Posts Tagged ‘Therapy’

Digital Therapeutics: A threat or opportunity to pharmaceuticals

Reporter and Curator: Dr. Sudipta Saha, Ph.D.


Digital Therapeutics (DTx) have been defined by the Digital Therapeutics Alliance (DTA) as “delivering evidence based therapeutic interventions to patients, that are driven by software to prevent, manage or treat a medical disorder or disease”. They might come in the form of a smart phone or computer tablet app, or some form of a cloud-based service connected to a wearable device. DTx tend to fall into three groups. Firstly, developers and mental health researchers have built digital solutions which typically provide a form of software delivered Cognitive-Behaviour Therapies (CBT) that help patients change behaviours and develop coping strategies around their condition. Secondly there are the group of Digital Therapeutics which target lifestyle issues, such as diet, exercise and stress, that are associated with chronic conditions, and work by offering personalized support for goal setting and target achievement. Lastly, DTx can be designed to work in combination with existing medication or treatments, helping patients manage their therapies and focus on ensuring the therapy delivers the best outcomes possible.


Pharmaceutical companies are clearly trying to understand what DTx will mean for them. They want to analyze whether it will be a threat or opportunity to their business. For a long time, they have been providing additional support services to patients who take relatively expensive drugs for chronic conditions. A nurse-led service might provide visits and telephone support to diabetics for example who self-inject insulin therapies. But DTx will help broaden the scope of support services because they can be delivered cost-effectively, and importantly have the ability to capture real-world evidence on patient outcomes. They will no-longer be reserved for the most expensive drugs or therapies but could apply to a whole range of common treatments to boost their efficacy. Faced with the arrival of Digital Therapeutics either replacing drugs, or playing an important role alongside therapies, pharmaceutical firms have three options. They can either ignore DTx and focus on developing drug therapies as they have done; they can partner with a growing number of DTx companies to develop software and services complimenting their drugs; or they can start to build their own Digital Therapeutics to work with their products.


Digital Therapeutics will have knock-on effects in health industries, which may be as great as the introduction of therapeutic apps and services themselves. Together with connected health monitoring devices, DTx will offer a near constant stream of data about an individuals’ behavior, real world context around factors affecting their treatment in their everyday lives and emotional and physiological data such as blood pressure and blood sugar levels. Analysis of the resulting data will help create support services tailored to each patient. But who stores and analyses this data is an important question. Strong data governance will be paramount to maintaining trust, and the highly regulated pharmaceutical industry may not be best-placed to handle individual patient data. Meanwhile, the health sector (payers and healthcare providers) is becoming more focused on patient outcomes, and payment for value not volume. The future will say whether pharmaceutical firms enhance the effectiveness of drugs with DTx, or in some cases replace drugs with DTx.


Digital Therapeutics have the potential to change what the pharmaceutical industry sells: rather than a drug it will sell a package of drugs and digital services. But they will also alter who the industry sells to. Pharmaceutical firms have traditionally marketed drugs to doctors, pharmacists and other health professionals, based on the efficacy of a specific product. Soon it could be paid on the outcome of a bundle of digital therapies, medicines and services with a closer connection to both providers and patients. Apart from a notable few, most pharmaceutical firms have taken a cautious approach towards Digital Therapeutics. Now, it is to be observed that how the pharmaceutical companies use DTx to their benefit as well as for the benefit of the general population.





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Immunotherapy may help in glioblastoma survival

Reporter and Curator: Dr. Sudipta Saha, Ph.D.


Glioblastoma is the most common primary malignant brain tumor in adults and is associated with poor survival. But, in a glimmer of hope, a recent study found that a drug designed to unleash the immune system helped some patients live longer. Glioblastoma powerfully suppresses the immune system, both at the site of the cancer and throughout the body, which has made it difficult to find effective treatments. Such tumors are complex and differ widely in their behavior and characteristics.


A small randomized, multi-institution clinical trial was conducted and led by researchers at the University of California at Los Angeles involved patients who had a recurrence of glioblastoma, the most common central nervous system cancer. The aim was to evaluate immune responses and survival following neoadjuvant and/or adjuvant therapy with pembrolizumab (checkpoint inhibitor) in 35 patients with recurrent, surgically resectable glioblastoma. Patients who were randomized to receive neoadjuvant pembrolizumab, with continued adjuvant therapy following surgery, had significantly extended overall survival compared to patients that were randomized to receive adjuvant, post-surgical programmed cell death protein 1 (PD-1) blockade alone.


Neoadjuvant PD-1 blockade was associated with upregulation of T cell– and interferon-γ-related gene expression, but downregulation of cell-cycle-related gene expression within the tumor, which was not seen in patients that received adjuvant therapy alone. Focal induction of programmed death-ligand 1 in the tumor microenvironment, enhanced clonal expansion of T cells, decreased PD-1 expression on peripheral blood T cells and a decreasing monocytic population was observed more frequently in the neoadjuvant group than in patients treated only in the adjuvant setting. These findings suggest that the neoadjuvant administration of PD-1 blockade enhanced both the local and systemic antitumor immune response and may represent a more efficacious approach to the treatment of this uniformly lethal brain tumor.


