Tissue Repository
Health care as we know it today will no longer exist in two more decades. There will be a fundamental shift from treatment to prevention by identifying the earliest footprints of diseases and intervening proactively.
Medicine is already undergoing a revolution through digital healthcare. The use of artificial intelligence (AI), wearable devices, refined scanning techniques, and next-generation sequencing technologies are merging to provide the tell-tale signs of diseases long before they become clinical entities.
Cancer is the prototype of an illness where the only compassionate and universal cure will have to come through early detection and prevention.
So far, our major research investment in cancer has been to develop a treatment for end-stage disease. These treatments are costly, benefit a few patients and exact a horrendous physical toll from the patients. If diagnosed at stage 4, only 15% cancer patients live beyond five years but if diagnosed at Stage 1, 90% will.
The key is early diagnosis.
Our focus has always been on early detection and prevention. I began by studying and treating acute myeloid leukemia (AML) in 1977. By 1984, it was clear to me that AML is too complicated, rapidly evolving a killer to be cured in my lifetime. The fastest way to deal with the problem would be to find it at its earliest manifestation and prevent it from mushrooming into its end-stage monstrosity.
This is why I turned my attention to studying and treating patients with a number of pre-leukemic disorders grouped under the term myelodysplastic syndromes (MDS). A third of MDS patients evolve to AML. My idea was simple. If we follow and carefully study the natural history of MDS, cataloging the changes that mark its evolution to AML, we will be able to develop preventive strategies by targeting earlier and earlier stages of the disease. And when we find the biomarkers of early disease, we could start monitoring at least those individuals at high risk of developing MDS; cancer survivors. Ideally, the early detection could be moved all the way back to continuous monitoring of the healthy population.
From chasing after the last cell to identifying the footprints of the first.
We needed samples to study. I started collecting blood and bone marrow samples from every patient I saw in 1984. Today, the repository has more than 60,000 samples from thousands of patients, many of them have progressed through the entire natural histories of their disease and serial samples were obtained from them at various time points.
A unique aspect of this repository is that samples have been saved at various time points on the same patient as their disease progressed from a pre-leukemia stage to frank acute leukemia. A careful PANOMICS study of these serial samples can yield the sequential disease caused perturbations that herald the appearance of acute leukemia.
Finally, it is the clinical information spanning three decades that constitutes a critical feature of our Tissue Repository because the significance of each genomic, transcriptomic, metabolomics, proteomics change can be tied to the stage of the disease as well as overall survival of the patient.
Why the Tissue Repository is unique:
No one in the world has as longstanding or well annotated a Tissue Bank of MDS-AML patients collected by a single physician. The repository is backed by a computerized data bank containing detailed clinical and pathologic information on each patient in real-time.
Landmark Publications
• A gene, RPS14, was discovered to cause a type of MDS called 5q- Syndrome. (Nature. 2008 Jan 17;451(7176):335-9.)
• Mutations in one of 5 genes have been found to predict survival for MDS patients. (N Engl J Med. 2011 Jun 30;364(26):2496-506).
• Myelodysplastic Syndromes. Nature Cancer Reviews, (12):850-859, 2012.
• A single mutation in b-catenin gene can cause leukemia in mice. Using the Tissue Repository, it was shown that the same pathway is abnormal in 30% MDS and AML patients. Blocking the pathway with a vitamin has already produced spectacular results in some patients. (Nature:(2014) DOI:doi:10.1038).
• Inhibition of leukemia cell engraftment and disease progression in mice by osteoblasts. Blood. 2014 Oct 30;124(18):2834-46.
• Disease-associated mutation in SRSF2 misregulates splicing by altering RNA-binding affinities. Proc Natl Acad Sci U S A. 2015 Aug 10. pii: 201514105
• Disease-associated mutation in SRSF2 misregulates splicing by altering RNA-binding affinities. Proc Natl Acad Sci U S A. 2015 Aug 10. pii: 201514105.
• U2AF35(S34F) Promotes Transformation by Directing Aberrant ATG7 Pre-mRNA 3’ End Formation. Mol Cell 2016; 62:479-90
• Physiologic Expression of Sf3b1(K700E) Causes Impaired Erythropoiesis, Aberrant Splicing, and Sensitivity to Therapeutic Spliceosome Modulation. Cancer Cell. 2016 Sep 12;30(3):404-17. doi: 10.1016/j.ccell.2016.08.006.
• Survey and evaluation of mutations in the human KLF1 transcription unit Sci Rep. 2018 Apr 26;8(1):6587. doi: 10.1038/s41598-018-24962-3.
• Severely impaired terminal erythroid differentiation as an independent prognostic marker in myelodysplastic syndromes. Blood Adv. 2018 Jun 26;2(12):1393-1402. doi: 10.1182/bloodadvances.2018018440.