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© 2025 Seerave Global Oncobiome Atlas. All rights reserved.
Cookies
Privacy Policy
© 2025 Seerave Global Oncobiome Atlas. All rights reserved.
Cookies
Privacy Policy
© 2025 Seerave Global Oncobiome Atlas.
All rights reserved.
Use Case 1:
Unraveling microbiome-based cancer diagnostics (ONCOBIOME)
Since 2019, ONCOBIOME aimed at bringing efficient, rapid and cost effective tests to diagnose cancer risk or its relapse.
Goal
Establishing a robust scientific foundation for clinical best practice recommendations on microbiome considerations in cancer patients and delivering actionable tools to prevent, identify, assess, predict, and mitigate microbiome-induced complications to improve patient prognosis.
Establishing a robust scientific foundation for clinical best practice recommendations on microbiome considerations in cancer patients and delivering actionable tools to prevent, identify, assess, predict, and mitigate microbiome-induced complications to improve patient prognosis.
Establishing a robust scientific foundation for clinical best practice recommendations on microbiome considerations in cancer patients and delivering actionable tools to prevent, identify, assess, predict, and mitigate microbiome-induced complications to improve patient prognosis.
The Initial Scientific Focus
Problem
Cancer patients worldwide face suboptimal treatment outcomes due to microbiome-related factors that remain poorly understood and unaddressed in clinical practice.
Traditional oncology approaches overlook how gut dysbiosis compromises immunotherapy effectiveness and overall treatment success, leading to preventable treatment failures across diverse cancer populations.
Cancer patients worldwide face suboptimal treatment outcomes due to microbiome-related factors that remain poorly understood and unaddressed in clinical practice.
Traditional oncology approaches overlook how gut dysbiosis compromises immunotherapy effectiveness and overall treatment success, leading to preventable treatment failures across diverse cancer populations.
Cancer patients worldwide face suboptimal treatment outcomes due to microbiome-related factors that remain poorly understood and unaddressed in clinical practice.
Traditional oncology approaches overlook how gut dysbiosis compromises immunotherapy effectiveness and overall treatment success, leading to preventable treatment failures across diverse cancer populations.
Evidence
The ONCOBIOME network has generated robust evidence through multi-cohort validation studies across diverse patient populations, cancer types, and disease stages that demonstrate consistent microbiome-cancer outcome relationships.
The consortium has successfully identified and validated gut microbiota signatures that correlate with cancer diagnosis, prognosis, and treatment responses, while establishing clear biological pathways showing how dysbiosis compromises natural and therapy-induced immune surveillance.
Additionally, ONCOBIOME is still populating a unique, microbiome database and demonstrated the proven ability of oncomicrobiome signatures to predict patient treatment responses.
The ONCOBIOME network has generated robust evidence through multi-cohort validation studies across diverse patient populations, cancer types, and disease stages that demonstrate consistent microbiome-cancer outcome relationships.
The consortium has successfully identified and validated gut microbiota signatures that correlate with cancer diagnosis, prognosis, and treatment responses, while establishing clear biological pathways showing how dysbiosis compromises natural and therapy-induced immune surveillance.
Additionally, ONCOBIOME is still populating a unique, microbiome database and demonstrated the proven ability of oncomicrobiome signatures to predict patient treatment responses.
The ONCOBIOME network has generated robust evidence through multi-cohort validation studies across diverse patient populations, cancer types, and disease stages that demonstrate consistent microbiome-cancer outcome relationships.
The consortium has successfully identified and validated gut microbiota signatures that correlate with cancer diagnosis, prognosis, and treatment responses, while establishing clear biological pathways showing how dysbiosis compromises natural and therapy-induced immune surveillance.
Additionally, ONCOBIOME is still populating a unique, microbiome database and demonstrated the proven ability of oncomicrobiome signatures to predict patient treatment responses.
Impact
Through its integrative approach of leveraging multiple cohorts across populations, cancer types and stages, ONCOBIIOME has laid the theoretical and practical foundations for the recognition of microbiota alterations as a hallmark of cancer.
