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Microbiome-Based Biomarkers in Cancer Diagnosis, Prognosis, and Treatment Outcome Prediction

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A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Biomarkers".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 30856

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Dr. Paolo Nuciforo

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Vall d’Hebron Institute of Oncology (VHIO), Vall d’Hebron University Hospital, 08035 Barcelona, Spain
Interests: Biomarkers; Cancer Microbiome; Digital Pathology

Special Issue Information

Dear Colleagues,

The relationship between cancer and microbes is complex. Although cancer is generally considered to be a disease of host genetics and environmental factors, microorganisms are implicated in ~20% of human malignancies. Recent scientific advances have significantly contributed to our understanding of the complex connection between the microbiome and cancer. Our bodies are continuously exposed to microbial cells, both resident and transient, as well as their byproducts, including toxic metabolites. The circulation of toxic metabolites may contribute to cancer onset or progression at locations distant from where a particular microbe resides. Moreover, microbes may migrate to other locations in the human body and may promote tumorigenesis or disease progression through a variety of mechanisms.

As the scientiﬁc community continues to generate more microbiome data and integrate them with other “omics” such as transcriptomics, proteomics, and metabolomics, it is anticipated that novel microbial signatures associated with disease onset and progression will be identified in many cancer types. These microbiome signatures have the potential to be translated into diagnostics and therapeutics.

This Special Issue will highlight the role of the microbiome in cancer in all its aspects, from both basic and clinical perspectives, and will outline future perspectives for the use of microbiome-based biomarkers in oncology.

Dr. Paolo Nuciforo
Guest Editor

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Published Papers (10 papers)

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Research

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14 pages, 17312 KiB

Open AccessArticle

Exploring Gut Microbiome in Predicting the Efficacy of Immunotherapy in Non-Small Cell Lung Cancer

by Ben Liu, Justin Chau, Qun Dai, Cuncong Zhong and Jun Zhang

Cancers 2022, 14(21), 5401; https://doi.org/10.3390/cancers14215401 - 02 Nov 2022

Cited by 7 | Viewed by 2562

Abstract

We performed various analyses on the taxonomic and functional features of the gut microbiome from NSCLC patients treated with immunotherapy to establish a model that may predict whether a patient will benefit from immunotherapy. We collected 65 published whole metagenome shotgun sequencing samples along with 14 samples from our previous study. We systematically studied the taxonomical characteristics of the dataset and used both the random forest (RF) and the multilayer perceptron (MLP) neural network models to predict patients with progression-free survival (PFS) above 6 months versus those below 3 months. Our results showed that the RF classifier achieved the highest F-score (85.2%) and the area under the receiver operating characteristic curve (AUC) (95%) using the protein families (Pfam) profile, and the MLP neural network classifier achieved a 99.9% F-score and 100% AUC using the same Pfam profile. When applying the model trained in the Pfam profile directly to predict the treatment response, we found that both trained RF and MLP classifiers significantly outperformed the stochastic predictor in F-score. Our results suggested that such a predictive model based on functional (e.g., Pfam) rather than taxonomic profile might be clinically useful to predict whether an NSCLC patient will benefit from immunotherapy, as both the F-score and AUC of functional profile outperform that of taxonomic profile. In addition, our model suggested that interactive biological processes such as methanogenesis, one-carbon, and amino acid metabolism might be important in regulating the immunotherapy response that warrants further investigation. Full article

(This article belongs to the Special Issue Microbiome-Based Biomarkers in Cancer Diagnosis, Prognosis, and Treatment Outcome Prediction)

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14 pages, 3775 KiB

Open AccessArticle

Characterization of the Metabolome of Breast Tissues from Non-Hispanic Black and Non-Hispanic White Women Reveals Correlations between Microbial Dysbiosis and Enhanced Lipid Metabolism Pathways in Triple-Negative Breast Tumors

by Alana Smith, Xueyuan Cao, Qingqing Gu, Ernestine Kubi Amos-Abanyie, Elizabeth A. Tolley, Gregory Vidal, Beverly Lyn-Cook and Athena Starlard-Davenport

Cancers 2022, 14(17), 4075; https://doi.org/10.3390/cancers14174075 - 23 Aug 2022