Immunotherapy has not proved to be effective against glioblastoma. This small clinical trial explored the effect of PD-1 blockade on recurrent glioblastoma in relation to the timing of administration. A total of 35 patients undergoing resection of recurrent disease were randomized to either neoadjuvant or adjuvant pembrolizumab, and surgical specimens were compared between the two groups. Interestingly, the tumoral gene expression signature varied between the two groups, such that those who received neoadjuvant pembrolizumab displayed an INF-γ gene signature suggestive of T-cell activation as well as suppression of cell-cycle signaling, possibly consistent with growth arrest. Although the study was not powered for efficacy, the group found an increase in overall survival in patients receiving neoadjuvant pembrolizumab compared with adjuvant pembrolizumab of 13.7 months versus 7.5 months, respectively.


In this small pilot study, neoadjuvant PD-1 blockade followed by surgical resection was associated with intratumoral T-cell activation and inhibition of tumor growth as well as longer survival. How the drug works in glioblastoma has not been totally established. The researchers speculated that giving the drug before surgery prompted T-cells within the tumor, which had been impaired, to attack the cancer and extend lives. The drug didn’t spur such anti-cancer activity after the surgery because those T-cells were removed along with the tumor. The results are very important and very promising but would need to be validated in much larger trials.




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Tumor Organoids Used to Speed Cancer Treatment

Reporter: Irina Robu, PhD

Collecting cancer cells from patients and growing them into 3-D mini tumors could make it possible to quickly screen large numbers of potential drugs for ultra-rare cancers. Preliminary success with a new high-speed, high-volume approach is already guiding treatment decisions for some patients with recurring hard-to-treat cancers.

A London-based team labelled how a “tumor-in-a-dish” approach positively forecasted drug responses in cancer patients who previously took part in clinical trials. That study was a major development in a new research area focused on “organoids” — tiny 3-D versions of the brain, gut, lung and other organs grown in the lab to probe basic biology or test drugs.

UCLA cancer biologist Alice Soragni and her colleagues developed a high-volume, automated method to rapidly study drug responses in tumor organoids grown from patient cells. By studying mini tumors grown on a plate with 96 tiny test tubes, her team can screen hundreds of compounds at once and classify promising candidates within a time frame that is therapeutically actionable. According to Dr. Soragni, the method seemed to work for various kinds of ovarian cancer. It was shown that the lab-grown organoids mimicked how tumors in the body look and behave. And even in cases when mini tumors had a hard time growing in a dish, scientists still acknowledged potential drug candidates.
Up to now, the UCLA team has produced organoids from 35 to 40 people with various types of sarcoma which will allow them to classify tumors that won’t respond to conventional therapy. This proves useful for people with recurrent metastases, where it’s not clear if we’re doing anything for their overall survival or giving them more toxicity.


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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).

ICD10 C64
ICD9-CM 189.0
ICD-O M8312/3
OMIM 144700 605074
DiseasesDB 11245
MedlinePlus 000516
eMedicine med/2002

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:

  1. Clear cell RCC (ccRCC), dominant in histology (65%)
  2. Papillary (15-20%) and
  3. 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

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).


  • 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



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 ( 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

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

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.

Cytogenetic locations: 3p25.3 , 11q13.3
Matching terms: lindau, disease, von, hippellindau, hippel
  • Birt-Hogg-Dube syndrome,
Cytogenetic location: 17p11.2 
Matching terms: birthoggdube, syndrome, birt, hogg, dube
  • tuberous sclerosis
# 191100. TUBEROUS SCLEROSIS 1; TSC1 ICD+, Links
Cytogenetic location: 9q34.13 
Matching terms: tuber, sclerosi, tuberous
  • familial papillary renal cell carcinoma.
Cytogenetic locations: 3p25.3 3p25.3 3q21.1 8q24.13 12q24.31 17p11.2 17q12 
Matching terms: renal, familial, papillary, carcinoma, cell

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 (= 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)
 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)
 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
 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
 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
 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
 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
 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
 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):

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

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

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].


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

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
Clinical setting RR (%) PFS (months) OS (months)
VEGF-Targeted Therapy

Bevacizumab +

649 First-line 31 vs. 12 10.2 vs. 5.5
23.3 vs. 21.3
*CALBG 90206

Bevacizumab +

732 First-line 25.5 vs. 13 8.4 vs. 4.9
18.3 vs. 17.4
Sunitinib vs.
750 First-line 47 vs. 12 11 vs. 5
26.4 vs. 21.8

Sorafenib vs.