ONCOBIOME has launched microbiota-centered interventions and lobbies in favor of official guidelines for avoiding diet-induced or iatrogenic (for example, antibiotic- or proton pump inhibitor-induced) dysbiosis. Here, we review the key advances of the ONCOBIOME network and discuss the progress toward translating these into oncology clinical practice.
The full Impact of the ONCOBIOME network is summarised in the following Nature Medicine Review.
Through its integrative approach of leveraging multiple cohorts across populations, cancer types and stages, ONCOBIIOME has laid the theoretical and practical foundations for the recognition of microbiota alterations as a hallmark of cancer.
ONCOBIOME has launched microbiota-centered interventions and lobbies in favor of official guidelines for avoiding diet-induced or iatrogenic (for example, antibiotic- or proton pump inhibitor-induced) dysbiosis. Here, we review the key advances of the ONCOBIOME network and discuss the progress toward translating these into oncology clinical practice.
The full Impact of the ONCOBIOME network is summarised in the following Nature Medicine Review.
Through its integrative approach of leveraging multiple cohorts across populations, cancer types and stages, ONCOBIIOME has laid the theoretical and practical foundations for the recognition of microbiota alterations as a hallmark of cancer.
ONCOBIOME has launched microbiota-centered interventions and lobbies in favor of official guidelines for avoiding diet-induced or iatrogenic (for example, antibiotic- or proton pump inhibitor-induced) dysbiosis. Here, we review the key advances of the ONCOBIOME network and discuss the progress toward translating these into oncology clinical practice.
The full Impact of the ONCOBIOME network is summarised in the following Nature Medicine Review.
Use Case 2:
Unraveling the effects of antibiotics on cancer immunotherapy
The impact of antibiotics and PPIs on the overall survival of cancer patient with solid tumours (NSCLC) treated with Immunotherapy.
The impact of antibiotics and PPIs on the overall survival of cancer patient with solid tumours (NSCLC) treated with Immunotherapy.
Goal
Establishing a robust scientific foundation for clinical best practice recommendations on antibiotic use in cancer patients treated with immunotherapy (WP 1) and delivering actionable tools (WP 2 & 3) to prevent ("SPARE"), identify ("ASSESS & PREDICT") and mitigate ("RESTORE") antibiotic-induced dysbiosis to improve patient prognosis.
Establishing a robust scientific foundation for clinical best practice recommendations on antibiotic use in cancer patients treated with immunotherapy (WP 1) and delivering actionable tools (WP 2 & 3) to prevent ("SPARE"), identify ("ASSESS & PREDICT") and mitigate ("RESTORE") antibiotic-induced dysbiosis to improve patient prognosis.
Establishing a robust scientific foundation for clinical best practice recommendations on antibiotic use in cancer patients treated with immunotherapy (WP 1) and delivering actionable tools (WP 2 & 3) to prevent ("SPARE"), identify ("ASSESS & PREDICT") and mitigate ("RESTORE") antibiotic-induced dysbiosis to improve patient prognosis.
The Initial Scientific Focus
Problem
An estimated 30% of patients take antibiotics prior to immunotherapies like immune checkpoint inhibitors, and analyses of more than 40,000 patients have found a strong association between antibiotic use, immune system function, and poorer responses to these promising new treatments. Immunotherapies still only work in a fraction of cancer patients, and it has become a major effort to uncover why.
An estimated 30% of patients take antibiotics prior to immunotherapies like immune checkpoint inhibitors, and analyses of more than 40,000 patients have found a strong association between antibiotic use, immune system function, and poorer responses to these promising new treatments. Immunotherapies still only work in a fraction of cancer patients, and it has become a major effort to uncover why.
An estimated 30% of patients take antibiotics prior to immunotherapies like immune checkpoint inhibitors, and analyses of more than 40,000 patients have found a strong association between antibiotic use, immune system function, and poorer responses to these promising new treatments. Immunotherapies still only work in a fraction of cancer patients, and it has become a major effort to uncover why.