Cited by 5 | Viewed by 1987

Abstract

Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer that is non-responsive to hormonal therapies and disproportionately impact women of African ancestry. We previously showed that TN breast tumors have a distinct microbial signature that differs from less aggressive breast tumor subtypes and normal breast tissues. However, it is unknown whether these differences in breast tumor microbiota may be driven by alterations in microbial metabolites, leading to potentially protective or pathogenic consequences. The goal of this global metabolomic profiling study was to investigate alterations in microbial metabolism pathways in normal and breast tumor tissues, including TNBC, of non-Hispanic black (NHB) and non-Hispanic white (NHW) women. In this study, we profiled the microbiome (16S rRNA) from breast tumor tissues and analyzed 984 metabolites from a total of 51 NHB and NHW women. Breast tumor tissues were collected from 15 patients with TNBC, 12 patients with less aggressive luminal A-type (Luminal) breast cancer, and 24 healthy controls for comparison using UHPLC-tandem mass spectrometry. Principal component analysis and hierarchical clustering of the global metabolomic profiling data revealed separation between metabolic signatures of normal and breast tumor tissues. Random forest analysis revealed a unique biochemical signature associated with elevated lipid metabolites and lower levels of microbial-derived metabolites important in controlling inflammation and immune responses in breast tumor tissues. Significant relationships between the breast microbiome and the metabolome, particularly lipid metabolism, were observed in TNBC tissues. Further investigations to determine whether alterations in sphingolipid, phospholipid, ceramide, amino acid, and energy metabolism pathways modulate Fusobacterium and Tenericutes abundance and composition to alter host metabolism in TNBC are necessary to help us understand the risk and underlying mechanisms and to identify potential microbial-based targets. Full article

(This article belongs to the Special Issue Microbiome-Based Biomarkers in Cancer Diagnosis, Prognosis, and Treatment Outcome Prediction)

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11 pages, 1131 KiB

Open AccessArticle

Prognostic Value of Fusobacterium nucleatum after Abdominoperineal Resection for Anal Squamous Cell Carcinoma

by Marc Hilmi, Cindy Neuzillet, Jérémie H. Lefèvre, Magali Svrcek, Sophie Vacher, Leonor Benhaim, Peggy Dartigues, Emmanuelle Samalin, Julien Lazartigues, Jean-François Emile, Eugénie Rigault, Nathalie Rioux-Leclercq, Christelle de La Fouchardière, David Tougeron, Wulfran Cacheux, Pascale Mariani, Laura Courtois, Matthieu Delaye, Virginie Dangles-Marie, Astrid Lièvre and Ivan Bieche Show full author list Hide full author list

Cancers 2022, 14(7), 1606; https://doi.org/10.3390/cancers14071606 - 22 Mar 2022

Cited by 7 | Viewed by 2028

Abstract

Main prognostic factors of anal squamous cell carcinoma (ASCC) are tumor size, differentiation, lymph node involvement, and male gender. However, they are insufficient to predict relapses after exclusive radiotherapy (RT) or chemoradiotherapy (CRT). Fusobacterium nucleatum has been associated with poor prognosis in several digestive cancers. In this study, we assessed the association between intratumoral F. nucleatum load and clinico-pathological features, relapse, and survival in patients with ASCC who underwent abdominoperineal resection (APR) after RT/CRT. We retrospectively analyzed surgical samples from a cohort of 166 patients with ASCC who underwent APR. F. nucleatum 16S rRNA gene sequences were quantified using real-time quantitative PCR. We associated F. nucleatum load with classical clinicopathological features, overall survival (OS), disease-free survival (DFS), and metastasis-free survival (MFS) using Cox regression univariate and multivariate analyses. Tumors harboring high loads of F. nucleatum (highest tercile) showed longer OS and DFS (median: not reached vs. 50.1 months, p = 0.01, and median: not reached vs. 18.3 months, p = 0.007, respectively). High F. nucleatum load was a predictor of longer OS (HR = 0.55, p = 0.04) and DFS (HR = 0.50, p = 0.02) in multivariate analysis. High F. nucleatum load is an independent favorable prognostic factor in patients with ASCC who underwent APR. Full article

(This article belongs to the Special Issue Microbiome-Based Biomarkers in Cancer Diagnosis, Prognosis, and Treatment Outcome Prediction)

