Friday, March 15, 2013

CPRIT: At its February 25, 2013 meeting, the CPRIT Oversight Committee approved proposed changes to existing agency rules and the addition of three new rules

so you know:

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At its February 25, 2013 meeting, the CPRIT Oversight Committee approved proposed changes to existing agency rules and the addition of three new rules. The changes proposed are designed to implement many of the State Auditor’s recommendations concerning ethics, conflicts of interest, grant review and documentation of the agency’s grant processes.

The proposed rule changes and new rules appear in the March 15, 2013 edition of the Texas Register. Public comment is accepted for 30 days following publication and is due no later than 5:00 pm on April 15, 2013. At its meeting in late April, the Oversight Committee expects to consider final rules reflecting the comments received.

Individuals or organizations interested in providing input on the rule changes and new rules may do so by sending written comments to Ms. Kristen Pauling Doyle, General Counsel, Cancer Prevention and Research Institute of Texas, P. O. Box 12097, Austin, Texas 78711. Comments may also be submitted electronically to kdoyle@cprit.state.tx.us or by facsimile transmission to 512/475-2563. Comments must be received no later than 5:00 pm on April 15, 2013.

Maternal caffeine intake during pregnancy is associated with birth weight but not with gestational length: results from a large prospective observational cohort study

This has been an intriguing question for a long time. Here the Institute of Public Health of Norway looked at 59,123 women and found that ... but read on:

Verena Sengpiel, Elisabeth Elind, Jonas Bacelis, Staffan Nilsson, Jakob Grove, Ronny Myhre, Margaretha Haugen, Helle M Meltzer, Jan Alexander, Bo Jacobsson and Anne-Lise Brantsaeter

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BMC Medicine 2013, 11:42 doi:10.1186/1741-7015-11-42
Published: 19 February 2013

Abstract (provisional)

Background

Pregnant women consume caffeine daily. The aim of this study was to examine the association between maternal caffeine intake from different sources and (a) gestational length, particularly the risk for spontaneous preterm delivery (PTD), and (b) birth weight (BW) and the baby being small for gestational age (SGA).

Methods

This study is based on the Norwegian Mother and Child Cohort Study conducted by the Norwegian Institute of Public Health. A total of 59,123 women with uncomplicated pregnancies giving birth to a live singleton were identified. Caffeine intake from different sources was self-reported at gestational weeks 17, 22 and 30. Spontaneous PTD was defined as spontaneous onset of delivery between 22+0 and 36+6 weeks (n = 1,451). As there is no consensus, SGA was defined according to ultrasound-based (Marsal, n = 856), population-based (Skjaerven, n = 4,503) and customized (Gardosi, n = 4,733) growth curves.

Results

The main caffeine source was coffee, but tea and chocolate were the main sources in women with low caffeine intake. Median pre-pregnancy caffeine intake was 126 mg/day (IQR 40 to 254), 44 mg/day (13 to 104) at gestational week 17 and 62 mg/day (21 to 130) at gestational week 30. Coffee caffeine, but not caffeine from other sources, was associated with prolonged gestation (8 h/100 mg/day, P <10-7). Neither total nor coffee caffeine was associated with spontaneous PTD risk. Caffeine intake from different sources, measured repeatedly during pregnancy, was associated with lower BW (Marsal -28 g, Skjaerven -25 g, Gardosi -21 g per 100 mg/day additional total caffeine for a baby with expected BW 3,600 g, P <10-25). Caffeine intake of 200 to 300 mg/day increased the odds for SGA (OR Marsal 1.62, Skjaerven 1.44, Gardosi 1.27, P <0.05), compared to 0 to 50 mg/day.

Conclusions

Coffee, but not caffeine, consumption was associated with marginally increased gestational length but not with spontaneous PTD risk. Caffeine intake was consistently associated with decreased BW and increased odds of SGA. The association was strengthened by concordant results for caffeine sources, time of survey and different SGA definitions. This might have clinical implications as even caffeine consumption below the recommended maximum (200 mg/day in the Nordic countries and USA, 300 mg/day according to the World Health Organization (WHO)) was associated with increased risk for SGA.

The complete article is available as a provisional PDF. The fully formatted PDF and HTML versions are in production.

