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Konrad Huppi, Ph.D.

Portait Photo of Konrad Huppi
Genetics Branch
Gene Silencing Section
Staff Scientist
Center for Cancer Research
National Cancer Institute
Building 37, Room 6128
Bethesda, MD 20892


Dr. Huppi obtained his degree in immunology from the University of Pennsylvania in 1984. Originally, he studied immunoglobulin gene structure with Susumu Tonegawa at the Basel Institute for Immunology, and later worked on somatic mutation of immunoglobulin genes with Martin Weigert at the Fox Chase Cancer Center in Philadelphia. His research moved from antibody gene structure to plasma cell tumors when he joined the Laboratory of Genetics at the NCI under Dr. Michael Potter in 1984. Specializing in the construction of gene libraries, Dr. Huppi's lab has been instrumental in the cloning and sequencing of a large number of genes including mouse Cdn1ka, p107, BCL3 and PARP. In 1990, Dr. Huppi cloned several noncoding transcripts in the region of human 8q24 known as PVT1. Most recently, Dr. Huppi has returned to PVT1 in the Gene Silencing Section of Natasha Caplen to discover that a cluster of miRNAs is transcribed from this region and may be overexpressed as a result of chromosomal translocation, retroviral integration or gene amplification in a number of B cell, T cell or solid tumors. Through the construction of miRNA containing lentiviruses, Dr. Huppi is currently pursuing the targets of these miRNAs.


Co-localization of miRNAs with regions of genomic instability

A correlation between the proximity of human chromosomal fragile sites and the location of the regulatory small non-coding RNAs, termed microRNAs (miRs), has suggested another means by which altered gene expression in tumors might be achieved (Calin et al.,PNAS, 2004). We have recently extended this initial observation to a large-scale study of overlapping retroviral integration sites (RIS) or translocation (Tx) breakpoints (~345) and the genomic location of miRs (~319) in the mouse (Huppi et al., Seminars in Cancer Biology, 2007). Utilizing the Jenkins-Copeland mouse Retrovirus Tagged Cancer Gene Database ( and the Sanger miRNA registry (, we had found that a significantly large number (47%) of mouse miRs reside in clusters (51), many of which overlap with clusters of RIS. Since both of these databases have just recently been updated (miRBase Release 10.1, RTCGD Aug. 2007 using UCSC mm8), we have adjusted the locations of RIS and miRs accordingly by using the C57BL/6 whole genome contig as the reference. We also now find 74 clusters (within 1Mb) representing 69.5% of the total number (442) of miRNAs in the mouse genome. Of these, 44 are paired while there are 14 clusters of 3 members alone. Several other clusters contain multiple members (>3) including mmu-miR-669b on the proximal end of chromosome 2 (9 members), mmu-miR-302b on chromosome 3 (5), mmu-miR-182 on proximal chromosome 6 (6), mmu-miR-709 on chromosome 8 (6), mmu-miR-342 on chromosome 12 (49), mmu-713 on chromosome 13 (4), mmu-miR17-92 on chromosome 14 (6) and the mmu-miR PVT1 cluster (6) and mmu-miR-688 (4) on chromosome 15. On chromosome X alone, there are three large clusters of microRNAs of 5 (mmu-miR-500), 13 (mmu-miR-717) and 14 members (mmu-miR-743a).
This strategy continues to reveal many instances where miRs and RIS overlap very closely ( As an example, a cluster of RIS located on mouse chromosome 11 resides within 10kb of mmu-miR-142 and one RIS (583) actually interrupts the processing of the miR transcript. In a B-cell leukemia, the human counterpart, hsa-miR-142, is similarly interrupted by the breakpoint of a T(8;17) Tx (Lagos-Quintana et al., Curr. Biol.2002). In another example, a large number of RIS are located 1.6-22.0kb from a cluster of miRs (miR-92-2) on mouse chromosome X and in a recent report, Wabl and colleagues have demonstrated that the 92-2 cluster is up-regulated directly as a result of the integration events (Lum et al., Retrovirology, 2007). The mouse homologue (mmu-miR-17-20a) of the hsa-miR-17-92 cluster in humans is the apparent target of a significant cluster of RIS on mouse chromosome 14. While many of the RIS are found within 10kb of the miR17-20a cluster, at least one RIS (Lnz25-2) is found only 945bp from mmu-miR-17. In a study of T cell lymphomas generated by RIS, the entire miR-17-20a cluster appears to be up-regulated in all 22 lymphomas as a result of the integration (Wang et al., PNAS 2006). In the absence of known gene targets, we would suggest that RIS may be targeting miRs which in turn results in an alternative means of de-regulating gene expression.

The Identification of MicroRNAs in a Genomically Unstable Region of Human Chromosome 8q24

In several instances, we have observed clusters of RIS not associated with any known miRs, suggesting potential areas to focus on in the search for as yet undiscovered miRNAs. To demonstrate the efficacy of this approach, we have focused on a region of instability on human Chr. 8q24 (and mouse Chr. 15) known as PVT1 which resides distal to the MYC proto-oncogene and which is the frequent site of variant Txs [T(8;22), T(2;8) in human Burkitt Lymphoma (BL) or T(6;15), T(15;16) in mouse plasmacytoma (PCT)]. Since PVT1, although transcriptionally active, is not known to encode a protein, we suspect that this region of 400kb might harbor novel miRs. The entire PVT1 region was subjected to detailed in silico analysis using the criteria of permissive stem-loop structure and species conservation, and 15 candidate miRNAs were identified. By Northern blot analysis, seven novel miRs have been experimentally validated and the primary miRNA sequence of two of them has been established by 5' RACE. Using real-time RT-PCR of precursors, both of these novel miRs show higher levels of expression in variant BL and PCT tumors as well as in MYC/PVT1 co-amplified breast or colon carcinomas. In addition, we have found that expression of both miRs increases with the maturation of B cells suggesting these miRs may be involved in the development of lymphoid cells. Over-expression studies of these novel miRNAs are under way in cell lines and mouse models to test for biologic effects and to identify potential protein-encoding transcript targets.

This page was last updated on 3/11/2014.