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18 pages, 3058 KiB

Open AccessArticle

Performance of 16S Metagenomic Profiling in Formalin-Fixed Paraffin-Embedded versus Fresh-Frozen Colorectal Cancer Tissues

by Alessandra Borgognone, Garazi Serna, Marc Noguera-Julian, Lidia Alonso, Mariona Parera, Francesc Català-Moll, Lidia Sanchez, Roberta Fasani, Roger Paredes and Paolo Nuciforo

Cancers 2021, 13(21), 5421; https://doi.org/10.3390/cancers13215421 - 29 Oct 2021

Cited by 11 | Viewed by 2946

Abstract

Formalin-fixed, paraffin-embedded (FFPE) tissues represent the most widely available clinical material to study colorectal cancer (CRC). However, the accuracy and clinical validity of FFPE microbiome profiling in CRC is uncertain. Here, we compared the microbial composition of 10 paired fresh-frozen (FF) and FFPE CRC tissues using 16S rRNA sequencing and RNA-ISH. Both sample types showed different microbial diversity and composition. FF samples were enriched in archaea and representative CRC-associated bacteria, such as Firmicutes, Bacteroidetes and Fusobacteria. Conversely, FFPE samples were mainly enriched in typical contaminants, such as Sphingomonadales and Rhodobacterales. RNA-ISH in FFPE tissues confirmed the presence of CRC-associated bacteria, such as Fusobacterium and Bacteroides, as well as Propionibacterium allowing discrimination between tumor-associated and contaminant taxa. An internal quality index showed that the degree of similarity within sample pairs inversely correlated with the dominance of contaminant taxa. Given the importance of FFPE specimens for larger studies in human cancer genomics, our findings may provide useful indications on potential confounding factors to consider for accurate and reproducible metagenomics analyses. Full article

(This article belongs to the Special Issue Microbiome-Based Biomarkers in Cancer Diagnosis, Prognosis, and Treatment Outcome Prediction)

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25 pages, 4563 KiB

Open AccessArticle

Colorectal Tumour Mucosa Microbiome Is Enriched in Oral Pathogens and Defines Three Subtypes That Correlate with Markers of Tumour Progression

by Barbora Zwinsová, Vyacheslav A. Petrov, Martina Hrivňáková, Stanislav Smatana, Lenka Micenková, Natálie Kazdová, Vlad Popovici, Roman Hrstka, Roman Šefr, Beatrix Bencsiková, Lenka Zdražilová-Dubská, Veronika Brychtová, Rudolf Nenutil, Petra Vídeňská and Eva Budinská

Cancers 2021, 13(19), 4799; https://doi.org/10.3390/cancers13194799 - 25 Sep 2021

Cited by 8 | Viewed by 3359

Abstract

Long-term dysbiosis of the gut microbiome has a significant impact on colorectal cancer (CRC) progression and explains part of the observed heterogeneity of the disease. Even though the shifts in gut microbiome in the normal-adenoma-carcinoma sequence were described, the landscape of the microbiome within CRC and its associations with clinical variables remain under-explored. We performed 16S rRNA gene sequencing of paired tumour tissue, adjacent visually normal mucosa and stool swabs of 178 patients with stage 0–IV CRC to describe the tumour microbiome and its association with clinical variables. We identified new genera associated either with CRC tumour mucosa or CRC in general. The tumour mucosa was dominated by genera belonging to oral pathogens. Based on the tumour microbiome, we stratified CRC patients into three subtypes, significantly associated with prognostic factors such as tumour grade, sidedness and TNM staging, BRAF mutation and MSI status. We found that the CRC microbiome is strongly correlated with the grade, location and stage, but these associations are dependent on the microbial environment. Our study opens new research avenues in the microbiome CRC biomarker detection of disease progression while identifying its limitations, suggesting the need for combining several sampling sites (e.g., stool and tumour swabs). Full article

(This article belongs to the Special Issue Microbiome-Based Biomarkers in Cancer Diagnosis, Prognosis, and Treatment Outcome Prediction)

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20 pages, 4695 KiB

Open AccessArticle

Gut Microbiota Dynamics during Chemotherapy in Epithelial Ovarian Cancer Patients Are Related to Therapeutic Outcome

by Federica D’Amico, Anna Myriam Perrone, Simone Rampelli, Sara Coluccelli, Monica Barone, Gloria Ravegnini, Marco Fabbrini, Patrizia Brigidi, Pierandrea De Iaco and Silvia Turroni

Cancers 2021, 13(16), 3999; https://doi.org/10.3390/cancers13163999 - 08 Aug 2021

