Early Antibiotic Exposure Is Not Detrimental to Therapeutic Effect from Immunotherapy in Hepatocellular Carcinoma

BACKGROUND AND RATIONALE: Immune checkpoint inhibitor (ICI) therapy is an expanding therapeutic option for hepatocellular carcinoma (HCC). Antibiotics (ATB) taken prior to or early during ICI therapy can impact immunotherapy efficacy across indications; however, the effect of ATB is undefined in HCC. METHODS: In a large international cohort of 450 ICI recipients from Europe, North America, and Asia, we categorized patients according to timing of ATB focusing on exposure within −30 to +30 days from ICI (early immunotherapy period [EIOP]). EIOP was evaluated in association with overall survival (OS), progression-free survival (PFS), and best radiologic response using RECIST 1.1 criteria. RESULTS: Our study comprised mostly cirrhotic (329, 73.3%) males (355, 79.1%) with a Child-Turcotte Pugh class of A (332, 73.9%), receiving ICI after 1 therapy line (251, 55.9%) for HCC of Barcelona clinic liver cancer stage C (325, 72.4%). EIOP (n = 170, 37.9%) was independent of baseline clinicopathologic features of HCC and correlated with longer PFS (6.1 vs. 3.7 months, log-rank p = 0.0135). EIOP+ patients had similar OS, overall response, and disease control rates (DCRs) compared to EIOP. The effect of EIOP persisted in landmark time analyses and in multivariable models, confirming the independent predictive role of EIOP in influencing PFS following adjustment for covariates reflective of tumor burden, liver function, and ICI regimen administered. In patients receiving programmed cell death-1 receptor/ligand inhibitors monotherapy, EIOP was also associated with higher DCRs (61.4% vs. 50.9%, p = 0.0494). CONCLUSIONS: Unlike other oncological indications, ATB in the 30 days before or after ICI initiation is associated with improved benefit from immunotherapy, independent of disease and treatment-related features. Evaluation of the immune microbiologic determinants of response to ICI in HCC warrants further investigation

Concomitant medications and immune checkpoint inhibitor therapy for cancer: causation or association?

The majority of cancer patients assume concomitant medications for the treatment of cancer-related symptoms or co-morbidities. As immune checkpoint inhibitors expand in the treatment of a widening range of malignancies, drug–drug interactions have become an area of increasing interest due to the potential for some concomitant medications to exert immune-modulatory effects and influence outcomes from immunotherapy. Here, we review the evidence supporting this association across selected drug classes including antibiotics, proton pump inhibitors, metformin, and opioids

Concomitant medications and immune checkpoint inhibitor therapy for cancer: causation or association?

The majority of cancer patients assume concomitant medications for the treatment of cancer-related symptoms or co-morbidities. As immune checkpoint inhibitors expand in the treatment of a widening range of malignancies, drug–drug interactions have become an area of increasing interest due to the potential for some concomitant medications to exert immune-modulatory effects and influence outcomes from immunotherapy. Here, we review the evidence supporting this association across selected drug classes including antibiotics, proton pump inhibitors, metformin, and opioids

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.