Final Progress Report for Research Projects Funded by Health

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Final Progress Report for Research Projects Funded by
Health Research Grants
Instructions: Please complete all of the items as instructed. Do not delete instructions. Do not
leave any items blank; responses must be provided for all items. If your response to an item is
“None”, please specify “None” as your response. “Not applicable” is not an acceptable response
for any of the items. There is no limit to the length of your response to any question. Responses
should be single-spaced, no smaller than 12-point type. The report must be completed using
MS Word. Submitted reports must be Word documents; they should not be converted to pdf
format. Questions? Contact Health Research Program staff at 717-783-2548.

1. Grantee Institution: American College of Radiology

2. Reporting Period (start and end date of grant award period): 1/01/2005 – 12/31/2008

3. Grant Contact Person (First Name, M.I., Last Name, Degrees): Mark J. Dorfman, MBA,
CPA, CFP

4. Grant Contact Person’s Telephone Number: (215) 574-3156

5. Grant ME Number or SAP Number: SAP# 4100026182

6. Project Number and Title of Research Project: 1 - Conducting Biomarker, Genomics,
and Proteomics Correlative Research in the Radiation Therapy Oncology Group

7. Start and End Date of Research Project: 1/01/2005 – 12/31/2008

8. Name of Principal Investigator for the Research Project: Walter J. Curran, Jr., MD

9. Research Project Expenses.

9(A) Please provide the amount of health research grant funds spent on this project for the
entire duration of the grant, including any interest earned that was spent:

$ 789,724.94

9(B) Provide the last names (include first initial if multiple individuals with the same last
name are listed) of all persons who worked on this research project and were supported with
health research funds. Include position titles (Principal Investigator, Graduate Assistant,
Post-doctoral Fellow, etc.), percent of effort on project and total health research funds
expended for the position. For multiple year projects, if percent of effort varied from year to
year, report in the % of Effort column the effort by year 1, 2, 3, etc. of the project (x% Yr 1;
z% Yr 2-3).
Last Name Position Title % of Effort on Project Cost
Bae PhD Biostatistician 34% Yr1; 72% Yr 2; 51% $ 303,922.95
Yr3; 71% Yr 4
Ho MS Biostatistician 2.85% Yr 1; 18.5% Yr 2; $ 32,676.40
9% Yr 3
Swann PhD Biostatistician <1% Yr 1; 4% Yr 2 $ 8,054.54
Harris MS Biostatistician 5% Yr 3; 13% Yr 4 $ 19,878.67
Pajak PhD Biostatistician 6% yr 3; 13% Yr 4 $ 31,435.46
Sadek Sr. Director Stat. 3% Yr 3 $ 6,804.42
Moughan MS Biostatistician 5% yr 3; 11% Yr 4 $ 17,142.70

9(C) Provide the names of all persons who worked on this research project, but who were not
supported with health research funds. Include position titles (Research Assistant,
Administrative Assistant, etc.) and percent of effort on project. For multiple year projects, if
percent of effort varied from year to year, report in the % of Effort column the effort by year
1, 2, 3, etc. of the project (x% Yr 1; z% Yr 2-3).

Last Name Position Title % of Effort on Project
Curran Principal Investigator 5%

9(D) Provide a list of all scientific equipment purchased as part of this research grant, a short
description of the value (benefit) derived by the institution from this equipment, and the cost
of the equipment.

Type of Scientific Equipment Value Derived Cost
Stata Corporation Statistical analysis software $ 9,632.73

10. Co-funding of Research Project during Health Research Grant Award Period. Did this
research project receive funding from any other source during the project period when it was
supported by the health research grant?

Yes_________ No_____x_____

If yes, please indicate the source and amount of other funds:

11. Leveraging of Additional Funds

11(A) As a result of the health research funds provided for this research project, were you
able to apply for and/or obtain funding from other sources to continue or expand the
research?

Yes_________ No______ x____

If yes, please list the applications submitted (column A), the funding agency (National
Institutes of Health—NIH, or other source in column B), the month and year when the
application was submitted (column C), and the amount of funds requested (column D). If

2
you have received a notice that the grant will be funded, please indicate the amount of funds
to be awarded (column E). If the grant was not funded, insert “not funded” in column E.