903 Second-line


10 vs. 2 5.5 vs. 2.8
Pazopanib vs.
435 First line/second line


30 vs. 3 9.2 vs. 4.2
22.9 vs. 20.5

Axitinib vs.
sorafenib [269]

723 Second line

(post-sunitinib, cytokine,
bevacizumab or

19 vs. 9
6.7 vs. 4.7
Not reported
mTOR-Targeted Therapy
vs. Tem + IFNa
vs. IFNa[249]
624 First line, ≥ 3 poor risk
9 vs. 5 3.8 vs. 1.9 for
10.9 vs. 7.3 for
Everolimus vs.
placebo [274]
410 Second line
(post sunitinib and/or
2 vs. 0 4.9 vs. 1.9


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 alphamTOR 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.

PMC full text: Open Access J Urol. Author manuscript; available in PMC 2013 Jul 8.

Open Access J Urol. 2010 Aug; 2010(2): 125–141. doi:  10.2147/RRU.S7242

Table: RCC-Associated Antigens (RCCAA) Recognized by T Cells.

Antigen Antigen
Frequency of
Among RCC
Tumors (%)
CD8+ T cell
Patients with
HLA Class I
CD4+ T cell
Patients with
HLA Class II
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 115116
IGFBP3ab ML 97 NR Multiple 117118
EphA2a ML > 90 A2 DR4 1744119
RU2AS Antisense
> 90 B7 NR 120
(CA-IX) ab
RCC 90 A2, A24 Multiple 4751
EGFRab ML 85 A2 NR 121122
HIFPH3a ML 85 A24 NR 123
c-Meta ML > 80 A2 NR 124
WT-1a ML 80 A2, A24 NR 125128
MUC1ab ML 76 A2 DR3 46129130
5T4 ML 75 A2, Cw7 DR4 54131133
iCE aORF 75 B7 NR 134
MMP7a ML 75 A3 Multiple 117135136
Cyclin D1a ML 75 A2 Multiple 117137138
HAGE b CT 75 A2 DR4 139
hTERT ab ML > 70 Mutliple Multiple 140142
FGF-5 Protein splice variant > 60 A3 NR 143
mutVHLab ML > 60 NR NR 144
MAGE-A3 b CT 60 Multiple Multiple 145
SART-3 ML 57 Mulitple NR 146149
SART-2 ML 56 A24 NR 150
PRAME b CT 40 Multiple NR 151154
p53ab Mutant/WT
32 Mutliple Multiple 155156
MAGE-A9b CT >30 A2 NR 157
MAGE-A6b CT 30 Mutliple DR4 18158
MAGE-D4b CT 30 A25 NR 159
Her2/neua ML 1030 Multiple Multiple 45160164
SART-1a ML 25 Multiple NR 165167
RAGE-1 CT (ORF2/5) 21 Mutliple Multiple 151157168169
TRP-1/ gp75 ML 11 A31 DR4 151170172

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;



PMC full text: Open Access J Urol. Author manuscript; available in PMC 2013 Jul 8.

Open Access J Urol. 2010 Aug; 2010(2): 125–141. doi:  10.2147/RRU.S7242

Expected Impact on Teff versus Suppressor Cells
Co-Therapeutic Agent Teff
References found in Open Access J Urol. Author manuscript; available in PMC 2013 Jul 8.
IL-2 +/− ↑ (Treg) 173175
IL-7 ↑ (Treg) 176178
IL-12 – (Treg), ↓ (MDSC) 179181
IL-15 ↑ (Treg)* 182183
IL-18 ↓ (Treg) 184186
IL-21 ? +/− (Treg) 187190
IFN-α +/− (Treg) 175191194
IFN-γ -? ? ↑ ↑ (Treg); ↑ ?(MDSC) 195197
GM-CSF ? ↑ (Treg); ↑(MDSC) 198202
Coinhibitory Antagonist
CTLA-4 ? ↓ (Treg) 203204
PD1/PD1L ↓ (Treg) 205207
Costimulatory Agonist
CD40/CD40L ↑ (Treg); ↑(MDSC) 208211
GITR/GITRL ↓ (Treg); ↓ (MDSC) 212213
OX40/OX86 ↑↓ (Treg); ↓ (MDSC) 214219
4-1BB/4-1BBL ↑ (Treg) 220224
TLR Agonists
Imiquimod (TLR7) ? 225227
Resiquimod (TLR8) ? ? 228229
CpG (TLR9) ↓ (Treg) 230232
VEGF-Trap ? ? 233
Sunitinib ? ↓ (Treg/MDSC) 98100234
Sorafenib ? ↓ (MDSC) 235
Bevacizumab ? ? ↓ (MDSC) 236237
Gefitinib (IRESSA) ? ? ? ? ? 238239
Cetuximab ? ? ? ? 240
mTOR Inhibitors
Temsirolimus/Everolimus ? ↓ (Treg) 241
Treg/MDSC Inhibitors
Iplimumab (CTLA-4) ? ↓ (Treg) 242243
ONTAK (CD25) +/− +/− ? ? ↓ (Treg) 244
Anti-TGFβ/TGFβR ↓ (Treg) 245247
Anti-IL10/IL10R +/− ↓ (Treg) 248249
Anti-IL35/IL35R ↑? ↑? ↑? ↑? ↓ (Treg) 250
1-methyl trytophan ? ? ↓ (MDSC) 251
ATRA ? ? ↑ (Treg), ↓ (MDSC) 9093

