Renal (Kidney) Cancer: Connections in Metabolism at Krebs cycle and Histone Modulation
Curator: Demet Sag, PhD, CRA, GCP
Through Histone Modulation
Renal cell carcinoma accounts for only 3% of total human malignancies but it is still the most common type of urological cancer with a high prevalence in elderly men (>60 years of age).
Most kidney cancers are renal cell carcinomas (RCC). RCC lacks early warning signs and 70 % of patients with RCC develop metastases. Among them, 50 % of patients having skeletal metastases developed a dismal survival of less than 10 % at 5 years.
There are three main histopathological entities:
- Clear cell RCC (ccRCC), dominant in histology (65%)
- Papillary (15-20%) and
- Chromophobe RCC (5%).
There are very rare forms of RCC shown in collecting duct, mucinous tubular, spindle cell, renal medullary, and MiTF-TFE translocation carcinomas.
Subtypes of clear cell and papillary RCC, and a new subtype, clear cell papillary http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3399969/bin/nihms380694f6.jpg
Different subtypes of clear cell RCC can be defined by HIF patterns as well as by transcriptomic expression as defined by ccA and ccB subtypes. Papillary RCC also demonstrates distinct histological subtypes. A recently described variant denoted as clear cell papillary RCC is VHL wildtype (VHL WT), while other clear cell tumors are characterized by VHL mutation, loss, or inactivation (VHL MT).
KEY POINTS
- Renal cell cancer is a disease in which malignant (cancer) cells form in tubules of the kidney.
- Smoking and misuse of certain pain medicines can affect the risk of renal cell cancer.
- Signs of renal cell cancer include
- Blood in your urine, which may appear pink, red or cola colored
- A lump in the abdomen.
- Back pain just below the ribs that doesn’t go away
- Weight loss
- Fatigue
- Intermittent fever
Factors that can increase the risk of kidney cancer include:
- Older age.
- High blood pressure (hypertension).
- Treatment for kidney failure.(long-term dialysis to treat chronic kidney failure)
- Certain inherited syndromes.
- von Hippel-Lindau disease
Tests that examine the abdomen and kidneys are used to detect (find) and diagnose renal cell cancer.
The following tests and procedures may be used:
There are 3 treatment approaches for Renal Cancer:
Stages of Renal Cancer:
| Stage I |
Tumour of a diameter of 7 cm (approx. 23⁄4 inches) or smaller, and limited to the kidney. No lymph node involvement or metastases to distant organs. |
| Stage II |
Tumour larger than 7.0 cm but still limited to the kidney. No lymph node involvement or metastases to distant organs. |
Stage III
any of the following |
Tumor of any size with involvement of a nearby lymph node but no metastases to distant organs. Tumour of this stage may be with or without spread to fatty tissue around the kidney, with or without spread into the large veins leading from the kidney to the heart. |
| Tumour with spread to fatty tissue around the kidney and/or spread into the large veins leading from the kidney to the heart, but without spread to any lymph nodes or other organs. |
Stage IV
any of the following |
Tumour that has spread directly through the fatty tissue and the fascia ligament-like tissue that surrounds the kidney. |
| Involvement of more than one lymph node near the kidney |
| Involvement of any lymph node not near the kidney |
| Distant metastases, such as in the lungs, bone, or brain. |
| Grade Level |
Nuclear Characteristics |
| Grade I |
Nuclei appear round and uniform, 10 μm; nucleoli are inconspicuous or absent. |
| Grade II |
Nuclei have an irregular appearance with signs of lobe formation, 15 μm; nucleoli are evident. |
| Grade III |
Nuclei appear very irregular, 20 μm; nucleoli are large and prominent. |
| Grade IV |
Nuclei appear bizarre and multilobated, 20 μm or more; nucleoli are prominent |
GENETICS:
90% or more of kidney cancers are believed to be of epithelial cell origin, and are referred to as renal cell carcinoma (RCC), which are further subdivided based on histology into clear-cell RCC (75%), papillary RCC (15%),
chromophobe tumor (5%), and oncocytoma (5%).
Nephrectomy continues to be the cornerstone of treatment for localized renal cell carcinoma (RCC). Research is still underway to developed targeted agents against the vascular endothelial growth factor (VEGF) molecule and related pathways as well as inhibitors of the mammalian target of rapamycin (mTOR),
clear cell RCC (ccRCC) doesn’t respond well to radiation chemotherapy due to high radiation resistancy. The hallmark genetic features of solid tumors such as KRAS or TP53 mutations are also absent. However, there is a well-designed association presented between ccRCC and mutations in the VHL gene
Hereditary RCC, accounts for around 4% of cases, has been a relatively dominant area of RCC genetics.