Crossing the Omic Chasm. A Time for Omic Ancillary Systems

Free ViewPoint

Justin Starren, MD, PhD; Marc S. Williams, MD; Erwin P. Bottinger, MD

[+] Author Affiliations

JAMA. 2013;():1-2. doi:10.1001/jama.2013.1579.

Text Size: A A A

Published online March 14, 2013

Article

Figures

References

Figures in this Article

Despite the information gains from genome-wide association studies and next-generation sequencing (NGS), there remains a chasm between this scientific knowledge and daily clinical practice. Leveraging recent advances in genomics to improve patient care will require electronic health record (EHR) systems that incorporate genomic clinical decision support (CDS). The eMerge (Electronic Medical Records and Genomics)¹^- 2 consortium is bridging this chasm by developing interoperable systems that can integrate large-scale genomic data with clinical workflows. According to a recent Institute of Medicine report,³ the current document-centric approach to omic (eg, genomic, epigenomic, proteomic, metabolomic) data will not scale, making storage of raw omic data in current-generation EHRs not feasible. Although commercial EHRs may eventually evolve to handle omic data efficiently, dedicated omic ancillary systems will be essential in the interim.

Historically, “EHR” has been taken to refer to the system used in day-to-day patient care, whereas systems that collect and manage specialized data, such as laboratory, pharmacy, and imaging, have been considered “ancillary” systems. Before discussing how an omic ancillary system would function, it is useful to consider how omic data differ from conventional health data. The simplest difference is the amount of data. Current EHRs are optimized to manage large numbers of discrete and actionable items to facilitate clinical care. They are not designed to store large blocks of data that do not require rapid access. When diagnostic tests create large data sets, ancillary systems are developed to manage the data, and only a subset of clinically relevant information is transferred to the EHR. The archetypal example is imaging. Radiologic images are stored in a picture archiving and communication system (PACS). Radiologists interpret the images to generate a report, and only the text report is stored in the EHR database. An EHR may interface with a PACS to display images, but it does not store them. This dichotomy is evident by comparing the amount of data stored in the EHR vs that stored in ancillary systems. For example, at Northwestern University, the EHR averages 375 kB per patient, whereas the PACS averages 104 MB per patient (a 277-fold difference). Typical NGS identifies 3 to 10 million variants per individual,⁴ requiring 5 to 10 GB of storage (50-fold greater than imaging). Compression may reduce the absolute storage requirement but will not reduce the number of variants to be considered.

One maxim taught to medical students is never to order any test unless the results of the test may affect a treatment decision. The implication of this maxim is that clinicians know how they will interpret each piece of information before that information is collected. Most clinical laboratory tests measure variable parameters (eg, serum sodium level) compared with set reference values, allowing interpretation using the relevant clinical context. It is unlikely that current understanding of sodium metabolism will change so radically that reinterpretation of historical sodium values is necessary.

Omic data are different. An individual's germline genetic sequence changes little over a lifetime, but understanding of that sequence is changing rapidly. For years the DNA between coding regions was called “junk,” but it is now known that this DNA plays an important role in gene regulation.⁵^- 6 The 1000 Genomes project has identified tens of millions of different genomic variants; the clinical significance of these variants is mostly unknown, but current understanding is rapidly changing. Unlike serum sodium levels, the clinical implications of NGS obtained today will keep changing for years as knowledge evolves. This necessitates systems that dynamically reanalyze and reinterpret stored static genomic results in the context of evolving knowledge.

The Figure shows the possible data paths that omic data may take from collection to use. Today, most genomic results are delivered as textual reports (route A). Small panels of genes can be reported as conventional laboratory results (route B).⁷ Although some results will likely continue to be stored this way, NGS will overwhelm both routes. Conventional human-centric approaches to genomic results do not support reinterpretation as new knowledge emerges and will be gradually replaced by computer-centric approaches.

Figure. Integration of Genomic Data With Electronic Health Records

Integration depends on the format and complexity of the data. Note that data paths convey high-level data flows and do not necessarily imply point-to-point connections. CLIA indicates Clinical Laboratory Improvement Amendments.

