by Azra Raza
To detect the first cancer cell’s footprints, a map of early biologic markers of cancer has to be constructed. This is what our resources should be targeting. Thankfully, the race has already begun. We will all benefit from cooperation at the deepest level. Heed the advice of an anonymous sage who said, “If you want to be incrementally better: be competitive. If you want to be exponentially better: be cooperative.”
For the life of a creature is in the blood.
—LEVITICUS 17:11
It began at the junction of the mother and child: the placenta. The question was whether congenital diseases in a growing fetus were detectable by seeking their footprints in the mother’s blood instead of the amniotic fluid. The embryo is known to exfoliate cells that cross the placenta and enter the mother’s bloodstream, but capturing and examining these fetal cells for detailed molecular analysis proved to be a challenge because they were so few. The quantity issue was resolved when fetal DNA, known as cell-free fetal, or cff-DNA, was found circulating in the maternal blood during pregnancy. Shed by the placenta in large enough quantities, cff-DNA was promptly utilized for noninvasive prenatal screening (NIPS) of congenital diseases in the developing fetus. NIPS, using a few cubic centimeters of blood drawn from the mother, has proved to be the most sensitive method for prenatal diagnosis of Down syndrome.
Analysis of cff-DNA has displaced amniocentesis. Can similar techniques be developed whereby surrogate markers released into the blood by a growing tumor are detected? This would provide not just early cancer diagnosis but also save the patient from undergoing an invasive biopsy procedure. In healthy individuals, cell-free DNA, or cf-DNA, is found in the blood but in very tiny amounts. In cancer patients, however, circulating tumor DNA, or ct-DNA, derived from dying cancer cells, is detectable in higher quantities even in early stages of tumor formation because immune cells fail to clear it efficiently from the blood. This ct-DNA can be subjected to molecular profiling and serve as the noninvasive “liquid biopsy” comparable to NIPS. Much effort has been devoted to developing liquid biopsies that can noninvasively identify the presence of genetic material from cancer cells in the blood or molecular markers in urine or saliva to diagnose cancer at its inception or even precancerous lesions. What are these surreptitious, clandestine, cloaked, surrogate markers?
One is the mutated DNA discarded by dying malignant cells. The second is transcripts of messenger RNA transmitting instructions for abnormal protein synthesis or the proteins themselves. All three can serve as biomarkers for malignancy, all three can be detected in the blood. While germ line DNA is exactly the same in all cells of an organism, the transcriptome and proteome differ depending upon cell lineage. The transcriptome and proteome of a white blood cell would be different from that of a brain cell, whereas DNA in both would be the same. Early signs of a cancerous growth could be traced through mutations in the DNA or abnormal expression of sets of RNA and proteins. Ideally, a measure of all three will be combined in the future for a truly comprehensive picture using no more than a single drop of blood, urine, or saliva. The population-based screening trials to establish the clinical relevance of these approaches would require massive cooperation between academia, institutions, industry, and oncologists.
There is much exciting work going on in the area of detecting the first rather than the last cancer cell. Large-scale, population-based studies are being conducted by several commercial entities to test the accuracy and clinical utility of their methods of screening, and the results are regularly posted in the public domain. It is the responsibility of government institutions to provide a coordinated, collaborative approach designed to systematically study the common deadly human tumors and provide a road map for progress in a timely fashion. In the following sections, we will briefly look at some of the ongoing attempts in this area.
MicroRNAs are small regulatory RNAs that don’t code for proteins. They are frequently dysregulated in cancer, and because they are present in human plasma in a remarkably stable form, they can provide robust information on otherwise unrecognized malignancies. A comprehensive database showing unique profiles important for different types of cancers remains to be assembled, but serious research is already under way at multiple levels in this area. Using digital microfluidics—a decentralized, automated, and affordable platform called a lab on a chip that requires only one drop of blood to do its work—microRNA diagnostic signatures of various common cancers, such as lung, ovarian, and gastric tumors, are being generated. At present, only 1 percent of endoscopies yield a diagnosis of cancer. A full 99 percent are performed in vain. With this blood test, only a selected few would need to undergo the invasive procedure, resulting in tremendous cost savings also. A panel of eight microRNAs demonstrated robust diagnostic accuracy in not only tissue specimens but also in the plasma specimens from stage I ovarian cancer patients. Similarly, microRNA signatures serving as diagnostic, prognostic, and predictive biomarkers for early breast cancer are being formalized. MicroRNA signatures for lung cancers exist. Preoperative plasma levels of four microRNAs (specifically, miR-29a, 200b, 203, and 31) can serve as potential prognostic biomarkers in colorectal cancers, and detection of miR-31, 141, and 16 levels in the plasma herald recurrence during colorectal cancer surveillance. The microRNA field is practically in its infancy but will receive the attention of researchers if the funding agencies make it their priority.