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,*

Go to:


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Robert C, Ribas A, Wolchok JD, Hodi FS, Hamid O, Kefford R, Weber JS, Joshua AM, Hwu WJ, Gangadhar TC, Patnaik A, Dronca R, Zarour H, Joseph RW, Boasberg P, Chmielowski B, Mateus C, Postow MA, Gergich K, Elassaiss-Schaap J, et al. Anti-programmed-death-receptor-1 treatment with pembrolizumab in ipilimumab-refractory advanced melanoma: a randomised dose-comparison cohort of a phase 1 trial. Lancet 384(9948):1109-1117, 2014.

Robert C, Thomas L, Bondarenko I, O’day S, M DJ, Garbe C, Lebbe C, Baurain JF, Testori A, Grob JJ, Davidson N, Richards J, Maio M, Hauschild A, Miller WH Jr, Gascon P, Lotem M, Harmankaya K, Ibrahim R, Francis S, et al. Ipilimumab plus dacarbazine for previously untreated metastatic melanoma. N Engl J Med 364(26):2517-2526, 2011.

Sheridan C. Cautious optimism surrounds early clinical data for PD-1 blocker. Nat Biotechnol30(8):729-730, 2012.

Tarhini AA, Cherian J, Moschos SJ, Tawbi HA, Shuai Y, Gooding WE, Sander C, Kirkwood JM. Safety and efficacy of combination immunotherapy with interferon alfa-2b and tremelimumab in patients with stage IV melanoma. J Clin Oncol 30(3):322-328, 2012.

Topalian SL, Drake CG, Pardoll DM. Targeting the PD-1/B7-H1(PD-L1) pathway to activate anti-tumor immunityCurr Opin Immunol 24(2):207-212, 2012a.

Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, Mcdermott DF, Powderly JD, Carvajal RD, Sosman JA, Atkins MB, Leming PD, Spigel DR, Antonia SJ, Horn L, Drake CG, Pardoll DM, Chen L, Sharfman WH, Anders RA, Taube JM, et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med 366(26):2443-2454, 2012b.

Waterhouse P, Penninger JM, Timms E, Wakeham A, Shahinian A, Lee KP, Thompson CB, Griesser H, Mak TW. Lymphoproliferative disorders with early lethality in mice deficient in Ctla-4. Science270(5238):985-988, 1995.

Weber JS, Kähler KC, Hauschild A. Management of immune-related adverse events and kinetics of response with ipilimumab. J Clin Oncol 30(21):2691-2697, 2012.

Weber JS, Minor DR, D’Angelo S, Hodi FS, Gutzmer R, Neyns B, Hoeller C, Khushalani NI, Miller WH, Grob J, Lao C, Linette G, Grossmann K, Hassel J, Lorigan P, Maio M, Sznol M, Lambert A, Yang A, Larkin J. A phase 3 randomized, open-label study of nivolumab (anti-PD-1; BMS-936558; ONO-4538) versus investigator’s choice chemotherapy (ICC) in patients with advanced melanoma after prior anti-CTLA-4 therapy. ESMO Annual Meetings. Abstract #LBA3_PR. 2014.

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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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Imaging-guided cancer treatment

Imaging-guided cancer treatment

Writer & reporter: Dror Nir, PhD

It is estimated that the medical imaging market will exceed $30 billion in 2014 (FierceMedicalImaging). To put this amount in perspective; the global pharmaceutical market size for the same year is expected to be ~$1 trillion (IMS) while the global health care spending as a percentage of Gross Domestic Product (GDP) will average 10.5% globally in 2014 (Deloitte); it will reach ~$3 trillion in the USA.

Recent technology-advances, mainly miniaturization and improvement in electronic-processing components is driving increased introduction of innovative medical-imaging devices into critical nodes of major-diseases’ management pathways. Consequently, in contrast to it’s very small contribution to global health costs, medical imaging bears outstanding potential to reduce the future growth in spending on major segments in this market mainly: Drugs development and regulation (e.g. companion diagnostics and imaging surrogate markers); Disease management (e.g. non-invasive diagnosis, guided treatment and non-invasive follow-ups); and Monitoring aging-population (e.g. Imaging-based domestic sensors).

In; The Role of Medical Imaging in Personalized Medicine I discussed in length the role medical imaging assumes in drugs development.  Integrating imaging into drug development processes, specifically at the early stages of drug discovery, as well as for monitoring drug delivery and the response of targeted processes to the therapy is a growing trend. A nice (and short) review highlighting the processes, opportunities, and challenges of medical imaging in new drug development is: Medical imaging in new drug clinical development.

The following is dedicated to the role of imaging in guiding treatment.