Cited by 23 | Viewed by 3152

Abstract

Epithelial ovarian cancer (EOC) is one of the most lethal and silent gynecological tumors. Despite appropriate surgery and chemotherapy, relapse occurs in over half of patients with a poor prognosis. Recently, the gut microbiota (GM) was hypothesized to influence the efficacy of anticancer therapies, but no data are available in EOC. Here, by 16S rRNA gene sequencing and inferred metagenomics, we profiled the GM of EOC patients at diagnosis and reconstructed its trajectory along the course of neoadjuvant or adjuvant chemotherapy up to follow-up. Compared to healthy subjects, the GM of EOC patients appeared unbalanced and severely affected by chemotherapy. Strikingly, discriminating patterns were identified in relation to the therapeutic response. Platinum-resistant patients showed a marked temporal reduction in GM diversity and increased instability with loss of health-associated taxa and increased proportions of Coriobacteriaceae and Bifidobacterium. Notably, most of these microorganisms are lactate producers, suggesting increased lactate production as supported by inferred metagenomics. In contrast, the GM of platinum-sensitive patients appeared overall more diverse and stable and enriched in lactate utilizers from the Veillonellaceae family. In conclusion, we identified potential GM signatures of therapeutic outcome in EOC patients, which could open up new opportunities for cancer prognosis and treatment. Full article

(This article belongs to the Special Issue Microbiome-Based Biomarkers in Cancer Diagnosis, Prognosis, and Treatment Outcome Prediction)

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13 pages, 3399 KiB

Open AccessArticle

Dynamics of Fecal Microbiota with and without Invasive Cervical Cancer and Its Application in Early Diagnosis

by Gi-Ung Kang, Da-Ryung Jung, Yoon Hee Lee, Se Young Jeon, Hyung Soo Han, Gun Oh Chong and Jae-Ho Shin

Cancers 2020, 12(12), 3800; https://doi.org/10.3390/cancers12123800 - 16 Dec 2020

Cited by 20 | Viewed by 3398

Abstract

The fecal microbiota is being increasingly implicated in the diagnosis of various diseases. However, evidence on changes in the fecal microbiota in invasive cervical cancer (ICC) remains scarce. Here, we aimed to investigate the fecal microbiota of our cohorts, develop a diagnostic model for predicting early ICC, and identify potential fecal microbiota-derived biomarkers using amplicon sequencing data. We obtained fecal samples from 29 healthy women (HC) and 17 women with clinically confirmed early ICC (CAN). Although Shannon’s diversity index was not reached at statistical significance, the Chao1 and Observed operational taxonomic units (OTUs) in fecal microbiota was significantly different between CAN and HC group. Furthermore, there were significant differences in the taxonomic profiles between HC and CAN; Prevotella was significantly more abundant in the CAN group and Clostridium in the HC group. Linear discriminant analysis effect size (LEfSe) analysis was applied to validate the taxonomic differences at the genus level. Furthermore, we identified a set of seven bacterial genera that were used to construct a machine learning (ML)-based classifier model to distinguish CAN from patients with HC. The model had high diagnostic utility (area under the curve [AUC] = 0.913) for predicting early ICC. Our study provides an initial step toward exploring the fecal microbiota and helps clinicians diagnose. Full article

(This article belongs to the Special Issue Microbiome-Based Biomarkers in Cancer Diagnosis, Prognosis, and Treatment Outcome Prediction)

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14 pages, 5772 KiB

Open AccessArticle

The Pancreatic Microbiome is Associated with Carcinogenesis and Worse Prognosis in Males and Smokers

by Jaideep Chakladar, Selena Z. Kuo, Grant Castaneda, Wei Tse Li, Aditi Gnanasekar, Michael Andrew Yu, Eric Y. Chang, Xiao Qi Wang and Weg M. Ongkeko