Detection of circulating tumor-derived DNA (ct-DNA) from the blood could provide a safe and reliable platform for early detection of cancer. Former vice president Biden’s Cancer Moonshot initiative is undertaking the Blood Profiling Atlas in Cancer project, which will collect data on cancer signals in the blood. Because ct-DNA carries the somatic alterations of the tumor, it is a more reliable test but presents challenges related to the number of genes that would have to be sequenced to cover the most frequent mutations seen in common cancers. The depth of sequencing would have to be dense also to distinguish small amounts of ct-DNA from much higher levels of cf-DNA shed by normal cells. A reference library of cancer mutations versus those found in matched healthy donors is under creation now. This ten-thousand-plus-subject study, called the Circulating Cell-Free Genome Atlas (CCGA), will be the largest database of mutations found in the blood of cancer patients.
Once ct-DNA is detected, the next challenge is to identify the organ source from which it is derived. The specific mutations would be helpful in tracing the tissue of origin since the patterns of somatic alterations for specific tumor types have been well described. To prevent overtreatment, it would be critical to separate the aggressive tumor types from less invasive ones. Recognition of unique associations of lethality with ct-DNA profiles on serial sampling would help refine these distinctions. Even if the tissue of origin is traced and the tumor removed in a timely fashion, there is no guarantee that occult metastases are not already operating elsewhere. In patients at risk of developing certain cancers like those with mutations in BRCA1 or BRCA2 genes (at risk of breast and ovarian cancers), or smokers at risk of lung cancer, the ct-DNA results can be supplemented with organ-specific tests and imaging. Finally, if detectable after tumor resection, presence of ct-DNA is associated with a high risk of recurrence in patients with breast and colon cancers, as well as with non-small-cell lung cancer. In these cases, ct-DNA can be used to monitor the success of therapy.
The ability to distinguish a cancer patient from a healthy individual is not enough; some tumors grow so slowly that detecting them early and treating them aggressively could be more of a health hazard for the patient than simply letting the cancer grow. Ideally, a biomarker for early detection of cancer should be able to provide clues to the source organ and the potential aggressiveness of the disease. In other words, the information has to be actionable. Detection of proteins unique to a tumor cell would be the ideal biomarker, as they would provide both diagnostic information and serve as a therapeutic target. Tests to measure blood-borne proteins, such as PSA, CEA, and CA-125, have been available for decad
es. They are helpful in early detection, but for even earlier detection, a collection of antigens—or what might be called a protein signature of an occult tumor, as opposed to a single protein—is likely to provide a more comprehensive view. Proteomics is not as well developed so far as the study of genomes or transcriptomes. There are many reasons for this related to sampling errors, lack of technology, and bioinformatics support. To detect large numbers of proteins, well-characterized antibodies have to be available. A new method using antibody microarrays is now available for this purpose. Large-scale studies for protein signatures have not been conducted yet. The Cancer Moonshot initiative could help in this area.
Another interesting biomarker is the exosome. These are small vesicles pinched off from cells and shed into body fluids like blood, saliva, and urine, and they carry signals for intercellular communication. Their role in cancer, in coagulation, and in waste management is well recognized; exosomes can serve as biomarkers of many diseases. They are collected from blood and analyzed for their cargo. Those derived from cancer cells can provide clues to their cells of origin. They serve as the advance party, deployed to scout fresh target organs for the metastatic spread of cancer. They carry oncoproteins, RNA, DNA fragments, and lipids from malignant donor cancer cells to recipient host organ cells in local and distant sites, preparing the microenvironment, making it suitable to receive and house the arriving cancer. Exosomes help create the premetastatic niche in new areas and promote disease progression. Proteomic, transcriptomic, and genomic analysis of exosomes has led to the identification of markers that can serve as liquid biopsies for a variety of solid tumors like colorectal cancers, brain tumors, and breast and prostate malignancies. High-throughput platforms for clinical utilization of exosome-based diagnostics have been developed. One microfluidic device can profile exosomal microRNAs. Exosome-based diagnostics provide more specific information in comparison to other liquid biopsy biomarkers because they are more stable. Finally, exosomes can serve as vehicles to deliver cancer drugs and vaccines.
Following the exosomes preparing new sites for metastasis are the cells that tumors release in the bloodstream. Like exosomes, these circulating tumor cells (CTCs) can be captured through liquid biopsies to help in early cancer detection. They can also serve as prognostic markers and to monitor response to treatment and early relapse. As few as one abnormal cell can be detected from a cubic centimeter of blood using technologies such as the isolation-by-size-of-epithelial-tumors (ISET) methodology. Captured on filters, these rare circulating cells can be studied using immune markers and histochemical stains for further characterization. In one study, no CTCs were detected in the blood of six hundred healthy volunteers, while all patients with diagnosed cancer showed the presence of CTC detected with the ISET technology, CTC counts being higher in more advanced cases. With further technologic refinement in accuracy and specificity, CTC monitoring can become a part of routine periodic checkups in healthy individuals.