Do not include funding from your own institution or from CURE (tobacco settlement funds).
Do not include grants submitted prior to the start date of the grant as shown in Question 2. If
you list grants submitted within 1-6 months of the start date of this grant, add a statement
below the table indicating how the data/results from this project were used to secure that
grant.

A. Title of research B. Funding C. Month D. Amount E. Amount
project on grant agency (check and Year of funds of funds to
application those that apply) Submitted requested: be awarded:
NIH $ $
None  Other federal
(specify:_______)
 Nonfederal
source (specify:
_____________)

11(B) Are you planning to apply for additional funding in the future to continue or expand
the research?

Yes___x______ No__________

If yes, please describe your plans:

We may apply in the future for funding to cover additional cancer related translational
research projects.

12. Future of Research Project. What are the future plans for this research project?

None

13. New Investigator Training and Development. Did students participate in project
supported internships or graduate or post-graduate training for at least one semester or one
summer?

Yes_________ No____x__

If yes, how many students? Please specify in the tables below:

Undergraduate Masters Pre-doc Post-doc
Male
Female
Unknown
Total

3
Undergraduate Masters Pre-doc Post-doc
Hispanic
Non-Hispanic
Unknown
Total

Undergraduate Masters Pre-doc Post-doc
White
Black
Asian
Other
Unknown
Total

14. Recruitment of Out-of–State Researchers. Did you bring researchers into Pennsylvania to
carry out this research project?

Yes_________ No___ x_______

If yes, please list the name and degree of each researcher and his/her previous affiliation:

15. Impact on Research Capacity and Quality. Did the health research project enhance the
quality and/or capacity of research at your institution?

Yes_________ No____ x______

If yes, describe how improvements in infrastructure, the addition of new investigators, and
other resources have led to more and better research.

16. Collaboration, business and community involvement.

16(A) Did the health research funds lead to collaboration with research partners outside of
your institution (e.g., entire university, entire hospital system)?

Yes_________ No____ x______

If yes, please describe the collaborations:

16(B) Did the research project result in commercial development of any research products?

Yes_________ No___x _______

If yes, please describe commercial development activities that resulted from the research
project:

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16(C) Did the research lead to new involvement with the community?

Yes_________ No___ x_______

If yes, please describe involvement with community groups that resulted from the
research project:

17. Progress in Achieving Research Goals, Objectives and Aims.
List the project goals, objectives and specific aims (as contained in the grant application’s
strategic plan). Summarize the progress made in achieving these goals, objectives and aims
for the entire grant award period. Indicate whether or not each goal/objective/aim was
achieved; if something was not achieved, note the reasons why. Describe the methods used.
If changes were made to the research goals/objectives/aims, methods, design or timeline
since the original grant application was submitted, please describe the changes. Provide
detailed results of the project. Include evidence of the data that was generated and analyzed,
and provide tables, graphs, and figures of the data.

This response should be a DETAILED report of the methods and findings. It is not sufficient
to state that the work was completed. Insufficient information may result in an unfavorable
performance review, which may jeopardize future funding. If research findings are pending
publication you must still include enough detail for the expert peer reviewers to evaluate the
progress during the course of the project.

Health research grants funded under the Tobacco Settlement Act will be evaluated via a
performance review by an expert panel of researchers and clinicians who will assess project
work using this Final Progress Report, all project Annual Reports and the project’s strategic
plan. After the final performance review of each project is complete, approximately 12-16
months after the end of the grant, this Final Progress Report, as well as the Final Performance
Review Report containing the comments of the expert review panel, and the grantee’s written
response to the Final Performance Review Report, will be posted on the CURE Web site.

There is no limit to the length of your response. Responses must be single-spaced below,
no smaller than 12-point type. If you cut and paste text from a publication, be sure
symbols print properly, e.g., the Greek symbol for alpha () and beta (ß) should not
print as boxes (). DO NOT DELETE THESE INSTRUCTIONS.

1) Dawson, D., Garcia, M., Dawson, N., Tze, S., Seligson, D., Farrell, J., Kurdistani, S. &
Guha, C. (2008). Cellular Patterns of Histone Modifications Predict Clinical Prognosis in
Resectable Pancreatic Adenocarcinoma: Results from the RTOG 9704 Study. Am Assoc for
Cancer Res (AACR) 99th Annual Meeting, San Diego, CA, AACR.