View Large | Save Figure | Download Slide (.ppt)

Increasingly, NGS and other high-dimensionality omic testing will become routine, creating large, complex data sets and setting the stage for “omic” ancillary systems. This approach adds value by providing a location to store variants of unknown significance until enough knowledge emerges to move these variants into clinical practice. Three paths could facilitate transfer of actionable genomic information to the EHR: (1) results of the genomic analysis could be manually reviewed, converted to a textual report, and presented to the clinician (route C); (2) “computable observations” could be created and stored within the EHR, where the observations can be used to trigger conventional CDS rules (route D); or (3) an external CDS system could be incorporated that is queried by the EHR at appropriate points in the clinical workflow (route E). Although that CDS system is shown as part of the omic ancillary system, it is also possible that the CDS system could be external to the organization.

Large organizations will likely operate their own omics ancillary systems, in the same way that they maintain other ancillaries. For smaller practices, reference laboratories may add omic ancillary services to their existing services. The number of clinically significant variants is currently limited, but the availability of affordable NGS will greatly accelerate this flow. Omic ancillary systems are one way to bridge the omic chasm without waiting for an entirely new generation of EHRs to emerge.

AUTHOR INFORMATION

Corresponding Author: Justin Starren, MD, PhD, Division of Health and Biomedical Informatics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 750 N Lake Shore Dr, 11th Floor, Chicago, IL 60611 (justin.starren@northwestern.edu).

Published Online: March 14, 2013. doi:10.1001/jama.2013.1579

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Bottinger reported that he is named on a previous patent application for personalized clinical decision support.

Funding/Support:The eMERGE Network was initiated and funded by National Human Genome Research Institute through the following grants: U01HG006828 (Cincinnati Children's Hospital Medical Center/Harvard); U01HG006830 (Children's Hospital of Philadelphia); U01HG006389 (Essentia Institute of Rural Health); U01HG006382 (Geisinger Clinic); U01HG006375 (Group Health Cooperative); U01HG006379 (Mayo Clinic); U01HG006380 (Mount Sinai School of Medicine); U01HG006388 (Northwestern University); U01HG006378 (Vanderbilt University); and U01HG006385 (Vanderbilt University serving as the Coordinating Center).

Role of the Sponsors: The funders had no role in the preparation, review, or approval of the manuscript.

Additional Contributions: We thank all the members of the eMERGE EHR Integration workgroup for input on this article.

REFERENCES

McCarty CA, Chisholm RL, Chute CG, et al; eMERGE Team. The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies. BMC Med Genomics. 2011;413
PubMed | Link to Article

Kho AN, Pacheco JA, Peissig PL, et al. Electronic medical records for genetic research: results of the eMERGE consortium. Sci Transl Med. 2011;3(79):re1
PubMed | Link to Article

Institute of Medicine Roundtable on Translating Genomic-Based Research for Health. Integrating Large-Scale Genomic Information Into Clinical Practice: Workshop Summary. Washington, DC: National Academies Press; 2012

Pelak K, Shianna KV, Ge D, et al. The characterization of twenty sequenced human genomes. PLoS Genet. 2010;6(9):e1001111
PubMed | Link to Article

Dunham I, Kundaje A, Aldred SF, et al; ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489(7414):57-74
PubMed | Link to Article

Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61-70
PubMed | Link to Article

Health Level 7 International (HL7) Clinical Genomics Committee. Clinical Genomics. HL7 website. http://www.hl7.org/Special/committees/clingenomics/index.cfm. Accessed October 31, 2012

News from the CPRIT

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Wednesday, March 13, 2013

Jakafi

Superior reductions in spleen volume and improvements in Total Symptom Score (TSS) vs placebo.^1,2 Learn more at www.jakafi.com.

Regulate JAK signaling. Reduce splenomegaly and symptoms of myelofibrosis.