The heyday of reductionism, looking for one culprit gene at a time and searching for the one magic bullet, is over. The era of big data, cloud computing, artificial intelligence, and wearable sensors has arrived. The study of cancer is evolving into a data-driven, quantitative science. Merging information obtained from liquid biopsies (RNA, DNA, proteomics, exosome studies, CTC) with histopathology, radiologic, and scanning techniques, aided by rapid machine learning, image reconstruction, intelligent software, and microfluidics can—and will—revolutionize the way we diagnose and prevent rather than treat cancer in the future. The ideal strategy will emerge from harnessing cutting-edge technology for a multidisciplinary systems biology approach through a consilience of scientists with expertise in molecular genetics, imaging, chemistry, physics, engineering, mathematics, and computer science.
Leroy Hood has done precisely this with his Institute for Systems Biology in Seattle. He has initiated a novel concept designed to detect disease in its earliest stage through health care that is predictive, preventive, personalized, and participatory (P4). By using detection of disease-perturbed networks in otherwise healthy individuals and finding solutions early, Hood is pioneering a new health care discipline termed scientific wellness. Through application of systems biology and P4 strategies, cancer care can finally be personalized in its truest sense.
The challenges after an abnormal cell is detected early are to determine the organ it is coming from, its malignant potential, and finding the means to eliminate it immediately. At least for MDS and AML, we are well equipped to begin the exploration using the tissue repository. Selected samples studied by panomics to understand the natural history of the preleukemia and its transition to acute leukemia would lead to an understanding of changes at the RNA, DNA, and protein level involved in the transformation. Studies of microRNA, cell-free DNA, and exosomes from the serum as well as the clonal response of immune cells as the disease progresses are of critical value in defining stage-specific markers of disease perturbations. Once we have the early markers of disease transition from preleukemia to acute leukemia, these markers can provide the missing “address” of cancer cells to the body’s immune cells. As already noted, when cancer cells are detected at such an early stage, the first issue is to determine whether the tumor is aggressive or not because nonaggressive ones may as well be left alone. This research is ideally conducted on banked samples where the outcome for the patients over a period of a decade or more is known. For example, MDS patients whose serial bone marrows are stored in the repository can be studied for markers that identify patients likely to progress to leukemia and die early versus those who lived with MDS for more than ten years.
Once we have the biomarkers to identify its potential lethality, attacking the cancer early will be lifesaving. The strategy to eliminate early cancer has to be a better one than the traditional slash-poison-burn approach. The presently evolving cellular therapeutics would be ideal for targeting those few abnormal cells with laser-like precision.
Advances in our understanding of the immune system have led to therapies based on using the body’s own soldiers, such as T cells and natural killer cells, to target cancer from the inside. The supreme efficiency of CAR-T cells becomes a problem in treating advanced cancers because of their overefficiency—they kill off any cell expressing the marker they are seeking, including normal cells. With more discriminating addresses being developed to target cancers, this supreme competence can be turned to our advantage by directing the CAR-Ts to cancer cells when their number is low. This would avoid all the life-threatening cytokine storms and tumor lysis syndromes associated with destruction of large hunks of tumor tissue. In the case of MDS, as soon as an early marker is detected—waving a red flag that the first acute leukemia cells have arisen—the markers can be used to arm and activate immune cells to home in on their target. The same strategy of identifying markers on the earliest cancer cells of all types—breast, lung, prostate, GI—is now being developed. Elegant studies, especially those coming from Bert Vogelstein’s group at Johns Hopkins University, have already elaborated various aspects of this proposal.
Research is also ongoing in all these areas funded by the National Institutes of Health, but the investment remains paltry compared to funding provided for studies conducted on cell lines and animal models. Through redirection of intellectual and financial resources from the same old grant proposals to grant incentives for early detection using actual human samples, and by posing exciting challenges to competitive scientists, progress will be accelerated dramatically. The piece that is missing from the equation is an admission of failure of current strategies and a willingness to take a 180-degree turn to start all over again. We already invest a lot of effort to find minimal residual disease. Why not apply the same rigor and focus to minimal initial disease?
From the perspective of my lab, with the tissue repository at its disposal, this new approach to investigating cancer would start with a focused, systems biology approach to interrogate the first thousand samples of
serum and bone marrow from patients who either died early (within two years) or late (after five years). So far, we have compared small numbers of patients in these types of sets using one or at most two of the omics technologies—for example, quantifying the messenger RNA for gene expression profiling and/or sequencing the DNA to look for mutations in targeted genes. Studying large numbers of patients simultaneously using every technology available to examine RNA, DNA, and protein expression in multiple compartments (blood, bone marrow, buccal smears, circulating T cells) is more likely to yield complex signatures with strong clinical associations than have been discovered with limited samples. This discovery-set data, examined exhaustively by the latest technology, would then be used to characterize the next group, a test set of another few thousand samples from the tissue repository, for confirmation of the biomarkers. The refined signatures would then be used in a prospective validation set of samples for final and ultimate application to the clinical setting of living, dynamic patient populations. Such a thorough, retrospective analysis of the tissue repository studied through a systems biology approach has the best chance of yielding clues to perfect our diagnostic, prognostic, and therapeutic capabilities. Novel targets will emerge when important proteins or gene mutational profiles together suggest activations of heretofore unsuspected signaling pathways.