Background:
Locus-specific alterations in histone modifications play important roles in the dysregulated
expression of particular genes involved in tumor progression. Cancer cells also show changes in

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cellular levels of specific histone modifications, with some cells containing higher levels of
certain histone modifications than others. This cellular epigenetic heterogeneity is predictive of
clinical outcome in prostate carcinoma. Here we assessed whether cellular levels of a histone
modification could predict clinical outcome in pancreatic adenocarcinoma.

Methods:
Immunohistochemical analysis for histone 3 lysine 9 dimethylation (H3K9me2) was performed
on tissue microarrays (TMAs) of resected pancreatic adenocarcinoma from patients enrolled in
the multicenter Radiation Therapy Oncology Group 9704 clinical trial of localized pancreatic
adenocarcinoma (n=195, eligible patients analyzable by immunohistochemistry). The median
percentage of tumor cells positive for H3K9me2 was determined for each patient tumor across
triplicate TMAs and was assigned a percent rank relative to all tumors evaluated. Patients were
divided into two groups based on a median percent rank cut-off of < 30 or > 30. The two groups
were statistically evaluated against baseline clinical and pathologic parameters, as well as
clinical outcome measures.

Results:
There were no positive statistical correlations between the two H3K9me2 groups and various
baseline parameters, including patient age/sex, tumor location, tumor size, tumor grade, margin
status, lymph node involvement or AJCC stage. Both univariate and multivariate proportional
hazard analyses demonstrated that the > 30 percent rank group was significantly associated with
better overall survival (univariate: p=0.02 HR=0.69; multivariate: p=0.02 HR=0.68) and disease-
free survival (univariate: p=0.006 HR=0.64; multivariate: p=0.002 HR=0.61). These data
correspond to a median disease free survival time of 9.24 months (95 % Confidence Interval (CI)
7.56-12.84 months) for the < 30 percent rank group versus 11.4 months (CI 9.96-12.6 months)
for the > 30 percent rank group.

Conclusions:
Immunohistochemical evaluation of a single histone modification (H3K9me2) in resectable
pancreatic cancer identifies two distinct sub-groups of patients with significant differences in
disease-free and overall survival, independent of other established prognostic indicators.
Increased prevalence of cells with lower cellular levels of H3K9me2 correlates with worse
outcome. Therefore, subgroups of pancreatic adenocarcinoma may be driven by distinct
epigenetic mechanisms and could respond differently to epigenetic therapy. Simple
immunohistochemical evaluation of H3K9me2 and/or other histone modifications represent
potential prognostic or predictive biomarkers for pancreatic adenocarcinoma.

2) Doll, C., Winter, K., Gaffney, D., Ryu, J., Jhingran, A., Dicker, A., Weidhaas, J., Miller, B.
& Magliocco, A. (2008). ERCC1, COX-2, and p53 Expression in Patients with Locally
Advanced Cervical Cancer Treated with Chemoradiotherapy and Celecoxib: A Quantitative
Immunohistochemical Analysis of RTOG 0128. ASTRO, Boston, MA, Elsevier.

Purpose/Objective(s)
To measure expression of ERCC1 in pre-treatment tumor biopsies in patients with locally
advanced cervical cancer treated with RT alone, to compare measurements using conventional

6
immunohistochemistry (IHC) vs automated quantitative IHC (AQUA®) expression, and to
correlate expression with clinical outcome.

Materials/Methods
This is a retrospective study of 192 patients who completed radical RT alone for cervical cancer
between 1986 and 1999. 120 patients had pre-RT paraffin-embedded tumor specimens available,
and tissue microarrays were constructed. Immunostaining was performed to detect protein levels
of ERCC1, using mouse anti-human ERCC1 monoclonal Ab, clone 8F1. ERCC1 was measured
using both conventional IHC, using a 4-point grading system (0, no staining; 1, weak staining; 2,
moderated staining; and 3, strong staining), and AQUA®. AQUA® ERCC1 expression was
analyzed by quartiles. Kaplan-Meier curves were constructed, and Cox univariate and
multivariate regression models were used to explore associations between expression of the
protein markers and clinical endpoints (local response at 3 months after RT, overall survival
[OS]). The kappa statistic was used to determine agreement between conventional IHC and
AQUA® methods.