Causative genes have been identified in several familial cancer syndromes that predispose to RCC including
- VHLmutations in von Hippel-Lindau disease that predispose to ccRCC and VHL is somatically mutated in up to 80% of ccRCC
- METmutations in familial papillary renal cancer,
- dominantly activating kinase domainMET mutation reported in 4–10% of sporadic papillary RCC[2].
- FH (fumarate hydratase) mutations in hereditary leiomyomatosis and renal cell cancer that predispose to papillary RCC
- FLCN(folliculin) mutations in Birt-Hogg-Dubé syndrome that predispose to primarily chromophobe RCC.
In addition, there are germline mutations:
- in theTSC1/2 genes predispose to tuberous sclerosis complex where approximately 3% of cases develop ccRCC,
- in the SDHB(succinate dehydrogenase type B) in patients with paraganglioma syndrome shows elevated risk to develop multiple types of RCC.
GWAS in almost 6000 RCC cases demonstrated that loci on 2p21 and 11q13.3 play a role in RCC. Although EPAS1 gene encoding a transcription factor operative in hypoxia-regulated responses in 2p21 , 11q13.3 has no known coding genes.
There has been, however, comparatively less progress in the elaboration of the somatic genetics of sporadic RCC.
Absent mutations in sporadic RCC:
- somaticFH mutations
- somatic mutations ofTSC12 and SDHB
Present mutations in sporadic ccRCC (chromophobe RCC) are
- TSC1mutations occur in 5% of ccRCCs and
- somatic mutations inFLCN rare
- may predict for extraordinary sensitivity to mTORC1 inhibitors clinically.
The COSMIC database reports somatic point mutations in TP53 in 10% of cases, KRAS/HRAS/NRAS combined ≤1%, CDKN2A 10%, PTEN 3%, RB1 3%, STK11/LKB1 ≤1%, PIK3Ca ≤1%, EGFR1% and BRAF ≤1% in all histological samples. Further information can be found at (http://www.sanger.ac.uk/ genetics/CGP/cosmic/) for the RCC somatic genetics.
HIF- and hypoxia-mediated epigenetic regulation work together due to histone modification because HIF activate several chromatin demethylases, including JMJD1A (KDM3A), JMJD2B (KDM4B), JMJD2C (KDM4C) and JARID1B (KDM5B), all of which are directly targeted by HIF.
Overview of Histone 3 modifications implicated in RCC genetics http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3399969/bin/nihms380694f1.jpg
A number of histone modifying genes are mutated in renal cell carcinoma. These include the H3K36 trimethylase SETD2, the H3K27 demethylase UTX/KDM6A, the H3K4 demethylase JARID1C/KDM5C and the SWI/SNF complex compenent PBRM1, shown in this cartoon to represent their relative activities on Histone H3.
Hyper-methylation is observed on RASSF1 highly (50% f RCC) yet less on VHL and CDKN2A, yet there is a methylation and silencing observed on TIMP3 and secreted frizzled-related protein 2.
RCC is ONE OF THE “CILIOPATHIES” among Polycystic Kidney Disease (PKD), Tuberous Sclerosis Complex (TSC) and VHL Syndrome. The main display of cysts is dysfunctional primary cilia.
Mol Cancer Res. Author manuscript; available in PMC 2013 Jan 1.
Mol Cancer Res. 2012 Jul; 10(7): 859–880. Published online 2012 May 25. doi: 10.1158/1541-7786.MCR-12-0117
pVHL mutants are categorized as Class A, B and C depending on the affected step in pVHL protein quality control http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3399969/bin/nihms380694f2.jpg
VHL proteostasis involves the chaperone mediated translocation of nascent VHL peptide from the ribosome to the TRiC/CCT chaperonin, where folding occurs in an ATP dependent process. The VBC complex is formed while VHL is bound to TRiC, and the mature complex is then released. Three different classes of mutation exist: Class A mutations prevent binding of VHL to TRiC, and abrogate folding into a mature complex. Class B mutations prevent association of Elongins C and B to VHL. Class C mutations inhibit interaction between VHL and HIF1 a.
