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      Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions

      research-article
      1 , 2 , 20 , 3 , 11 , 20 , 1 , 4 , 20 , 2 , 21 , 5 , 6 , 7 , 21 , 1 , 1 , 8 , 9 , 10 , 7 , 11 , 1 , 12 , 15 , 1 , 1 , 7 , 13 , 14 , 15 , 16 , 15 , 16 , 12 , 17 , 6 , 18 , 9 , 6 , 2 , 22 , 3 , 6 , 7 , 19 , 22 , , 1 , 22 , 23 , ∗∗
      Cell
      Cell Press
      tumor mycobiome, tumor microbiome, cancer, biomarkers, fungi, microbial interactions, liquid biopsy, metagenomics, metatranscriptomics

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          Summary

          Cancer-microbe associations have been explored for centuries, but cancer-associated fungi have rarely been examined. Here, we comprehensively characterize the cancer mycobiome within 17,401 patient tissue, blood, and plasma samples across 35 cancer types in four independent cohorts. We report fungal DNA and cells at low abundances across many major human cancers, with differences in community compositions that differ among cancer types, even when accounting for technical background. Fungal histological staining of tissue microarrays supported intratumoral presence and frequent spatial association with cancer cells and macrophages. Comparing intratumoral fungal communities with matched bacteriomes and immunomes revealed co-occurring bi-domain ecologies, often with permissive, rather than competitive, microenvironments and distinct immune responses. Clinically focused assessments suggested prognostic and diagnostic capacities of the tissue and plasma mycobiomes, even in stage I cancers, and synergistic predictive performance with bacteriomes.

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          Highlights

          • Fungi were detected in 35 cancer types and were often intracellular

          • Multiple fungal-bacterial-immune ecologies were detected across tumors

          • Intratumoral fungi stratified clinical outcomes, including immunotherapy response

          • Cell-free fungal DNA diagnosed healthy and cancer patients in early-stage disease

          Abstract

          Characterization of fungi across multiple sample types and patient cohorts across 35 cancer types reveals their distribution, association with immune cell types, and potential prognostic value, including synergy with bacteria.

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          Most cited references110

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              Cytoscape: a software environment for integrated models of biomolecular interaction networks.

              Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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                Author and article information

                Contributors
                Journal
                Cell
                Cell
                Cell
                Cell Press
                0092-8674
                1097-4172
                29 September 2022
                29 September 2022
                : 185
                : 20
                : 3789-3806.e17
                Affiliations
                [1 ]Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
                [2 ]Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
                [3 ]Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
                [4 ]Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
                [5 ]Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
                [6 ]Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
                [7 ]Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, CA, USA
                [8 ]Department of Microbiology and Plant Pathology, Institute for Integrative Genome Biology, University of California Riverside, Riverside, CA, USA
                [9 ]Department of Physics, Bar-Ilan University, Ramat-Gan, Israel
                [10 ]Department of Natural Sciences, The Open University of Israel, Raanana, Israel
                [11 ]Micronoma Inc., San Diego, CA, USA
                [12 ]Cancer Research Center, Sheba Medical Center, Ramat Gan, Israel
                [13 ]School of Life Sciences, Arizona State University, Tempe, AZ, USA
                [14 ]Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA
                [15 ]Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
                [16 ]Department of Pathology, Sheba Medical Center, Ramat Gan, Israel
                [17 ]Breast Oncology Institute, Sheba Medical Center, Ramat Gan, Israel
                [18 ]Moores Cancer Center, University of California San Diego Health, La Jolla, CA, USA
                [19 ]Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
                Author notes
                []Corresponding author robknight@ 123456eng.ucsd.edu
                [∗∗ ]Corresponding author ravidst@ 123456weizmann.ac.il
                [20]

                These authors contributed equally

                [21]

                These authors contributed equally

                [22]

                These authors contributed equally

                [23]

                Lead contact

                Article
                S0092-8674(22)01127-8
                10.1016/j.cell.2022.09.005
                9567272
                36179670
                8a31323d-7c0c-454a-858f-6047c9aa9e65
                © 2022 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 13 December 2021
                : 13 May 2022
                : 31 August 2022
                Categories
                Resource

                Cell biology
                tumor mycobiome,tumor microbiome,cancer,biomarkers,fungi,microbial interactions,liquid biopsy,metagenomics,metatranscriptomics

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