Results
Mean follow-up was 6 years. The majority of patients (63%) had FIGO stage IIB or III disease.
Mean radiation dose to point A was 82 Gy, typically using a combination of external beam RT
and low dose rate brachytherapy. Tumors with ERCC1 expression in the highest quartile (>975)
were classified as high expressors. The 10-year OS was worse in high ERCC1 expressors: 24%
vs 50%, HR = 1.7 (p = 0.04). In addition, tumors with high ERCC1 expression had a worse local
response to RT, with 73% complete clinical response to RT at 3 months post RT, versus 88% (p
= 0.06). On multivariate analysis, adjusting for FIGO stage, pre-treatment hemoglobin, and nodal
status, high ERCC1 expression remained a significant independent prognostic factor for death
(HR = 1.9, p = 0.027). Measurement of ERCC1 using conventional IHC scoring methods did not
significantly correlate with outcome (10-year OS 39% for high expressors vs 47%, p = 0.52;
local response at 3 months 80% vs 88%, p = 0.22). Agreement between conventional IHC and
AQUA results was poor (kappa = 0.26).

Conclusions
Cervical cancer patients with high ERCC1 expressing tumors treated with RT have significantly
worse overall survival, and a trend to worse local response. AQUA® appears to be superior to
conventional IHC in identifying patients at risk for death. This subset of patients may be more
resistant to radiation therapy.

3) Komaki, R., Paulus, R., Olsen, C., Conway, P., Ang, K., Trotti, A., Blumenschein, G.,
Curran, W., Choy, H. & Hirsch, F. (2008). Correlation of EGFR Expression by IHC & FISH to
Predict Patient Outcome: A Phase II RTOG 0324 Study for Patients With Stage III NSCLC
Treated by Chemoradiotherapy & Cetuximab (C225). ASTRO, Boston, MA, Elsevier.

Purpose/Objective(s)
NSCLC expresses epidermal growth factor receptor (EGFR), which is associated with poor
outcome. Cetuximab is a chimerized monoclonal antibody that targets EGFR and has been
shown as a radiosensitizer.

7
Materials/Methods
Stage III NSCLC pts with PS = 1 and weight loss = 5% were treated by C225 (400 mg/m2) on
day 1 of wk 1, then wkly C225 (250 mg/m2) until completion of therapy (wks 2-17). During wk
2, pts started CRT (63 Gy/35 fx) and wkly carboplatin (C) AUC 2 and paclitaxel (P) 45 mg/m2 ×
6 followed by C (AUC 6) and P (200 mg/m2) × 2 (wks 12-17). 45 (52%) pts had EGFR
evaluated by FISH and 51 (59%) pts had EGFR evaluated by IHC. 42 (48%) pts had both FISH
and IHC. Analysis of FISH, IHC, and both were done to predict pt outcome.

Results
93 pts were accrued 3/2004 to 6/2005 with 87 evaluable for analysis. 45 (52%) pts had EGFR
evaluated by FISH and 51 (59%) pts had EGFR evaluated by IHC. 42 (48%) pts had both FISH
and IHC. There were no differences in pretreatment characteristics of pts with FISH, IHC, or
both (with IHC = 45 vs. without IHC = 42) and IHC (with EGFR = 51 vs. without EGFR = 36).
Pts without FISH and/or IHC were more likely to have non-squamous ca. compared to pts with
both FISH and IHC (78% vs. 55%; p = 0.02). Pts with IHC had a better 24-m OS and 24-m PFS
compared to pts without IHC (OS: 62.6% vs. 30.6%, log-rank p = 0.013; PFS: 37.3% vs. 16.7%,
log-rank p= 0.012). Pts without IHC were twice as likely to progress as pts with it (hazard ratio
[HR]: 1.94, p = 0.019). 42 pts had both FISH and IHC available. 9/42 had pos FISH and a med
IHC QS = 0.713 and 33 (79%) did not. Pts with pos FISH score with a med IHC QS > 0.713.
Analysis showed that the 24-m actuarial estimates and Cox proportional hazards models for OS,
PFS, and TTP, respectively were generated. The 24-m OS for FISH pos/IHC = 0.713 gp is
66.7% (28.2, 87.8) and 54.2% (35.9, 69.4) for the other gp [HR = 0.88 (0.35, 2.27)]. The 24-m
PFS for the FISH pos/IHC QS = 0.713 gp is 22.2% (3.4, 51.3) and 33.3% (18.2, 49.3) for the
other gp [HR = 0.92 (0.41, 2.06)]. The 24-m TTP failure for the FISH pos/IHC QS = 0.713 gp is
55.6% (18.6, 92.5) and 51.5% (34.0, 5969.1) for the other gp [HR = 0.96 (0.38, 2.42)].