- familial papillary renal cell carcinoma.
| # 144700. RENAL CELL CARCINOMA, NONPAPILLARY; RCC |
ICD+, Links |
|
NONPAPILLARY RENAL CARCINOMA 1 LOCUS, INCLUDED
Cytogenetic locations: 3p25.3 , 3p25.3 , 3q21.1 , 8q24.13 , 12q24.31 , 17p11.2 , 17q12
Matching terms: renal, familial, papillary, carcinoma, cell |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4358399/bin/467fig3.jpg
Model for the control of the fate of nephron progenitor cells. Eya1 lies genetically upstream of Six2. Six2 labels the nephron progenitor cells, which can either maintain a progenitor state and self-renew or differentiate via the Wnt4-mediated MET. Wnt4 expression is under the direct control of Wt1. β-Catenin is involved in both progenitor cell fates through activation of different transcriptional programs. Active nuclear phosphorylated Yap/Taz shifts the progenitor balance toward the self-renewal fate. Eya1 and Six2 interact directly with Mycn, leading to dephosphorylation of Mycn pT58, stabilization of the protein, increased proliferation, and potentially a shift of the nephron progenitor toward self-renewal. Genes activated in Wilms’ tumors are depicted in green, and inactivated genes are in blue. Deregulation of Yap/Taz in Wilms’ tumors results in phosphorylated Yap not being retained in the cytoplasm as it should, but it translocates to the nucleus and thus shifts the progenitor cell balance toward self-renewal. This model is likely a simplification, as it presumes that all Wilms’ tumors, regardless of causative mutation, are caused by the same mechanism.
Epigenetic aberrations associated with Wilms’ tumor
Chinese Case Study: PMCID: PMC4471788
They u8ndertook this study based on association of low circulating adiponectin concentrations with a higher risk of several cancers, including renal cell carcinoma. Thus they demonstrated that by case–control study that ADIPOQ rs182052 is significantly associated with ccRCC risk.
They investigated the frequency of three single nucleotide polymorphisms (SNPs), rs182052G>A, rs266729C>G, rs3774262G>A, in the adiponectin gene (ADIPOQ). 1004 registered patients with clear cell renal cell carcinoma (ccRCC) compared with 1108 healthy subjects (n = 1108).
The first table presents the characteristics of 1004 patients with clear cell renal cell carcinoma and 1108 cancer-free controls from a Chinese Han population. The Second and third table shows the SNP results.
Table 1: The characteristics of the examined population.
| Variable |
Cases, n (%) |
Controls, n (%) |
P-value† |
| 1004 (100) |
1108 (100) |
| Age, years |
| ≤44 |
195 (19.4) |
230 (20.8) |
0.559 |
| 45–64 |
580 (57.8) |
644 (58.1) |
| ≥65 |
229 (22.8) |
234 (21.1) |
| Sex |
| Male |
711 (70.8) |
815 (73.6) |
0.160 |
| Female |
293 (29.2) |
293 (26.4) |
| BMI, kg/m2 |
| <25 |
480 (47.8) |
589 (53.2) |
0.014 |
| ≥25 |
524 (52.2) |
519 (46.8) |
| Smoking status |
| Never |
455 (45.3) |
529 (47.7) |
0.265 |
| Ever/current |
549 (54.7) |
579 (52.3) |
| Hypertension |
| No |
639 (63.6) |
780 (70.4) |
0.001 |
| Yes |
365 (36.4) |
328 (29.6) |
| Fuhrman grade |
| I |
40 (4.0) |
|
|
| II |
380 (37.8) |
|
|
| III |
347 (34.6) |
|
|
| IV |
175 (17.4) |
|
|
| Missing |
62 (6.2) |
|
|
| Stage at diagnosis |
| I |
738 (73.5) |
|
|
| II |
71 (7.1) |
|
|
| III |
19 (1.9) |
|
|
| IV |
176 (17.5) |
|
|
†Pearson’s χ2-test.
