Researchers completed the genetic sequencing and analyses of more than 11,000 tumors from patients, spanning 33 types of cancer and identifying about 300 genes that drive tumor growth.
Remarkably, they say, just over half of all tumors analyzed carry genetic mutations that therapies already approved for use in patients could target.
The types of cancer are all part of the Cancer Genome Atlas (TCGA) project, launched in 2005 to pursue the genetic basis of cancer. The findings appear in a series of studies in Cell Press journals.
“For the 10,000 tumors we analyzed, we now know in detail the inherited mutations driving cancer and the genetic errors that accumulate as people age, increasing the risk of cancer,” says Li Ding, associate professor of medicine and director of computational biology in the division of oncology at Washington University in St. Louis. “This is the first definitive summary of the genetics behind 33 major types of cancer.”
Cancer is a disease of errors in genes rather than particular organs.
Ding, also an assistant director of the McDonnell Genome Institute at Washington University, is an author of six papers published in Cell (one, two, three), Cell Reports (one, two), and Cell Systems, detailing the genetic mutations underlying cancer.
Genomic studies over the past decade have demonstrated that cancer is a disease of errors in genes rather than particular organs.
“This analysis provides cancer researchers with unprecedented understanding of how, where, and why tumors arise in humans, enabling better-informed clinical trials and future treatments,” says National Institutes of Health Director Francis S. Collins.
The new analyses have revealed that the genetic errors of cancer result in specific molecular signatures that could guide treatment, Ding says.
“Rather than the organ of origin, we can now use molecular features to identify the cancer’s cell of origin,” Ding says. “We are looking at what genes are turned on in the tumor, and that brings us to a particular cell type. For example, squamous cell cancers can arise in the lung, bladder, cervix, and some tumors of the head and neck.
“We traditionally have treated cancers in these areas as completely different diseases. But studying their molecular features, we now know such cancers are closely related. Cancers originating in, for example, epithelial cells that line various organs are similarly closely related, regardless of their location.”
Ding says the research supports the idea that tumors of any type with high numbers of mutations—which often are resistant to chemotherapy—are susceptible to immunotherapy drugs called checkpoint inhibitors.
Highly mutated tumors produce comparatively more misshapen proteins that can trigger an immune response. But as a safeguard against autoimmunity, the body often puts the breaks on such an immune response. Still, to treat aggressive tumors, checkpoint inhibitors can remove those breaks, letting the immune system fight the tumor more effectively.
The studies also further clarify the significance of certain mutations in the BRCA1 gene that drive breast and ovarian cancer. Specific mutations in this gene are known to significantly increase the risk of certain types of cancer. But the consequences of many other mutations in this gene were unknown, making it difficult to predict cancer risk.
“We have known for a long time that BRCA1 is an important gene in cancer development,” Ding says. “But it’s very hard to tease out which specific mutations in BRCA1 are actually driving the cancer and which mutations are harmless.
“Our paper on cancer-causing variants in inherited mutations provides new clarity on the BRCA1 mutations actually driving tumor growth. We found 21 disease-causing BRCA1 and BRCA2 variants in breast cancer, three in cervical cancer, one in colorectal cancer, one in glioblastoma, and 38 in ovarian cancer.”
AI creates ‘maps’ of immune system fighting cancer
Ding says she is particularly excited about the prospect of using these analyses to re-examine data from past clinical trials. Many times, a small proportion of patients in a given trial did well on an experimental therapy, but many others did not respond to the treatment at all, and researchers didn’t understand why. Perhaps a drug was not approved for, say, lung cancer because of such results, but some patients with certain cancer mutations may benefit.
“Most earlier trials were not designed with genomics in mind,” Ding says. “We know how these patients responded. Now, we can sequence the tumor samples from patients enrolled in those trials with our latest software tools. We can look for correlations between the patients’ genomics and how they responded to the treatments.
“If we do this for many past trials, we will have tremendous statistical power to identify reasons why drugs work for some patients and not others. So even negative trials that might have been a disappointment at the time can become powerful tools to design better treatments in the future.”
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In this way, a drug that might have failed as a treatment for lung cancer might be re-examined as a potential therapy for, say, squamous cell carcinoma, again, regardless of location.
“Even after genomic sequencing, sometimes we still can’t explain what is going on,” Ding says. “This is why we are planning to expand beyond studies of the tumor cells to include the entire tumor ecosystem—the immune cells that infiltrate the tumor and the supporting tissue that creates the tumor’s microenvironment.”
The National Institutes of Health provided partial funding.