Evidence
Based on the current evidence around antibiotics (ATBs) in cancer immunotherapy, there is substantial associational data from approximately 44,000 patients showing a relationship between antibiotic use and immunotherapy outcomes.
The research includes mechanistic studies conducted in mouse models and roughly three studies examining different antibiotic types administered within 90 days of immunotherapy initiation.
However, the existing data is largely heterogeneous and retrospective in nature, with most studies conducted in the context of metastatic disease, limiting the ability to draw definitive conclusions about the optimal management of antibiotic use during cancer immunotherapy.
Based on the current evidence around antibiotics (ATBs) in cancer immunotherapy, there is substantial associational data from approximately 44,000 patients showing a relationship between antibiotic use and immunotherapy outcomes.
The research includes mechanistic studies conducted in mouse models and roughly three studies examining different antibiotic types administered within 90 days of immunotherapy initiation.
However, the existing data is largely heterogeneous and retrospective in nature, with most studies conducted in the context of metastatic disease, limiting the ability to draw definitive conclusions about the optimal management of antibiotic use during cancer immunotherapy.
Based on the current evidence around antibiotics (ATBs) in cancer immunotherapy, there is substantial associational data from approximately 44,000 patients showing a relationship between antibiotic use and immunotherapy outcomes.
The research includes mechanistic studies conducted in mouse models and roughly three studies examining different antibiotic types administered within 90 days of immunotherapy initiation.
However, the existing data is largely heterogeneous and retrospective in nature, with most studies conducted in the context of metastatic disease, limiting the ability to draw definitive conclusions about the optimal management of antibiotic use during cancer immunotherapy.
Gaps
Despite extensive associational evidence, critical gaps remain regarding antibiotics and immunotherapy outcomes. Causality has not been established, and the mechanistic link between antibiotic-induced microbiome disruption and immunotherapy response remains poorly characterized in humans. Key clinical parameters including specific antibiotic classes, dosing, duration, and indications that may differentially impact outcomes are largely unexplored. The field lacks prospective data and understanding of antibiotic effects in neoadjuvant and adjuvant settings. Additionally, the impact of other microbiome-modifying medications such as proton pump inhibitors and corticosteroids on immunotherapy efficacy remains understudied.
Despite extensive associational evidence, critical gaps remain regarding antibiotics and immunotherapy outcomes. Causality has not been established, and the mechanistic link between antibiotic-induced microbiome disruption and immunotherapy response remains poorly characterized in humans. Key clinical parameters including specific antibiotic classes, dosing, duration, and indications that may differentially impact outcomes are largely unexplored. The field lacks prospective data and understanding of antibiotic effects in neoadjuvant and adjuvant settings. Additionally, the impact of other microbiome-modifying medications such as proton pump inhibitors and corticosteroids on immunotherapy efficacy remains understudied.
Despite extensive associational evidence, critical gaps remain regarding antibiotics and immunotherapy outcomes. Causality has not been established, and the mechanistic link between antibiotic-induced microbiome disruption and immunotherapy response remains poorly characterized in humans. Key clinical parameters including specific antibiotic classes, dosing, duration, and indications that may differentially impact outcomes are largely unexplored. The field lacks prospective data and understanding of antibiotic effects in neoadjuvant and adjuvant settings. Additionally, the impact of other microbiome-modifying medications such as proton pump inhibitors and corticosteroids on immunotherapy efficacy remains understudied.
Use Cases
Pave the way for next generation approaches for microbiome restoration.
The Seerave Global Oncobiome Atlas emerged out of ONCOBIOME and PRIMM, two collaborative research initiatives that significantly contributed to establish the theoretical and practical foundations for the recognition of microbiota alterations as a hallmark of cancer.
We envision that further harmonizing data across different sites and making transparent the pathways through which these resources can be accessed will further accelerate discovery and translation towards patient impact.
Specific use cases for the
Seerave Global Oncobiome Atlas are to:
Unravel microbiome-based diagnostics for cancer
Unravel the effects of antibiotics and other microbiome-modifiers on cancer immunotherapy
Unravel markers of successful microbiome-based correction of cancer-associated dysbiosis