Table 2:
Association between ADIPOQ single nucleotide polymorphisms (SNP) and clear cell renal cell carcinoma risk
| SNP |
HWE |
Cases, n(%) |
Controls, n(%) |
Crude OR (95% CI) |
P-value |
Adjusted OR (95% CI) |
P-value† |
| rs182052 |
| GG |
0.636 |
249 (24.8) |
315 (28.4) |
1.00 |
|
1.00 |
|
| AG |
|
485 (48.3) |
544 (49.1) |
1.13 (0.92–1.39) |
0.253 |
1.11 (0.90–1.37) |
0.331 |
| AA |
|
270 (26.9) |
249 (22.5) |
1.37 (1.08–1.75) |
0.010 |
1.36 (1.07–1.74) |
0.013 |
| AG/AA versusGG |
|
|
|
1.20 (0.99–1.46) |
0.060 |
1.19 (0.98–1.45) |
0.086 |
| AA versusGG/AG |
|
|
|
1.28 (1.04–1.57) |
0.019 |
1.27 (1.04–1.56) |
0.019 |
| rs266729 |
| CC |
0.143 |
502 (50.0) |
572 (51.6) |
1.00 |
|
1.00 |
|
| CG |
|
398 (39.6) |
434 (39.2) |
1.05 (0.88–1.25) |
0.635 |
1.05 (0.87–1.26) |
0.633 |
| GG |
|
104 (10.4) |
102 (9.2) |
1.16 (0.86–1.57) |
0.324 |
1.17 (0.86–1.58) |
0.307 |
| CG/GG versusCC |
|
|
|
1.07 (0.91–1.29) |
0.456 |
1.07 (0.90–1.27) |
0.445 |
| GG versus CC/CG |
|
|
|
1.19 (0.83–1.59) |
0.377 |
1.15 (0.86–1.54) |
0.353 |
| rs3774262 |
| GG |
0.106 |
482 (48.0) |
523 (47.2) |
1.00 |
|
1.00 |
|
| AG |
|
420 (41.8) |
459 (41.4) |
0.99 (0.83–1.20) |
0.938 |
0.99 (0.82–1.19) |
0.905 |
| AA |
|
102 (10.2) |
126 (11.4) |
0.88 (0.66–1.17) |
0.381 |
0.90 (0.67–1.20) |
0.463 |
| AG/AA versusGG |
|
|
|
0.98 (0.80–1.16) |
0.711 |
0.97 (0.82–1.15) |
0.722 |
| AA versusGG/AG |
|
|
|
0.88 (0.67–1.18) |
0.372 |
0.90 (0.68–1.19) |
0.465 |
Bold values indicate significance.
†Adjusted for age, sex, BMI, smoking status, and hypertension. CI, confidence interval; OR, odds ratio; HWE, Hardy–Weinberg equilibrium.
Table 3:
Association between ADIPOQ single nucleotide polymorphisms (SNP) and clear cell renal cell carcinoma risk
| SNP |
HWE |
Cases, n(%) |
Controls, n(%) |
Crude OR (95% CI) |
P-value |
Adjusted OR (95% CI) |
P-value† |
| rs182052 |
| GG |
0.636 |
249 (24.8) |
315 (28.4) |
1.00 |
|
1.00 |
|
| AG |
|
485 (48.3) |
544 (49.1) |
1.13 (0.92–1.39) |
0.253 |
1.11 (0.90–1.37) |
0.331 |
| AA |
|
270 (26.9) |
249 (22.5) |
1.37 (1.08–1.75) |
0.010 |
1.36 (1.07–1.74) |
0.013 |
| AG/AA versusGG |
|
|
|
1.20 (0.99–1.46) |
0.060 |
1.19 (0.98–1.45) |
0.086 |
| AA versusGG/AG |
|
|
|
1.28 (1.04–1.57) |
0.019 |
1.27 (1.04–1.56) |
0.019 |
| rs266729 |
| CC |
0.143 |
502 (50.0) |
572 (51.6) |
1.00 |
|
1.00 |
|
| CG |
|
398 (39.6) |
434 (39.2) |
1.05 (0.88–1.25) |
0.635 |
1.05 (0.87–1.26) |
0.633 |
| GG |
|
104 (10.4) |
102 (9.2) |
1.16 (0.86–1.57) |
0.324 |
1.17 (0.86–1.58) |
0.307 |
| CG/GG versusCC |
|
|
|
1.07 (0.91–1.29) |
0.456 |
1.07 (0.90–1.27) |
0.445 |
| GG versus CC/CG |
|
|
|
1.19 (0.83–1.59) |
0.377 |
1.15 (0.86–1.54) |
0.353 |
| rs3774262 |
| GG |
0.106 |
482 (48.0) |
523 (47.2) |
1.00 |
|
1.00 |
|
| AG |
|
420 (41.8) |
459 (41.4) |
0.99 (0.83–1.20) |
0.938 |
0.99 (0.82–1.19) |
0.905 |
| AA |
|
102 (10.2) |
126 (11.4) |
0.88 (0.66–1.17) |
0.381 |
0.90 (0.67–1.20) |
0.463 |
| AG/AA versusGG |
|
|
|
0.98 (0.80–1.16) |
0.711 |
0.97 (0.82–1.15) |
0.722 |
| AA versusGG/AG |
|
|
|
0.88 (0.67–1.18) |
0.372 |
0.90 (0.68–1.19) |
0.465 |
Bold values indicate significance.