Precise treatment is a major pillar of modern medicine. An important aspect to enable accurate administration of treatment is complementing the accurate identification of the organ location that needs to be treated with a system and methods that ensure application of treatment only, or mainly to, that location. Imaging is off-course, a major component in such composite systems. Amongst the available solution, functional-imaging modalities are gaining traction. Specifically, molecular imaging (e.g. PET, MRS) allows the visual representation, characterization, and quantification of biological processes at the cellular and subcellular levels within intact living organisms. In oncology, it can be used to depict the abnormal molecules as well as the aberrant interactions of altered molecules on which cancers depend. Being able to detect such fundamental finger-prints of cancer is key to improved matching between drugs-based treatment and disease. Moreover, imaging-based quantified monitoring of changes in tumor metabolism and its microenvironment could provide real-time non-invasive tool to predict the evolution and progression of primary tumors, as well as the development of tumor metastases.

A recent review-paper: Image-guided interventional therapy for cancer with radiotherapeutic nanoparticles nicely illustrates the role of imaging in treatment guidance through a comprehensive discussion of; Image-guided radiotherapeutic using intravenous nanoparticles for the delivery of localized radiation to solid cancer tumors.

 Graphical abstract


One of the major limitations of current cancer therapy is the inability to deliver tumoricidal agents throughout the entire tumor mass using traditional intravenous administration. Nanoparticles carrying beta-emitting therapeutic radionuclides [DN: radioactive isotops that emits electrons as part of the decay process a list of β-emitting radionuclides used in radiotherapeutic nanoparticle preparation is given in table1 of this paper.) that are delivered using advanced image-guidance have significant potential to improve solid tumor therapy. The use of image-guidance in combination with nanoparticle carriers can improve the delivery of localized radiation to tumors. Nanoparticles labeled with certain beta-emitting radionuclides are intrinsically theranostic agents that can provide information regarding distribution and regional dosimetry within the tumor and the body. Image-guided thermal therapy results in increased uptake of intravenous nanoparticles within tumors, improving therapy. In addition, nanoparticles are ideal carriers for direct intratumoral infusion of beta-emitting radionuclides by convection enhanced delivery, permitting the delivery of localized therapeutic radiation without the requirement of the radionuclide exiting from the nanoparticle. With this approach, very high doses of radiation can be delivered to solid tumors while sparing normal organs. Recent technological developments in image-guidance, convection enhanced delivery and newly developed nanoparticles carrying beta-emitting radionuclides will be reviewed. Examples will be shown describing how this new approach has promise for the treatment of brain, head and neck, and other types of solid tumors.

The challenges this review discusses

  • intravenously administered drugs are inhibited in their intratumoral penetration by high interstitial pressures which prevent diffusion of drugs from the blood circulation into the tumor tissue [1–5].
  • relatively rapid clearance of intravenously administered drugs from the blood circulation by kidneys and liver.
  • drugs that do reach the solid tumor by diffusion are inhomogeneously distributed at the micro-scale – This cannot be overcome by simply administering larger systemic doses as toxicity to normal organs is generally the dose limiting factor.
  • even nanoparticulate drugs have poor penetration from the vascular compartment into the tumor and the nanoparticles that do penetrate are most often heterogeneously distributed

How imaging could mitigate the above mentioned challenges

  • The inclusion of an imaging probe during drug development can aid in determining the clearance kinetics and tissue distribution of the drug non-invasively. Such probe can also be used to determine the likelihood of the drug reaching the tumor and to what extent.

Note: Drugs that have increased accumulation within the targeted site are likely to be more effective as compared with others. In that respect, Nanoparticle-based drugs have an additional advantage over free drugs with their potential to be multifunctional carriers capable of carrying both therapeutic and diagnostic imaging probes (theranostic) in the same nanocarrier. These multifunctional nanoparticles can serve as theranostic agents and facilitate personalized treatment planning.

  • Imaging can also be used for localization of the tumor to improve the placement of a catheter or external device within tumors to cause cell death through thermal ablation or oxidative stress secondary to reactive oxygen species.

See the example of Vintfolide in The Role of Medical Imaging in Personalized Medicine


Note: Image guided thermal ablation methods include radiofrequency (RF) ablation, microwave ablation or high intensity focused ultrasound (HIFU). Photodynamic therapy methods using external light devices to activate photosensitizing agents can also be used to treat superficial tumors or deeper tumors when used with endoscopic catheters.

  • Quality control during and post treatment

For example: The use of high intensity focused ultrasound (HIFU) combined with nanoparticle therapeutics: HIFU is applied to improve drug delivery and to trigger drug release from nanoparticles. Gas-bubbles are playing the role of the drug’s nano-carrier. These are used both to increase the drug transport into the cell and as ultrasound-imaging contrast material. The ultrasound is also used for processes of drug-release and ablation.