Jakafi^®—the first and only FDA-approved agent for intermediate or high-risk myelofibrosis^1,3

Dear Dr Kankonde,

Consider Jakafi for your patients with intermediate or high-risk myelofibrosis. Jakafi reduces splenomegaly and improves the symptoms of myelofibrosis, as measured by TSS.* Symptoms measured by TSS were abdominal discomfort, early satiety, pain under left ribs, pruritus, night sweats and bone/muscle pain. In a clinical study, most patients receiving placebo experienced increased splenomegaly and worsening of symptoms.^1,2

Jakafi regulates JAK1 and JAK2 signaling^1,2

•	Dysregulated Janus kinase (JAK) signaling is a key feature of myelofibrosis⁴
•	Splenomegaly and debilitating symptoms of myelofibrosis have been linked to dysregulated JAK signaling⁵
•	Dysregulated JAK signaling may occur via many mechanisms, including^3,6-13

—	JAK2 mutations
—	Receptor mutations (eg, MPL mutations)
—	Increased JAK1 signaling
—	Excess cytokines
—	Damaged intracellular signaling mechanisms (eg, those involving SOCS)

View the Jakafi Mechanism of Action (MOA) video >

MPL=myeloproliferative leukemia virus oncogene; SOCS=suppressor of cytokine signaling.

•	Treatment with Jakafi can cause hematologic adverse reactions, including thrombocytopenia, anemia and neutropenia, which are each dose-related effects, with the most frequent being thrombocytopenia and anemia
•	Patients should be assessed for the risk of developing serious bacterial, mycobacterial, fungal and viral infections
•	The three most frequent non-hematologic adverse reactions were bruising, dizziness and headache

Jakafi demonstrated superior reductions in spleen volume and significant improvements in symptom scores^1,14,15

41.9% vs 0.7%^1,2†
Patients achieving a >35% reduction in spleen volume at 24 weeks vs placebo (COMFORT-I)
(P < 0.0001)

28.5% vs 0%^1,2‡
Patients achieving a >35% reduction in spleen volume at 48 weeks vs best available therapy (BAT) (COMFORT-II)
(P < 0.0001)

45.9% vs 5.3%^1,2†
Patients achieving a >50% improvement in TSS at 24 weeks vs placebo (COMFORT-I) (P < 0.0001)

Reductions in spleen volume and improvements in TSS were seen with Jakafi in both JAK2V617F-positive and JAK2V617F-negative patients, relative to placebo.²

COMFORT-I: Percent Change in Spleen Volume in Individual Patients From Baseline to Week 24 or Last Observation

Each bar represents an individual patient's response.

COMFORT-I: Percent Change in TSS in Individual Patients From Baseline to Week 24 or Last Observation

Each bar represents an individual patient's response. Worsening of TSS is truncated at 150%.

Please see Important Safety Information.

Learn more about how Jakafi can help your patients >

*	TSS was captured by the modified Myelofibrosis Symptom Assessment Form (MFSAF v2.0), a daily patient diary recorded for 25 weeks. Symptom scores ranged from 0 to 10 with 0 representing symptoms "absent" and 10 representing "worst imaginable" symptoms. These scores were added to create the daily total score, which has a maximum of 60. At baseline, mean TSS was 18.0 in the group receiving Jakafi and 16.5 in the placebo group.^1,2
^†	Based on COMFORT-I, a randomized, double-blind, placebo-controlled study in patients with myelofibrosis who were refractory to or not candidates for available therapy.^1,14
^‡	Based on COMFORT-II, an open-label, randomized study of Jakafi vs BAT.^1,15

IncyteCARES (Connecting to Access, Reimbursement, Education and Support)

IncyteCARES offers free educational support for your patients taking Jakafi.

Order the IncyteCARES Patient Starter Packet >

Learn about
Jakafi

View the Jakafi MOA video and learn about how Jakafi works.

Order the IncyteCARES Patient Starter Packet

Give your patients this resource, which provides information about Jakafi treatment and patient support services.

Indications and Usage

Jakafi is indicated for treatment of patients with intermediate or high-risk myelofibrosis, including primary myelofibrosis, post–polycythemia vera myelofibrosis and post–essential thrombocythemia myelofibrosis.

