Can microbes diagnose cancer?

And while liquid biopsy methods have progressed significantly, there remain limitations to their efficacy and utility. The possibility of sample contamination during collection, processing and sequencing limits these investigations, as procedural controls have rarely been implemented in cancer genomics projects and false negatives are not uncommon.

“While there has been amazing progress in the area of liquid biopsy and early cancer detection, current liquid biopsies aren’t yet able to reliably distinguish normal genetic variation from true early cancer, and they can’t pick up cancers where human genomic alterations aren’t known or aren’t detectable,” said Dr. Sandip Pravin Patel, who serves as the deputy director of the San Diego Center for Precision Immunotherapy in addition to being the co-leader of experimental therapeutics at Moores Cancer Center at UC San Diego Health of the University of California, San Diego.

After watching his grandmother succumb to pancreatic cancer in a matter of months, Gregory Poore, a researcher at UC San Diego and colleague of Patel, delved deeper into a 2017 study in Science that suggested that microbes invade cancer cells in a way that impeded the efficacy of chemotherapy drugs. In research conducted in the lab of Dr. Rob Knight, professor and director of the Center for Microbiome Innovation, Poore and his team have found compelling evidence that microbial DNA may offer a previously unrecognized window in cancer diagnosis.

“Almost all previous cancer research efforts have assumed tumors are sterile environments and ignored the complex interplay human cancer cells may have with the bacteria, viruses and other microbes that live in and on our bodies. The number of microbial genes in our bodies vastly outnumbers the number of human genes, so it shouldn’t be surprising that they give us important clues to our health,” Knight explained.

Their study, published in March 2020 in Nature, details the methodology of their work to confirm the role of microbial analysis in the diagnosis of cancer. They began by re-examining whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia–IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumor DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3 percent of total sequence data.

According to the study, they could also discriminate among samples from healthy, cancer-free individuals and those from patients with multiple types of cancer (prostate, lung and melanoma; 100 samples in total) solely using plasma-derived, cell-free microbial nucleic acids. Using machine learning, researchers were able to correctly identify people with lung cancer in 86-percent sensitivity while identifying a non-diseased person with 100-percent specificity. They were able to distinguish between those three cancer types and could often tell which participants had which of the three manifestations. For example, the models could correctly distinguish between a person with prostate cancer and a person with lung cancer with 81-percent sensitivity.

“The ability, in a single tube of blood, to have a comprehensive profile of the tumor’s DNA (nature) as well as the DNA of the patient’s microbiota (nurture), so to speak, is an important step forward in better understanding host-environment interactions in cancer,” said Patel.

While the possibilities unearthed through this research are extremely exciting, the team is quick to acknowledge some potential limitations. While performing well in these initial tests, there remains a possibility that that blood-based microbial DNA readings could miss some signs of cancer and provide a false negative, or, conversely, pick up on non-cancer-related DNA changes that could lead to a false or premature positive. Likewise, a positive indicator stemming from a microbial test would likely require additional diagnostic tests in order to confirm, stage and locate a tumor.

“It is important to understand that we just opened the pandora box on how microbiome and cancer tissue and healthy adjacent host tissue may interact. Their role could well be on a cancer by cancer basis. For example, in some cases, the microbiome may be sent by the host as an offensive mechanism against the cancer or, in some cases, the cancer tissue may be recruiting the microbe in their micro-environment to provide them with necessary ‘nutrients’,” adds Dr. Sandrine Miller-Montgomery, executive director of the Center for Microbiome Innovation.