†Adjusted for age, sex, BMI, smoking status, and hypertension. CI, confidence interval; OR, odds ratio; HWE, Hardy–Weinberg equilibrium.
Molecular Genetics Level for Physiology (Function):
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4503866/bin/10585_2015_9731_Fig6_HTML.jpg
a The protein–protein interaction for the identified 8 proteins in STRING (10 necessary proteins/genes were added into the network so as to find the potential strong connection among them. The red dotted lines circled three main pathways. b The ingenuity pathway analysis (IPA) for all these 18 genes showing that oxidative phosphorylation, mitochondria dysfunction and granzyme A are the significantly activated pathways (fold change over 1.5, P < 0.05). c The possible mechanism related mitochondria functions: unspecific condition like inflammation, carcinogens, radiation (ionizing or ultraviolet), intermittent hypoxia, viral infections which is carcinogenesis in our study that damages a cell’s oxidative phosphorylation. Any of these conditions can damage the structure and function of mitochondria thus activating a respiratory chain changes (Complex I, II, III, IV) and also cytochrome c release. When the mitochondrial dysfunction persists, it produces genome instability (mtDNA mutation), and further lead to malignant transformation (metastasis) via increased ROS and apoptotic resistance. (Color figure online)
RENAL CELL CARCINOMA AND METABOLISM goes hand to hand in genes encoding enzymes of the Krebs cycle suppress tumor formation in kidney cells. This includes Succinate dehydrogenase (SDH), Fumarate hydratase (FH). As a result of accumulation of succinate or fumarate causes the inhibition of a family of 2-oxoglutarate-dependent dioxygeneases.
The FH and SDH genes function as two-hit tumor suppressor genes.
SDH has a complex of 4 different polypeptides (SDHA-D) function in electron transfer, catalyzes the conversion of succinate to fumarate. Furthermore, heterozygous germline mutations in SDHsubunits predispose to pheochromocytoma/paraganglioma. FH function to convert fumarate to malate. When its mutations presented as heterozygous germline, it predisposes hereditary leiomyomatosis and renal cell cancer (HLRCC). Among them about 20–50% of HLRCC families are typically papillary-type 2 (pRCC-2) and overwhelmingly aggressive.RCC is increasingly being recognized as a metabolic disease, and key lesions in nutrient sensing and processing have been detected.
Regulation of Prolyl Hydroxylases and Keap1 by Krebs cycle http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3399969/bin/nihms380694f4.jpg
Regulation of Prolyl Hydroxylases by Tricarboxylic Acid (TCA) Cycle Intermediates. Prolyl hydroxylases use TCA cycle intermediates to help catalyze the oxygen, iron and ascorbate dependent- addition of a hydroxyl side chain to a Pro402 and Pro564 of HIF alpha subunits, leading to VHL binding and degradation. Defects in either fumarate hydratase or succinate dehydrogenase will drive up levels of fumarate and succinate, which competitively bind prolyl hydroxylases, and prevent HIF prolyl hydroxylation. This results in higher intracellular HIF levels.
Regulation of mTORC1 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3399969/bin/nihms380694f5.jpg
HIF regulation and mTOR pathway connections. Hypoxia blocks HIF expression in a TSC1/2 and REDD dependent pathway [155]. HIF1α appears to be both TORC1 and TORC2 dependent, whereas HIF2α is only TORC2 dependent [275]. Signaling via TORC2 appears to upregulate HIF2α in an AKT dependent manner [69].
TREATMENT:
Based on the types of renal cancers the treatment method may vary but the general scheme is:
Drugs Approved for Kidney (Renal Cell) Cancer
Food and Drug Administration (FDA) approved drugs for kidney (renal cell) cancer. Some of the drug names link to NCI’s Cancer Drug Information summaries.
T cell regulation in RCC http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3399969/bin/nihms380694f7.jpg
Immune regulation of renal tumor cells. A: When an antigen presenting cell (APC) engages a T-cell via a cognate T-cell receptor (TCR) and CD28, T-cell cell activation occurs. B: Early and late T-cell inhibitory signals are mediated via CTLA-4 and PD-1 receptors, and this occurs via engagement of the APC via B7 and PD-L1, respectively. C: Inhibitory antibodies against CTLA-4 and PD-1 can overcome T-cell downregulation and once again allow cytokine production.