Additional example; Multifunctional nanoparticles for tracking CED (convection enhanced delivery)  distribution within tumors: Nanoparticle that could serve as a carrier not only for the therapeutic radionuclides but simultaneously also for a therapeutic drug and 4 different types of imaging contrast agents including an MRI contrast agent, PET and SPECT nuclear diagnostic imaging agents and optical contrast agents as shown below. The ability to perform multiple types of imaging on the same nanoparticles will allow studies investigating the distribution and retention of nanoparticles initially in vivo using non-invasive imaging and later at the histological level using optical imaging.



Image-guided radiotherapeutic nanoparticles have significant potential for solid tumor cancer therapy. The current success of this therapy in animals is most likely due to the improved accumulation, retention and dispersion of nanoparticles within solid tumor following image-guided therapies as well as the micro-field of the β-particle which reduces the requirement of perfectly homogeneous tumor coverage. It is also possible that the intratumoral distribution of nanoparticles may benefit from their uptake by intratumoral macrophages although more research is required to determine the importance of this aspect of intratumoral radionuclide nanoparticle therapy. This new approach to cancer therapy is a fertile ground for many new technological developments as well as for new understandings in the basic biology of cancer therapy. The clinical success of this approach will depend on progress in many areas of interdisciplinary research including imaging technology, nanoparticle technology, computer and robot assisted image-guided application of therapies, radiation physics and oncology. Close collaboration of a wide variety of scientists and physicians including chemists, nanotechnologists, drug delivery experts, radiation physicists, robotics and software experts, toxicologists, surgeons, imaging physicians, and oncologists will best facilitate the implementation of this novel approach to the treatment of cancer in the clinical environment. Image-guided nanoparticle therapies including those with β-emission radionuclide nanoparticles have excellent promise to significantly impact clinical cancer therapy and advance the field of drug delivery.

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 What is the key method to harness Inflammation to close the doors for many complex diseases?


Author and Curator: Larry H Bernstein, MD, FCAP


The main goal is to  have a quality of a healthy life.

When we look at the picture 90% of main fluid of life, blood, carried by cardiovascular system with two main pumping mechanisms, lung with gas exchange and systemic with complex scavenger actions, collection of waste, distribution of nutrition and clean gases etc.  Yet without lymphatic system body can’t make up the 100% fluid.  Therefore, 10% balance is completed by lymphatic system as a counter clockwise direction so that not only the fluid balance but also mass balance is  maintained. Finally, the immune system patches the  remaining mechanism by providing cellular support to protect the body because it contains 99% of white cells to fight against any kinds of invasion, attack, trauma.

These three musketeers, ccardiovascular, lyphatic and immune systems, create the core mechanism of survival during human life.

However, there is a cellular balance between immune and cardiovascular system since blood that made up off 99% red cells and 1% white blood cells that are used to scavenger hunt circulating foreign materials.   These three systems are acting with a harmony not only defend the body but provide basic needs of life.  Thus, controlling angiogenesis and working mechanisms in blood not only helps to develop new diagnostic tools but more importantly establishes long lasting treatments that can harness Immunomodulation.

The word inflammation comes from the Latin “inflammo”, meaning “I set alight, I ignite”.

Medical Dictionary description is:

“A fundamental pathologic process consisting of a dynamic complex of histologically apparent cytologic changes, cellular infiltration, and mediator release that occurs in the affected blood vessels and adjacent tissues in response to an injury or abnormal stimulation caused by a physical, chemical, or biologic agent, including the local reactions and resulting morphologic changes; the destruction or removal of the injurious material; and the responses that lead to repair and healing.”

The five elements makes up the signature of  inflammation:  rubor, redness; calor, heat (or warmth); tumor swelling; and dolor, pain; a fifth sign, functio laesa, inhibited or lost function.   However, these indications may not be present at once.

Please click on to the following link for genetic association of autoimmune diseases (Cho Et al selected major association signals in autoimmune diseases) from Cho JH, Gregersen PK. N Engl J Med 2011;365:1612-1623.

Inflammatory diseases grouped under two classification: the immune system related due to  inflammatory disorders, such as both allergic reactions  and some myopathies, with many immune system disorders.  The examples of inflammatory disorders  include Acne vulgaris, asthma, autoimmune disorders, celiac disease, chronic prostatitis, glomerulonepritis, hypersensitivities, inflammatory bowel diseases, pelvic inflammatory diseases, reperfusion diseases, rheumatoid arthritis, sarcoidosis, transplant rejection, vasculitis, interstitial cyctitis, The second kind of inflammation are related to  non-immune diseases such as cancer, atherosclerosis, and ischaemic heart disease.

This seems simple yet at molecular physiology and gene activation levels this is a complex response as an innate immune response from body.  There can be acute lasting few days after exposure to bacterial pathogens, injured tissues or chronic inflammation continuing few months to years after unresolved acute responses such as non-degradable pathogens, viral infection, antigens or any  foreignmaterials, or autoimmune responses.