Important Safety Information

•	Treatment with Jakafi can cause hematologic adverse reactions, including thrombocytopenia, anemia and neutropenia, which are each dose-related effects, with the most frequent being thrombocytopenia and anemia. A complete blood count must be performed before initiating therapy with Jakafi. Complete blood counts should be monitored as clinically indicated and dosing adjusted as required
•	The three most frequent non-hematologic adverse reactions were bruising, dizziness and headache
•	Patients with platelet counts <200 x 10⁹/L at the start of therapy are more likely to develop thrombocytopenia during treatment. Thrombocytopenia was generally reversible and was usually managed by reducing the dose or temporarily withholding Jakafi. If clinically indicated, platelet transfusions may be administered
•	Patients developing anemia may require blood transfusions. Dose modifications of Jakafi for patients developing anemia may also be considered
•	Neutropenia (ANC <0.5 x 10⁹/L) was generally reversible and was managed by temporarily withholding Jakafi
•	Patients should be assessed for the risk of developing serious bacterial, mycobacterial, fungal and viral infections. Active serious infections should have resolved before starting Jakafi. Physicians should carefully observe patients receiving Jakafi for signs and symptoms of infection (including herpes zoster) and initiate appropriate treatment promptly
•	A dose modification is recommended when administering Jakafi with strong CYP3A4 inhibitors or in patients with renal or hepatic impairment [see Dosage and Administration]. Patients should be closely monitored and the dose titrated based on safety and efficacy
•	There are no adequate and well-controlled studies of Jakafi in pregnant women. Use of Jakafi during pregnancy is not recommended and should only be used if the potential benefit justifies the potential risk to the fetus
•	Women taking Jakafi should not breast-feed. Discontinue nursing or discontinue the drug, taking into account the importance of the drug to the mother

Please see Full Prescribing Information.

References: 1. Jakafi Prescribing Information. Incyte Corporation. November 2011. 2. Data on file. Incyte Corporation. 3. Quintás-Cardama A, Vaddi K, Liu P, et al. Preclinical characterization of the selective JAK1/2 inhibitor INCB018424: therapeutic implications for the treatment of myeloproliferative neoplasms. Blood. 2010;115:3109-3117. 4. Anand S, Stedham F, Gudgin E, et al. Increased basal intracellular signaling patterns do not correlate with JAK2 genotype in human myeloproliferative neoplasms. Blood. 2011;118:1610-1621. 5. Verstovsek S, Kantarjian H, Mesa RA, et al. Safety and efficacy of INCB018424, a JAK1 and JAK2 inhibitor, in myelofibrosis. N Engl J Med. 2010;363:1117-1127. 6. Kralovics R, Passamonti F, Buser AS, et al. A gain-of-function mutation of JAK2 in myeloproliferative disorders. N Engl J Med. 2005;352:1779-1790. 7. Levine RL, Pardanani A, Tefferi A, Gilliland DG. Role of JAK2 in the pathogenesis and therapy of myeloproliferative disorders. Nat Rev Cancer. 2007;7:673-683. 8. Scott LM, Tong W, Levine RL, et al. JAK2 exon 12 mutations in polycythemia vera and idiopathic erythrocytosis. N Engl J Med. 2007;356:459-468. 9. Pikman Y, Lee BH, Mercher T, et al. MPLW515L is a novel somatic activating mutation in myelofibrosis with myeloid metaplasia. PLoS Med. 2006;3:1140-1151. 10. Kralovics R. Genetic complexity of myeloproliferative neoplasms. Leukemia. 2008;22:1841-1848. 11. Tefferi A, Vaidya R, Caramazza D, Finke C, Lasho T, Pardanani A. Circulating interleukin (IL)-8, IL-2R, IL-12, and IL-15 levels are independently prognostic in primary myelofibrosis: a comprehensive cytokine profiling study. J Clin Oncol. 2011;29:1356-1363. 12. Verstovsek S. Therapeutic potential of JAK2 inhibitors. Hematology Am Soc Hematol Educ Program. 2009:636-642. 13. Fourouclas N, Li J, Gilby DC, et al. Methylation of the suppressor of cytokine signaling 3 gene (SOCS3) in myeloproliferative disorders. Haematologica. 2008;93:1635-1644. 14. Verstovsek S, Mesa RA, Gotlib J, et al. A double-blind, placebo-controlled trial of ruxolitinib for myelofibrosis. N Engl J Med. 2012;366:799-807. 15. Harrison C, Kiladjian J-J, Al-Ali HK, et al. JAK inhibition with ruxolitinib versus best available therapy for myelofibrosis. N Engl J Med. 2012;366:787-798.