Phase III Trials of Targeted Therapy in Metastatic Renal Cell Carcinoma
| Trial |
Number
of
patients |
Clinical setting |
RR (%) |
PFS (months) |
OS (months) |
| VEGF-Targeted Therapy |
| *AVOREN
Bevacizumab +
IFNa
vs.IFNa[270] |
649 |
First-line |
31 vs. 12 |
10.2 vs. 5.5
(p<0.001) |
23.3 vs. 21.3
(p=0.129) |
| *CALBG 90206
Bevacizumab +
IFNa
vs.IFNa[271] |
732 |
First-line |
25.5 vs. 13 |
8.4 vs. 4.9
(p<0.001) |
18.3 vs. 17.4
(p=0.069) |
Sunitinib vs.
IFNa[248] |
750 |
First-line |
47 vs. 12 |
11 vs. 5
(p=0.0001) |
26.4 vs. 21.8
(p=0.051) |
| *TARGET
Sorafenib vs.
Placebo[272] |
903 |
Second-line
(post-cytokine) |
10 vs. 2 |
5.5 vs. 2.8
(p<0.01) |
17.8vs.15.2
(p=0.88) |
Pazopanib vs.
placebo[273] |
435 |
First line/second line
(post-cytokine) |
30 vs. 3 |
9.2 vs. 4.2
(p<0.0001) |
22.9 vs. 20.5
(p=0.224) |
| *AXIS
Axitinib vs.
sorafenib [269] |
723 |
Second line
(post-sunitinib, cytokine,
bevacizumab or
temsirolimus) |
19 vs. 9
(p=0.0001) |
6.7 vs. 4.7
(p<0.0001) |
Not reported |
| mTOR-Targeted Therapy |
*ARCC
Temsirolimus
vs. Tem + IFNa
vs. IFNa[249] |
624 |
First line, ≥ 3 poor risk
featuresa |
9 vs. 5 |
3.8 vs. 1.9 for
IFNa
monotherapy
(p=0.0001) |
10.9 vs. 7.3 for
IFNa(p=0.008) |
*RECORD-1
Everolimus vs.
placebo [274] |
410 |
Second line
(post sunitinib and/or
sorafenib) |
2 vs. 0 |
4.9 vs. 1.9
(p<0.0001) |
14.8 vs. 14.5 |
RCC renal cell carcinoma, RR response rate, OS overall survival, PFS progression free survival, VEGFvascular endothelial growth factor, IFNa interferon alpha, mTOR mammalian target of rapamycin. AVORENAVastin fOr RENal cell cancer, CALBG Cancer and Leukemia Group B. TARGET Treatment Approaches in Renal Cancer Global Evaluation Trial. AXIS Axitinib in Second Line. ARCC Advanced Renal-Cell Carcinoma. RECORD-1 REnal Cell cancer treatment withOral RAD001 given Daily.
aIncluding serum lactate dehydrogenase level of more than 1.5 times the upper limit of the normal range, a hemoglobin level below the lower limit of the normal range; a corrected serum calcium level of more than 10 mg per deciliter (2.5 mmol per liter), a time from initial diagnosis of renal-cell carcinoma to randomization of less than 1 year, a Karnofsky performance score of 60 or 70, or metastases in multiple organs.
Table: RCC-Associated Antigens (RCCAA) Recognized by T Cells.
| Antigen |
Antigen
Category |
Frequency of
Expression
Among RCC
Tumors (%) |
CD8+ T cell
recognition:
Patients with
HLA Class I
Allele(s) |
CD4+ T cell
recognition:
Patients with
HLA Class II
Allele(s) |
References found in Open Access J Urol. Author manuscript; available in PMC 2013 Jul 8. |
| Survivina |
ML |
100 |
Multiple |
Multiple |
114 |
| OFA-iLR |
OF |
100 |
A2 |
NR |
115, 116 |
| IGFBP3a, b |
ML |
97 |
NR |
Multiple |
117, 118 |
| EphA2a |
ML |
> 90 |
A2 |
DR4 |
17, 44, 119 |
| RU2AS |
Antisense
transcript |
> 90 |
B7 |
NR |
120 |
G250
(CA-IX) a, b |
RCC |
90 |
A2, A24 |
Multiple |
47, 51 |
| EGFRa, b |
ML |
85 |
A2 |
NR |
121, 122 |
| HIFPH3a |
ML |
85 |