As the system responses arise from plasma fluid, blood vessels, blood plasma through vasciular changes, differentiation in plasma cascade systems like coagulation system, fibrinolysis, complement system and kinin system.  Some of the various mediators include bradykinin produced by kinin system, C3, C5, membrane attack system (endothelial cell activation or endothelial coagulation activation mechanism) created by the complement system; factor XII that can activate kinin, fibrinolysys and coagulation systems at the same time produced in liver; plasmin from fibrinolysis system to inactivate factor Xii and C3 formation, and thrombin of coagulation system with a reaction through protein activated receptor 1 (PAR1), which is a seven spanning membrane protein-GPCR.   This system is quite fragile and well regulated.  For example activation of inactive Factor XII by collagen, platelets, trauma such as cut, wound, surgery that results in basement membrane changes since it usually circulate in inactive form in plasma automatically initiates and alerts kinin, fibrinolysis and coagulation systems.

Furthermore, the changes reflected through receptors and create gene activation by cellular mediators to establish system wide unified mechanisms. These factors (such as IFN-gamma, IL-1, IL-8, prostaglandins, leukotrene B4,  nitric oxide, histamines,TNFa) target immune cells and redesign their responses, mast cells, macrophages, granulocytes, leukocytes, B cells, T cells) platelets, some neuron cells and endothelial cells.  Therefore, immune system can react with non-specific or specific mechanisms either for a short or a long term.

As a result, controlling of mechanisms in blood and prevention of angiogenesis answer to cure/treat many diseases  Description of angiogenesis is simply formation of new blood vessels without using or changing pre-existing capillaries.  This involves serial numbers of events play a central role during physiologic and pathologic processes such as normal tissue growth, such as in embryonic development, wound healing, and the menstrual cycle.  However this system requires three main elements:  oxygen, nutrients and getting rid of waste or end products.

Genome Wide Gene Association Studies, Genomics and Metabolomics, on the other hand, development of new technologies for diagnostics and non-invasive technologies provided better targeting systems.

In this token recent genomewide association studies showed a clear view on a disease mechanism, or that suggest a new diagnostic or therapeutic approach particularly these disorders are related to  genes within the major histocompatibility complex (MHC) that predisposes the most significant genetic effect.  Presumably, these genes are reflecting the immunoregulatory effects of the HLA molecules themselves. As a result, the working mechanism of pathological conditions are revisited or created new assumptions to develop new targets for diagnosis and treatments.

Even though B and T cells are reactive to initiate responses there are several level of mechanisms control the cell differentiation for designing rules during health or diseases. These regulators are in check for both T and B cells.  For example, during Type 1 diabetes there are presence of more limited defects in selection against reactivity with self-antigens like insulin, thus, T cell differentiation is in jeopardy.  In addition, B cells have many active checkpoints to modulate the immune responses like  pre-B cells in the bone marrow are highly autoreactive yet they prefer to stay  in naïve-B cell forms in the periphery through tyrosine phosphatase nonreceptor type 22 (PTPN22) along with many genes play a role in autoimmunity.  In a nut shell this is just peeling the first layer of the onion at the level of Mendelian Genetics.

There is a great work to be done but if one can harness the blood and immune responses many complex diseases patients may have a big relief and have a quality of life.  When we look at the picture 90% of main fluid of life, blood, carried by cardiovascular system with two main pumping mechanisms, lung with gas exchange and systemic with complex scavenger actions, collection of waste, distribution of nutrition and clean gases.  Yet, without lymphatic system body can’t make up the 100% fluid.  Therefore, 10% balance is completed by lymphatic system as a counter clockwise direction so that not only the fluid balance but also mass balance is  maintained. Finally, the immune system patches the  remaining mechanism by providing cellular support to protect the body because it contains 99% of white cells to fight against any kinds of invasion, attack, trauma.


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Reporter and Curator: Dr. Sudipta Saha, Ph.D.


The majority of living forms depend for their functioning upon two classes of biocatalysts, the enzymes and the hormones. These biocatalysts permit the diverse chemical reactions of the organism to proceed at 38°C with specificity and at rates frequently unattainable in vitro at elevated temperatures with similar reactants. The physiologic importance of enzymes and hormones is evident not only under normal circumstances, but is reflected clinically in the diverse descriptions of errors of metabolism, due to lack or deficiency of one or more enzymes, and the numerous hypo and hyper functioning states resulting from imbalance of hormonal supply.


In as much as both enzymes and hormones function, with rare exception, to accelerate the rates of processes in cells, investigators have sought possible interrelationships and interactions of enzymes and hormones, particularly as a basis for the mechanism of hormonal action. It has seemed logical to hypothesize that hormones, while not essential for reactions to proceed but never the less affecting the rates of reactions, may function by altering either the concentration or activity of the prime cellular catalysts, the enzymes. This proposed influence of hormones on enzymatic activity might be a primary, direct effect achieved by the hormone participating as an integral part of an enzyme system, or an indirect influence based upon the hormone altering the concentration of available enzyme and/or substrate utilized by a particular enzyme. Many publications have described alterations in the activity of enzymes in various tissues following administration in vivo of diverse hormonal preparations. However, it is not possible to judge, in the in vivo experiments, whether the reported effects are examples of direct enzyme-hormone interaction, or an indirect influence of the hormone mediated via one or more metabolic pathways, and therefore other enzyme systems whose activities are not being measured. Data from in-vivo studies of this type are thus not pertinent to a discussion of direct hormone-enzyme interaction.