CTC Survey Results Released

Inbox
x

Andrew Kerry

3:08 AM (3 hours ago)

to me

Dear MUTOMBO,

We recently ran a survey on Circulating Tumour Cells which questioned stakeholders
across drug development, academia, cancer hospitals and the technology sector on the
challenges that they are facing in utilising CTCs in their research.

I think you’ll find the results interesting:

74.3% of respondents in the survey highlighted CTCs as either a "very high" or
"high priority" for their organisation
When questioned what was the biggest challenges faced in this field the top
challenge was identified as “Current technology is neither sensitive or specific
enough” (33%) with the second biggest challenge being that “There is no agreed
golden standard for technology” (25.5%)
A resounding 48.8% thought that to validate CTCs in the clinic there needs to be
“more clinical trials validating CTCs as a diagnostic/prognostic prospective”

These are just some of the revealing answers the survey uncovered. You can download
the full survey results from the World CTC Berlin Library.

In addition to these exciting results I’d also like to take the opportunity to announce the
latest speaker for World CTC Berlin:

Sarah Thayer, Associate Professor, Surgery, W. Gerald Austen Scholar in Academic
Surgery & Director, Pancreatic Biology Laboratory, Mass Gen Hospital

Presentation Title: The Capture, Growth and Genetic Analysis of CTC in PDAC: What
Can it Tell Us About this Disease?

Detection of CTC in patients with resectable PDAC using a Screencells Device
Methods used to achieve in vitro growth and confirmation of tumorigenicity
How selective deep sequencing was used to demonstrate the feasibility of
identifying mutations present in the primary tumour and their corresponding CTC

Download the meeting brochure to see the full array of CTC experts on the programme.

Kind regards

Andrew

Andrew Kerry

Hanson Wade

www.worldctc-berlin.com

Today more field research work in Indianapolis where I discover Carmel reportedly the best place to live in America. 'The number 1 best place to live" and I am there. This is not my impression we are talking about, this is from money magazine as of Sept 2012. Carmel IN was followed at a distance by McKinney,TX (will go there to visit when I am back in Texas. 3rd place Eden Prairie MN, 4. Newton MA, 5th. Redmond WA
6th Irvine CA.
VISIT THESE QUAINT PLACES TO DISCOVER THE CHARM OF AMERICAN CITIES, AND WRITE TO ME ABOUT. I REALLY AGREE THIS PLACE IS CHARMING! JUST WISH I HAD MORE TIME AND MONEY TO ENJOY IT FULLY!

Tuesday, March 12, 2013

Dr. Robert A. Kirken who has been appointed as the new dean of the UTEP College of Science

UTEP - The University of Texas at El Paso

Congratulations to Dr. Robert A. Kirken who has been appointed as the new dean of the UTEP College of Science. Read more about his announcement here: http://utepn.ws/WkKMol

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Monday, March 11, 2013

ADVANCES IN METASTATIC RENAL CANCER

*IL-2 (High dose) Response rate < 10% but with rare cures
* Medication approved
1. Sunitinib which was compred to Interferon to win approval
2. Avastin in combination to Interferon (not alone) was compared to interferon alone to win approval
3.Pazopanib was compared to placebo to win approval
4.Temsirolimus was compared to Interferon to win approval.
someone thought combining Interferon and Tensirolimus will give a higher response rate, well it did not. But this bring back the notion that until the MTOR is really amplified, rushing into its inhibition may not bring result. So timing suggested after failure of VEGF is critical.

5. Pazopanib was compared to Sunitinib, non inferiority proven although Pazopanib had PFS of 8.4 against a 9.5 months accomplished Sutent. The statical referee came in not statistical difference depite the hair color change of Pazopanib recipient! The hematologic toxicitywere worse with Sutent!

6.New kids on the block (Tivozanib and anti-PD1)
-Tivozanib was compared to Nexavar and came up on top in terms of PFS. OS not measure because of cross-over

ONE HAS VENTURED TO SUGGEST THAT
START WITH SUTENT
THAN AFINITOR
FOLLOWED BY AXITINIB
THAN ANTI-PD1
----------------------------------------

BUT REMEMBER THAT HISTOLOGY MAY FORCE YOU TO SKIP SUNITINIB
AND INTERFERON-BEVACIZUMAB ARE ALSO SOLID OPTIONS, AND SO REMAINS HIGH DOSE IL-2.

