The field of lung cancer research has experienced many breakthroughs in recent years, particularly in precision medicine where oncologists can match genetic mutations to targeted therapies. However, many perplexing questions remain. Why does cancer impact some people and not others? Why do some people respond well to treatments and others don’t? For all the progress, we still have a long way to go.

Over the past two decades, numerous advances in lung cancer treatment have been achieved through genomics. And, while this science has made significant headway, some of the biggest current challenges in lung cancer may be well served by augmenting genomics with other approaches. Because metabolites both influence and are influenced by genetics, proteins and microbiomes, metabolomics can be used in conjunction with genomics to create a more complete understanding of health and treatment response. Specifically, metabolomics is poised to help drive solutions to questions such as: Which people will respond to immunotherapies like immune checkpoint blockade (ICB) – and why others don’t? How do we best understand treatment resistance (particularly in more rare types of lung cancer)? And, how can cancer be detected at earlier stages when the treatments are more tractable?

Notably, although many patients experience durable responses to ICB, the majority do not respond. While the precise factors and predictive biomarkers have remained elusive, some clues exist. In particular, the microbiome has been convincingly linked to response to immunotherapies such as immune checkpoint blockade including in certain types of lung cancers[1].

However, the precise mechanisms and even specific microbial strains driving differences in response to immunotherapies remain elusive. Given that metabolomics is increasingly being recognized as the pivotal approach for determining microbiome function, its use will likely be key to finding biomarkers in response/non-response immunotherapy.

In the context of lack of response to immune checkpoint blockade and determining the factors that may limit or drive response, another layer to consider is what’s happening beyond the tumor. Here is where the branches of genomics and metabolomics can really come together and work in harmony to uncover more insights. What’s happening in the person’s immune system overall is just as important as what’s happening in the tumor. Metabolomics can help us understand both of these activities. Metabolites in the circulation or the tumor microenvironment will likely be important when combined with gene signatures or profiles of the immune cell types that are present in the tumor.

Additionally, metabolomics provides implications for early detection of cancer by combining with other liquid biopsy approaches. In the future we may be able to study the microbiome of patients and see who may be a good candidate for certain therapies as well as who may be most at risk for developing cancer. Or, a circulating metabolite, combined with other diagnostic criteria may help to identify cancer at an earlier stage of the disease.

With cancer, early detection often leads to the best results for curing the disease, but small-cell and non-small-cell cancers are often detected late.

A recent study involving lymphangioleiomyomatosis (LAM) provides a powerful example of how metabolomics can advance lung disease research. LAM is a slow metastasizing neoplasm that is typically due to tuberous sclerosis complex 2 (TSC2) gene mutations resulting in mTORC1 activation in proliferative smooth muscle–like cells in the lung. Metabolon collaborated with researchers at Harvard Medical School to better understand these drivers and, through metabolomics, identified a signature that served as a biomarker. Researchers were able to target the disease based on that signature and identified a novel therapeutic target for lung disease – TSC2 as a negative regulator of COX-2 expression and prostaglandin biosynthesis. This approach, could be applied to lung cancers to better identify drivers of disease, especially in different subtypes such as non-responders.

There is still much to learn about lung cancer and related therapies. Metabolomics reveals biological insights otherwise unseen by other ‘omic technologies, and by combining this powerful technology with the great insights we’ve already seen through genomics, we can accelerate our understanding of lung cancer, and thus, its treatment.

Metabolon can help you take the research to even deeper levels and uncover more actionable insights. Contact us at to get started.


Routy B, Chatelier EL, Derosa L, Duong CPM, Alou MT, Daillère R, et al. Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors. Science. 2017Feb;359(6371):91–7.