Cancers as Wounds that Do Not Heal: Differences and Similarities and between Renal Regeneration/Repair and Renal
Cell Carcinoma
Joseph Riss, Chand Khanna, Seongjoon Koo, Gadisetti V.R. Chandramouli, Howard H. Yang, Ying Hu, David E. Kleiner,
Andreas Rosenwald, Carl F. Schaefer, Shmuel A. Ben-Sasson, Liming Yang, John Powell, David W. Kane, Robert A. Star, Olga Aprelikova,
Kristin Bauer, James R. Vasselli, Jodi K. Maranchie, Kurt W. Kohn, Ken H. Buetow, W. Marston Linehan, John N. Weinstein,
Maxwell P. Lee, Richard D. Klausner, and J. Carl Barrett
* Laboratory of Molecular
Pharmacology, and tLaboratory of
Biosystems and Cancer
Center for Cancer Research,
National Cancer Institute, Bethesda, Maryland
Cancer Research 2006
Link to Journal (Under construction)
Supplemental Data:
- Supplemental Figure 4. Differentially expressed genes were validated by QPCR
The gene expression of IGFBP1, IGFBP 3, CTGF, AKT, FRAP, MYC, NF-kB, HK1, SIRT7, PHD1, was validated by QPCR. The gene expression
of PHD2 and PHD3 was quantified as well.
- Supplemental Table 4. The RRR 1,325 genes expression data and specific
functional gene-clusters
1,325 unique genes were identified in the current microarray dataset. The gene expression is presented as up or down from
normal-ischemic kidneys. Two separate groups of microarray experiments were conducted, and the results were subsequently normalized
to eliminate systematic bias. The first group consisted of normal and ischemic tissues, as well as and 1 and 2 days post-injury. The
second group consisted of normal kidneys and 5 and 14 days post-injury. The data from days 1 and 2 were normalized by the mean of
the normal-ischemic group, and the data from days 5 and 14 by the mean of the corresponding normal kidney. The genes were further
clustered according to RCC vs. normal kidney; renal cell culture hypoxia responsive genes vs. normoxia; HIF regulated genes; VHL,
IGF1, MYC, NF-kB pathway genes; purine pathway genes; gene expression following renal ischemia reperfusion and/or acute renal
failure (ARF) vs. normal tissue; and gene expression in response to serum (1, 2).
- Supplemental Table 5. An ontology analysis in timely dependent fashion: distinct and common ontologies
Table 5A. The differentially expressed genes were clustered according to
their pattern of expression as early, late or continually RRR. Functional ontology analysis was performed (p<0.05). The presented
ontologies are the ontology core and are hyperlinked to EMBL-EBI. The average RRR expression (log2) of each ontology
is presented in a green to red scale; green down-regulated, red up-regulated. The numbers and average RRR expression of up- and
down- regulated genes, the category p-value and enrichment are shown as well.
Table 5B. The genes in the three phases of renal regeneration and the
concordant and discordant genes are analyzed for GO (summary sheets). These genes were crossed with the data from supplemental
Table 4 (cross sheets); green downregulated and red up-regulated in RRR.
- Supplemental Table 6. The differently expressed genes in both RRR and RCC
exhibited distinct ontologies for the concordance vs. discordance genes
The differentially expressed genes in both RRR and RCC were clustered according to their concordance vs. discordant change.
Functional ontology was analysis performed (p<0.05). The ontologies are hyperlinked to EMBL-EBI. The average RRR expression of
each ontology is presented in a green to red scale; green down-regulated, red up-regulated. The number and average RRR
expression of genes up- / down- regulated in both RRR and RCC, the category p-value and enrichment are also given (the expression
direction and values are as in RRR, relative to the normal kidney).
- Supplemental Table 7. The significance of gene in the various expression
patterns of early, late, continues, pathways and the concordant or discordant groups was analyzed by using the chi square test.
See methods for further explanation.
- Supplemental Table 8. The RRR genes in non-probabilistic GO ontologies
The comprehensive probabilistic analysis may fail to capture many key aspects of the concordant and discordant gene functions.
Therefore, we also categorized the genes into gene-by-gene, non-probabilistic GO.
- Supplemental Table 9. An ontology analysis of the concordant and discordant
genes in pathway dependent fashion: distinct and common ontologies
The concordantly and discordantly differentially expressed genes were clustered according to their regulation by the pathways
of VHL, hypoxia, HIF, IGF1, MYC, p53 and NF-kB. Functional ontology was analysis performed (p<0.05).
- Supplemental text
Contact Information: | Dr. Joseph Riss |
| Wound healing and oncogenesis |
| NCI/ NIH Bldg 37/ Rm. 5046 |
| Mail Stop 4264 |
| 37 Convent MSC 4264 |
| Bethesda, MD 20892 |
| Tel No.: 1-301-402-7203 |
| Fax: 1-301-480-2772 |
| E-Mail: rissjo@mail.nih.gov |
| Link to GBG site |
|