Enzyme hormone interaction, as seen, for example, in the profound role of the enzymes of the liver in the metabolism of certain hormones, is of paramount importance in determining the effectiveness of these hormones. The ability of the organic chemist to prepare synthetic hormonal derivatives which are relatively resistant to enzymatic processes in the liver has been of outstanding value for approaches to oral hormonal therapy. Largely unexplored as yet is the possibility that enzyme-hormone interactions may lead to the production of physiologically more active substances from compounds normally synthesized and secreted by a particular endocrine gland. It may be said at the outset that in no instance has a hormone been demonstrated to influence the rate of a cellular reaction by functioning as a component of an enzyme system.


It is plausible that enzymes in a pathway might be structurally conserved because of their similar substrates and products for linked metabolic steps. However, this is not typically observed, and sequence analysis confirms the lack of convergent or divergent evolution. One might postulate that, if the folds or overall structures of the enzymes in a pathway are not conserved, then perhaps at least pathway-related active site similarities would exist. It is true that metal-binding sites and nucleotide-binding sites are structurally conserved. For example, cofactor-binding motifs for zinc, ATP, biopterin and NAD have been observed and biochemically similar reactions appear to maintain more structural similarity than pathway-related structural motifs. In general, ‘horizontal’ structural equivalency is prevalent in that chemistry-related structural similarities exist, but ‘vertical’ pathway-related structural similarities do not hold.


For metabolic pathways, protein fold comparisons and corresponding active site comparisons are sometimes possible if structural and functional homology exists. Unfortunately, with the current structural information available, the majority of active sites that can be structurally characterized are not similar within a metabolic pathway. Other examples exist of nearly completed pathways, for example, the tricarboxylic acid (TCA) cycle, and similar observations are observed. Situations in which different metals are incorporated in enzyme active sites lead to inherently different catalytic portions of the active sites. Slight differences in the ligand-binding portions of the respective active sites must lead to the observed differences in pathway-related enzyme specificities. These modifications in enzymatic activity are similar to what Koshland and co-workers previously observed. They showed that very minor active site perturbations to isocitrate dehydrogenase had drastic effects on catalysis.


Molecular level understanding of chemical and biological processes requires mechanistic details and active site information. The current knowledge regarding enzyme active sites is incomplete. Even in situations in which ATP-, ADP- or NAD(P)+-binding domains are observed or in situations in which similar folds are found (e.g. even for related kinases or for proteins involved in the immune system), structural comparisons do not yield specific details about active sites and it is not possible to predict where the substrate binds or to identify determinants of active site substrate specificity. Therefore, in this era of structural genomics, there should be major continued emphasis on completing structural information for important metabolic pathways. This will require improved efforts to obtain structures for enzyme complexes with appropriate cofactors, substrates or substrate analogs, as well as with inhibitors and regulators of activity. Then and only then will we have complete structural knowledge and facilitated structure-based drug design efforts. Structural genomics efforts promise to provide structural data in a high-throughput mode. However, we need to ensure that much of this focus is placed on completing the picture of metabolic pathways and enzyme active sites.


The availability of the human genomic sequence is changing the way in which biological questions are addressed. Based on the prediction of genes from nucleotide sequences, homologies among their encoded amino acids can be analyzed and used to place them in distinct families. This serves as a first step in building hypotheses for testing the structural and functional properties of previously uncharacterized paralogous genes. As genomic information from more organisms becomes available, these hypotheses can be refined through comparative genomics and phylogenetic studies. Instead of the traditional single-gene approach in endocrine research, we are beginning to gain an understanding of entire mammalian genomes, thus providing the basis to reveal subfamilies and pathways for genes involved in ligand signaling. The present review provides selective examples of postgenomic approaches in the analysis of novel genes involved in hormonal signaling and their chromosomal locations, polymorphisms, splicing variants, differential expression, and physiological function. In the postgenomic era, scientists will be able to move from a gene-by-gene approach to a reconstructionistic one by reading the encyclopedia of life from a global perspective. Eventually, a community-based approach will yield new insights into the complexity of intercellular communications, thereby offering us an understanding of hormonal physiology and pathophysiology. Many cellular signaling pathways ultimately control specific patterns of gene expression in the nucleus through a variety of signal-regulated transcription factors, including nuclear hormone receptors. The advent of genomic technologies for examining signal-regulated transcriptional responses and transcription factor binding on a genomic scale has dramatically increased our understanding of the cellular programs that control hormonal signaling and gene regulation. Studies of transcription factors, especially nuclear hormone receptors, using genomic approaches have revealed novel and unexpected features of hormone-regulated transcription, and a global view is beginning to emerge.


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