A24 |
NR |
123 |
| c-Meta |
ML |
> 80 |
A2 |
NR |
124 |
| WT-1a |
ML |
80 |
A2, A24 |
NR |
125–128 |
| MUC1a, b |
ML |
76 |
A2 |
DR3 |
46, 129, 130 |
| 5T4 |
ML |
75 |
A2, Cw7 |
DR4 |
54, 131–133 |
| iCE |
aORF |
75 |
B7 |
NR |
134 |
| MMP7a |
ML |
75 |
A3 |
Multiple |
117, 135, 136 |
| Cyclin D1a |
ML |
75 |
A2 |
Multiple |
117, 137, 138 |
| HAGE b |
CT |
75 |
A2 |
DR4 |
139 |
| hTERT a, b |
ML |
> 70 |
Mutliple |
Multiple |
140–142 |
| FGF-5 |
Protein splice variant |
> 60 |
A3 |
NR |
143 |
| mutVHLa, b |
ML |
> 60 |
NR |
NR |
144 |
| MAGE-A3 b |
CT |
60 |
Multiple |
Multiple |
145 |
| SART-3 |
ML |
57 |
Mulitple |
NR |
146–149 |
| SART-2 |
ML |
56 |
A24 |
NR |
150 |
| PRAME b |
CT |
40 |
Multiple |
NR |
151–154 |
| p53a, b |
Mutant/WT
ML |
32 |
Mutliple |
Multiple |
155, 156 |
| MAGE-A9b |
CT |
>30 |
A2 |
NR |
157 |
| MAGE-A6b |
CT |
30 |
Mutliple |
DR4 |
18, 158 |
| MAGE-D4b |
CT |
30 |
A25 |
NR |
159 |
| Her2/neua |
ML |
10–30 |
Multiple |
Multiple |
45, 160–164 |
| SART-1a |
ML |
25 |
Multiple |
NR |
165–167 |
| RAGE-1 |
CT (ORF2/5) |
21 |
Mutliple |
Multiple |
151, 157, 168, 169 |
| TRP-1/ gp75 |
ML |
11 |
A31 |
DR4 |
151, 170–172 |
A summary is provided for RCCAA that have been defined at the molecular level. RCCAA are characterized with regard to their antigen category, their prevalence of (over)expression among total RCC specimens evaluated, whether RCCAA expression is modulated by hypoxia or tumor DNA methylation status, and which HLA class I and class II alleles have been reported to serve as presenting molecules for T cell recognition of peptides derived from a given RCCAA.
Abbreviations: CT = Cancer-Testis Antigens; ML = Multi-lineage Antigens; NR = Not Reported; OF = Oncofetal Antigen; aORF = altered open reading frame; ORF = open reading frame; RCC = Renal cell carcinoma; WT = Wild-Type;
aHypoxia-Induced;
bHypomethylation-Induced.
| Expected Impact on Teff versus Suppressor Cells |
| Co-Therapeutic Agent |
Teff
priming |
Teff
function |
Teff
survival |
Teff
(TME) |
Treg/
MDSC |
References found in Open Access J Urol. Author manuscript; available in PMC 2013 Jul 8. |
| Cytokines |
|
|
|
|
|
|
| IL-2 |
↑ |
↑ |
+/− |
↑ |
↑ (Treg) |
173–175 |
| IL-7 |
↑ |
↑ |
↑ |
↑ |
↑ (Treg) |
176–178 |
| IL-12 |
↑ |
↑ |
↑ |
↑ |
– (Treg), ↓ (MDSC) |
179–181 |
| IL-15 |
↑ |
↑ |
↑ |
↑ |
↑ (Treg)* |
182, 183 |
| IL-18 |
↑ |
↑ |
↑ |
↑ |
↓ (Treg) |
184–186 |
| IL-21 |
↑ |
↑ |
↑ |
? |
+/− (Treg) |
187–190 |
| IFN-α |
↑ |
↑ |
↑ |
↑ |
+/− (Treg) |
175, 191–194 |
| IFN-γ |
↑ |
↑ |
-? |
? ↑ |
↑ (Treg); ↑ ?(MDSC) |
195–197 |
| GM-CSF |
↑ |
↑ |
? |
↑ |
↑ (Treg); ↑(MDSC) |
198–202 |
| Coinhibitory Antagonist |
|
|
|
|
|
|
| CTLA-4 |
↑ |
↑ |
? |
↑ |
↓ (Treg) |
203, 204 |
| PD1/PD1L |
↑ |
↑ |
↑ |
↑ |
↓ (Treg) |
205–207 |
| Costimulatory Agonist |
|
|
|
|
|
|
| CD40/CD40L |
↑ |
↑ |
↑ |
↑ |
↑ (Treg); ↑(MDSC) |
208–211 |
| GITR/GITRL |
↑ |
↑ |
↑ |
↑ |
↓ (Treg); ↓ (MDSC) |
212, 213 |
| OX40/OX86 |
↑ |
↑ |
↑ |
↑ |
↑↓ (Treg); ↓ (MDSC) |
214–219 |