Cancers 2020, 12(9), 2672; https://doi.org/10.3390/cancers12092672 - 18 Sep 2020

Cited by 44 | Viewed by 3589

Abstract

An intra-pancreatic microbiota was recently discovered in several prominent studies. Since pancreatic adenocarcinoma (PAAD) is one of the most lethal cancers worldwide, and the intratumor microbiome was found to be a significant contributor to carcinogenesis in other cancers, this study aims to characterize the PAAD microbiome and elucidate how it may be associated with PAAD prognosis. We further explored the association between the intra-pancreatic microbiome and smoking and gender, which are both risk factors for PAAD. RNA-sequencing data from The Cancer Genome Atlas (TCGA) were used to infer microbial abundance, which was correlated to clinical variables and to cancer and immune-associated gene expression, to determine how microbes may contribute to cancer progression. We discovered that the presence of several bacteria species within PAAD tumors is linked to metastasis and immune suppression. This is the first large-scale study to report microbiome-immune correlations in human pancreatic cancer samples. Furthermore, we found that the increased prevalence and poorer prognosis of PAAD in males and smokers are linked to the presence of potentially cancer-promoting or immune-inhibiting microbes. Further study into the roles of these microbes in PAAD is imperative for understanding how a pro-tumor microenvironment may be treated to limit cancer progression. Full article

(This article belongs to the Special Issue Microbiome-Based Biomarkers in Cancer Diagnosis, Prognosis, and Treatment Outcome Prediction)

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Review

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33 pages, 1088 KiB

Open AccessReview

Bacterial-Viral Interactions in Human Orodigestive and Female Genital Tract Cancers: A Summary of Epidemiologic and Laboratory Evidence

by Ikuko Kato, Jilei Zhang and Jun Sun

Cancers 2022, 14(2), 425; https://doi.org/10.3390/cancers14020425 - 15 Jan 2022

Cited by 6 | Viewed by 3205

Abstract

Infectious agents, including viruses, bacteria, fungi, and parasites, have been linked to pathogenesis of human cancers, whereas viruses and bacteria account for more than 99% of infection associated cancers. The human microbiome consists of not only bacteria, but also viruses and fungi. The microbiome co-residing in specific anatomic niches may modulate oncologic potentials of infectious agents in carcinogenesis. In this review, we focused on interactions between viruses and bacteria for cancers arising from the orodigestive tract and the female genital tract. We examined the interactions of these two different biological entities in the context of human carcinogenesis in the following three fashions: (1) direct interactions, (2) indirect interactions, and (3) no interaction between the two groups, but both acting on the same host carcinogenic pathways, yielding synergistic or additive effects in human cancers, e.g., head and neck cancer, liver cancer, colon cancer, gastric cancer, and cervical cancer. We discuss the progress in the current literature and summarize the mechanisms of host-viral-bacterial interactions in various human cancers. Our goal was to evaluate existing evidence and identify gaps in the knowledge for future directions in infection and cancer. Full article

(This article belongs to the Special Issue Microbiome-Based Biomarkers in Cancer Diagnosis, Prognosis, and Treatment Outcome Prediction)

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12 pages, 732 KiB

Open AccessReview

The Role of Bacteria in KSHV Infection and KSHV-Induced Cancers

by Ashley Markazi, Wen Meng, Paige M. Bracci, Michael S. McGrath and Shou-Jiang Gao

Cancers 2021, 13(17), 4269; https://doi.org/10.3390/cancers13174269 - 25 Aug 2021

Cited by 5 | Viewed by 2392

Abstract

The objective of this article is to review the current status of the bacteria-virus interplay in Kaposi’s sarcoma-associated herpesvirus (KSHV) infection and KSHV-driven cancers. KSHV is the etiological agent of several cancers, including Kaposi’s sarcoma (KS) and primary effusion lymphoma. Due to immunosuppression, patients with KSHV are at an increased risk for bacterial infections. Moreover, among patients coinfected by HIV and KSHV, patients with KS have distinct oral microbiota compared to non-KS patients. Bacterial biomarkers associated with KSHV-driven cancers can provide insights in discerning the mechanisms of KSHV-induced oncogenesis. For example, pathogen-associated molecular patterns and bacterial products of certain bacterial species can regulate the expression of KSHV lytic and latent genes, thereby affecting viral replication and dissemination. In addition, infection with distinct opportunistic bacterial species have been associated with increased cell proliferation and tumorigenesis in KSHV-induced cancers through activation of pro-survival and -mitogenic cell signaling pathways. By elucidating the various mechanisms in which bacteria affect KSHV-associated pathogenesis, we will be able to pinpoint therapeutic targets for KSHV infection and KSHV-related cancers. Full article

(This article belongs to the Special Issue Microbiome-Based Biomarkers in Cancer Diagnosis, Prognosis, and Treatment Outcome Prediction)

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