubes than for ventilator users with neuromuscular ventilatory insufficiency without gastrostomy tubes. Of the latter group, more than 90% of the pneumonias and hospitalizations were triggered by otherwise benign intercurrent upper respiratory tract infections. Oxygen therapy was associated with a significantly (P < 0.001) higher rate of pneumonias and hospitalizations than that seen for untreated patients after initial episodes of respiratory distress or during the use of either tracheostomy intermittent positive pressure ventilation or noninvasive ventilatory assistance methods. The lowest pneumonia and hospitalization rates (P < 0.001) were by full-time, noninvasive intermittent positive pressure ventilation users. We conclude that oxygen therapy is not an effective substitute for assisted ventilation for patients with primarily ventilatory insufficiency. Noninvasive ventilatory aids can be used effectively for up to full-time ventilatory support for patients with neuromuscular conditions whose bulbar muscle function is adequate to avert the need for gastrostomy tube placement.