| 4-1BB/4-1BBL |
↑ |
↑ |
↑ |
↑ |
↑ (Treg) |
220–224 |
| TLR Agonists |
|
|
|
|
|
|
| Imiquimod (TLR7) |
↑ |
↑ |
↑ |
↑ |
? |
225–227 |
| Resiquimod (TLR8) |
↑ |
↑ |
↑ |
? |
? |
228, 229 |
| CpG (TLR9) |
↑ |
↑ |
↑ |
↑ |
↓ (Treg) |
230–232 |
| Anti-Angiogenic |
|
|
|
|
|
|
| VEGF-Trap |
– |
– |
? |
? |
– |
233 |
| Sunitinib |
↑ |
↑ |
? |
↑ |
↓ (Treg/MDSC) |
98, 100, 234 |
| Sorafenib |
↓ |
↓ |
↓ |
? |
↓ (MDSC) |
235 |
| Bevacizumab |
↑ |
↑ |
? |
? |
↓ (MDSC) |
236, 237 |
| Gefitinib (IRESSA) |
? |
? |
? |
? |
? |
238, 239 |
| Cetuximab |
? |
↑ |
? |
? |
? |
240 |
| mTOR Inhibitors |
|
|
|
|
|
|
| Temsirolimus/Everolimus |
↓ |
↓ |
↓ |
? |
↓ (Treg) |
241 |
| Treg/MDSC Inhibitors |
|
|
|
|
|
|
| Iplimumab (CTLA-4) |
↑ |
↑ |
? |
↑ |
↓ (Treg) |
242, 243 |
| ONTAK (CD25) |
+/− |
+/− |
? |
? |
↓ (Treg) |
244 |
| Anti-TGFβ/TGFβR |
↑ |
↑ |
↑ |
↑ |
↓ (Treg) |
245–247 |
| Anti-IL10/IL10R |
↑ |
↑ |
↑ |
+/− |
↓ (Treg) |
248, 249 |
| Anti-IL35/IL35R |
↑? |
↑? |
↑? |
↑? |
↓ (Treg) |
250 |
| 1-methyl trytophan |
↑ |
↑ |
? |
? |
↓ (MDSC) |
251 |
| ATRA |
↑ |
↑ |
? |
? |
↑ (Treg), ↓ (MDSC) |
90–93 |
Agents that are currently or soon-to-be in clinical trials are summarized with regard to their anticipated impact(s) on Type-1 anti-tumor T cell (Te) activation, function, survival and recruitment into the TME. Additional anticipated effects of drugs on suppressor cells (Treg and MDSC) are also summarized. Key: ↑, agent is expected to increase parameter; ↓, agent is expected to inhibit parameter; +/−, minimal increase or decrease is expected in parameter as a consequence of treatment with agent; ?, unknown effect of agent on parameter.
Abbreviations: ATRA, all-trans retinoic acid; CTLA-4, cytotoxic T Lymphocyte antigen 4; GITR(L), glucocorticoid-induced TNF receptor (ligand); GM-CSF, granulocyte-macrophage colony stimulating factor; IFN, interferon; IL, interleukin; MDSC, myeloid-derived suppressor cell; PD1/PD1L, programmed cell death 1 (ligand); TGF-β(R), tumor necrosis factor-β(receptor); TLR, Toll-like receptor; TME, tumor microenvironment; Treg, regulatory T cell; VEGF, vascular endothelial growth factor.
Alternative and Complementary Therapies for Cancer:
- Art therapy
- Dance or movement therapy
- Exercise
- Meditation
- Music therapy
- Relaxation exercises
Mol Cancer Res. 2012 Jul; 10(7): 859–880. Published online 2012 May 25. doi: 10.1158/1541-7786.MCR-12-0117 PMCID: PMC3399969 NIHMSID: NIHMS380694
State-of-the-science: An update on renal cell carcinoma
Eric Jonasch,1 Andrew Futreal,1 Ian Davis,2 Sean Bailey,2 William Y. Kim,2 James Brugarolas,3 Amato Giaccia,4 Ghada Kurban,5 Armin Pause,6 Judith Frydman,4 Amado Zurita,1 Brian I. Rini,7 Pam Sharma,8Michael Atkins,9 Cheryl Walker,8,* and W. Kimryn Rathmell2,*
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[Discovery Medicine; ISSN: 1539-6509; Discov Med 18(101):341-350, December 2014.Copyright © Discovery Medicine. All rights reserved.]
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