7-AXITINIB (AN ANTI-VEGF(s) ) WAS ALSO MATCHED WITH SORAFENIB IN THE HUTSON ET AL STUDY.AND CAME UP ON TOP FOR PFS. HOWEVER THE OBSERVERS ARE SAYING THAT IN THE LATEST PHASE III STUDY AXITINIB,ALTHOUGH ACTIVE, DID NOT MEET ITS PRIMARY END POINT.

8.EVEROLIMUS AGAINST PLACEBO WON BIG PFS, BUT NO OS!?

AVASTIN and Blood Vessels

1. Avastin normalizes blood vessel and therefore improves drug delivery
2.Combination with anti-EGFR, shortens PFS
3. Changes endothelium
4. Refractoriness soon develops
5.no cures
6.lack of biomarkers to optimally evaluate,monitor efficacy, and therefore dose optimally
7.Increasing Fibroblast growth factor as a way of dealing with lack of VEGF receptors
?dummy receptor to hijack extracellular - transcription factors increase

INHIBITION OF MTOR

from R T Kurmasheva, et al

"Thus, inhibition of mTOR may have direct effects on cancer cell proliferation and survival, indirect effects via inhibition of HIF-1α, thus reducing tumour-elicited VEGF, direct effects on vascular endothelial cells, or vascular smooth muscle cells (Humar et al, 2002; Majumder et al, 2004). For example, induction of HIF-1α and VEGF by the CML-associated oncogene, BCR-ABL, is mTOR-dependent (Mayerhofer et al, 2002), and in vitro, rapamycin inhibited VEGF production in primary cultures from BCR-ABL transformed, imatinib resistant, CML (Mayerhofer et al, 2005). The role for mTOR in VEGF production is supported by regulation of HIF-1α by mTOR signalling and increased VEGF in cells deficient in the TSC that negatively regulates mTOR via Rheb (Hudson et al, 2002). However, other studies support a role mainly for PI3K and to a lesser extent mTOR being required for insulin-induced HIF-1α expression (Treins et al, 2002). Our studies indicate that rapamycin treatment has little effect on hypoxia-driven VEGF production in most rhabdomyosarcoma or neuroblastoma cell lines (Kurmasheva et al, submitted). Thus, in these cells it is unlikely that rapamycin would block tumour-derived VEGF, although it may directly block the response of vascular endothelial or other stromal cells in tumour tissue. Potentially, in vivo resistance to mTOR inhibition could be elicited by secretion of angiogenic factors that signal to stromal cells via mTOR-independent pathways to increase proliferation or motility of vascular cells."
------------------------------------------------------------------------------

Yesterday we saw that Anti-VEGF drug induced alteration of vascular endothelium that could eventually bring Hypoxia into the cell, today we add evidence that the Hypoxia may induce HIF expression bringing MTOR overexpression into the battle leading to cancer cellular survival. THIS INDICATES THAT WHILE CONTINUING AVASTIN, INTRODUCING MTOR INHIBITOR AT THIS POINT MAY BRING A NEW STRATEGY TO REVERSE AVASTIN RESISTANCE, MEANING WHEN PLACENTAL GROWTH FACTOR OVER EXPRESSION IS HIGH (A MARKER OF AVASTIN FAILURE) , IT WOULD BE AN APPROPRIATE TIME TO BRING IN THE MTOR WITHOUT STOPPING AVASTIN. REMEMBER STOPPING AVASTIN HAS DEVASTATING REBOUND OF CANCER. AVASTIN HERE SERVES AS A PRIME FOR MTOR!

Coalition for the Reversal of Breast Cancer Mortality in African American Women

Friday, March 15, 2013

CPRIT: At its February 25, 2013 meeting, the CPRIT Oversight Committee approved proposed changes to existing agency rules and the addition of three new rules

Maternal caffeine intake during pregnancy is associated with birth weight but not with gestational length: results from a large prospective observational cohort study