Large-scale database mining reveals hidden trends and future directions for cancer immunotherapy

Kather, Jakob Nikolas; Berghoff, Anna Sophie; Ferber, Dyke; Suarez-Carmona, Meggy; Reyes-Aldasoro, Constantino Carlos; Valous, Nektarios A.; Rojas-Moraleda, Rodrigo; Jäger, Dirk; Halama, Niels

doi:10.1080/2162402x.2018.1444412

Cited by 13 publications

(9 citation statements)

References 30 publications

(28 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Need for shared access to data that has already been captured concerning RT and immunotherapy. 48 Development of an immunotherapy registry to collect data on RT use during immunotherapy. Need for an efficient and novel clinical trial design that still ensures patient safety.…”

Section: Radiation Dose and Fractionation: Considerations For Imminent And Future Clinical Trialsmentioning

confidence: 99%

Radiation dose and fraction in immunotherapy: one-size regimen does not fit all settings, so how does one choose?

Demaria

Guha

Schoenfeld

et al. 2021

J Immunother Cancer

151

121

View full text Add to dashboard Cite

Recent evidence indicates that ionizing radiation can enhance immune responses to tumors. Advances in radiation delivery techniques allow hypofractionated delivery of conformal radiotherapy. Hypofractionation or other modifications of standard fractionation may improve radiation’s ability to promote immune responses to tumors. Other novel delivery options may also affect immune responses, including T-cell activation and tumor-antigen presentation changes. However, there is limited understanding of the immunological impact of hypofractionated and unique multifractionated radiotherapy regimens, as these observations are relatively recent. Hence, these differences in radiotherapy fractionation result in distinct immune-modulatory effects. Radiation oncologists and immunologists convened a virtual consensus discussion to identify current deficiencies, challenges, pitfalls and critical gaps when combining radiotherapy with immunotherapy and making recommendations to the field and advise National Cancer Institute on new directions and initiatives that will help further development of these two fields.This commentary aims to raise the awareness of this complexity so that the need to study radiation dose, fractionation, type and volume is understood and valued by the immuno-oncology research community. Divergence of approaches and findings between preclinical studies and clinical trials highlights the need for evaluating the design of future clinical studies with particular emphasis on radiation dose and fractionation, immune biomarkers and selecting appropriate end points for combination radiation/immune modulator trials, recognizing that direct effect on the tumor and potential abscopal effect may well be different. Similarly, preclinical studies should be designed as much as possible to model the intended clinical setting. This article describes a conceptual framework for testing different radiation therapy regimens as separate models of how radiation itself functions as an immunomodulatory ‘drug’ to provide alternatives to the widely adopted ‘one-size-fits-all’ strategy of frequently used 8 Gy×3 regimens immunomodulation.

show abstract

Section: Radiation Dose and Fractionation: Considerations For Imminent And Future Clinical Trialsmentioning

confidence: 99%

Radiation dose and fraction in immunotherapy: one-size regimen does not fit all settings, so how does one choose?

Demaria

Guha

Schoenfeld

et al. 2021

J Immunother Cancer

151

121

View full text Add to dashboard Cite

show abstract

“…Careful analyses of the immunological parameters of the local microenvironment have revealed the presence of multiple complex regulatory systems at the tissue level. 46,163–166 The local microenvironment in different organ sites, particularly in metastatic disease, needs to be targeted specifically to enable immunotherapy to be successful. Furthermore, data from clinical trials and limited preclinical models underscore the interdependency between the innate immune system and the adaptive immune response.…”

Section: Optimisation Of Immunotherapy: Innate and Adaptive Immunity mentioning

confidence: 99%

Harnessing the innate immune system and local immunological microenvironment to treat colorectal cancer

Kather

Halama

2019

Br J Cancer

Self Cite

View full text Add to dashboard Cite

Significant progress in the development of new immunotherapies has led to successful clinical trials for malignant melanoma and non-small cell lung cancer; however, for the majority of solid tumours of the gastrointestinal tract, little or no progress has been seen. The efficacy of immunotherapies is limited by the complexities of a diverse set of immune cells, and interactions between the tumour cells and all other cells in the local microenvironment of solid tumours. A large fraction of immune cells present in and around solid tumours derive from the innate arm of the immune system and using these cells against tumours offers an alternative immunotherapeutic option, especially as current strategies largely harness the adaptive arm of the immune system. This option is currently being investigated and attempts at using the innate immune system for gastrointestinal cancers are showing initial results. Several important factors, including cytokines, chemotherapeutics and the microbiome, influence the plasticity and functionality of innate (myeloid) cells in the microenvironment, and this complexity of regulation has limited translation into successful trials so far. In this review, current concepts of the immunobiology of the innate arm in the tumour microenvironment are presented in the context of clinical translation.

show abstract

“…While most of these studies have focused on the tumor cells, the stromal compartment—defined as all nontumor components of cancer tissue—is moving into the focus of biomarker research in oncology [24]. In solid tumors such as colorectal cancer (CRC), lymphocytes and fibroblasts profoundly shape the tumor microenvironment and have a significant impact on clinical end points [25,26].…”

Section: Introductionmentioning

confidence: 99%

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study

et al. 2019

Self Cite

View full text Add to dashboard Cite

BackgroundFor virtually every patient with colorectal cancer (CRC), hematoxylin–eosin (HE)–stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers. In the present study, we investigated whether deep convolutional neural networks (CNNs) can extract prognosticators directly from these widely available images.Methods and findingsWe hand-delineated single-tissue regions in 86 CRC tissue slides, yielding more than 100,000 HE image patches, and used these to train a CNN by transfer learning, reaching a nine-class accuracy of >94% in an independent data set of 7,180 images from 25 CRC patients. With this tool, we performed automated tissue decomposition of representative multitissue HE images from 862 HE slides in 500 stage I–IV CRC patients in the The Cancer Genome Atlas (TCGA) cohort, a large international multicenter collection of CRC tissue. Based on the output neuron activations in the CNN, we calculated a “deep stroma score,” which was an independent prognostic factor for overall survival (OS) in a multivariable Cox proportional hazard model (hazard ratio [HR] with 95% confidence interval [CI]: 1.99 [1.27–3.12], p = 0.0028), while in the same cohort, manual quantification of stromal areas and a gene expression signature of cancer-associated fibroblasts (CAFs) were only prognostic in specific tumor stages. We validated these findings in an independent cohort of 409 stage I–IV CRC patients from the “Darmkrebs: Chancen der Verhütung durch Screening” (DACHS) study who were recruited between 2003 and 2007 in multiple institutions in Germany. Again, the score was an independent prognostic factor for OS (HR 1.63 [1.14–2.33], p = 0.008), CRC-specific OS (HR 2.29 [1.5–3.48], p = 0.0004), and relapse-free survival (RFS; HR 1.92 [1.34–2.76], p = 0.0004). A prospective validation is required before this biomarker can be implemented in clinical workflows.ConclusionsIn our retrospective study, we show that a CNN can assess the human tumor microenvironment and predict prognosis directly from histopathological images.

show abstract

Large-scale database mining reveals hidden trends and future directions for cancer immunotherapy

Cited by 13 publications

References 30 publications

Radiation dose and fraction in immunotherapy: one-size regimen does not fit all settings, so how does one choose?

Radiation dose and fraction in immunotherapy: one-size regimen does not fit all settings, so how does one choose?

Harnessing the innate immune system and local immunological microenvironment to treat colorectal cancer

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study

Contact Info

Product

Resources

About