Conclusions
Pts without FISH and/or IHC are more likely to have non-squamous ca. compared to pts that
have both. This analysis suggests that the gp with low IHC/pos FISH has better 24-m OS and
PFS compared to the other gp, although there was no significant difference in regards to pts
outcome, which might be related to a small sample size.

4) Le, Q.-T., Harris, J., Magliocco, T., Kong, C., Diaz, R., Trotti, A., Erler, J., Dicker, A.,
Amato, G. & Ang, K. (2008). Validation of Lysyl Oxidase (LOX) as a Prognostic Marker for
Metastasis and Survival in Head and Neck Squamous Cell Carcinoma (HNSCC)--Radiation
Therapy Oncology Group (RTOG) Trial 9003. ASCO-NCI-EORTC (Molecular Markers in
Cancer), Hollywood, FL.

Background:
Tumor hypoxia promotes aggressive tumor phenotypes. We have previously identified LOX as a
hypoxia induced gene that mediates metastasis. Here, we validate the role of LOX as a marker
for metastasis in an independent HNSCC patient group.

8
Methods:
We performed traditional immunohistochemical (IHC) staining and automated quantitative
analysis (AQUA) for LOX expression in a small HNSCC patient group (n = 66) from one
institution. After establishing that both approaches correlated with each other, we performed
AQUA staining for LOX in 306 patients treated on RTOG 9003, a phase III trial comparing 4
radiation fractionation schedules without chemotherapy in 1,113 locally advanced HNSCC
patients. Pretreatment characteristics were similar between patients with and without LOX
assessment. We correlated AQUA LOX expression to time to metastasis (TTM, distant or
regional failure as first events), time to progression (TTP, any failure) and overall survival (OS).

Results:
There was a significant correlation of LOX intensity staining between IHC and AQUA (r = 0.26,
p = 0.036). LOX expression from both methods predicted for TTM in the small patient cohort.
AQUA consistently showed stronger nuclear than cytoplasmic LOX staining. The mean LOX
expression was 170.9 (SD 43.8) for nuclear and 130 (SD 45.3) for cytoplasmic staining.
Multivariate analysis, controlling for clinically significant parameters including nodal stage and
performance status, revealed that nuclear LOX expression, as a continuous variable, was an
independent predictor for TTM (hazard ratio [HR] 1.009, 95% CI 1.004-1.015, p = 0.0004), TTP
(HR 1.006, 95% CI 1.002-1.009, p = 0.004) and OS (HR 1.003, 95% CI 1.000-1.006, p = 0.03).
When nuclear LOX level was analyzed by quartiles, there was a 74% increase metastatic risk for
patients at the 75th percentile compared to those at the 25th percentile.

Conclusions:
AQUA nuclear LOX expression was strongly associated with increased metastasis, progression
and death in RTOG 9003 patients. This study validates LOX as a prognostic marker for
metastasis and survival in HNSCC.

5) Olsen, C., Paulus, R., Komaki, R., Varella-Garcia, M., Dziadziuszko, R., Curran, W., Robert,
F., Choy, H., Blumenschein, G. & Hirsch, F. (2008). RTOG 0324: A Phase II Study of
Cetuximab (C225) in Combination with Chemoradiation (CRT) in Patients with Stage IIIA/B
Non-Small Cell Lung Cancer (NSCLC): Correlation between FISH EGFR Expression and
Patients' Outcome. ASCO, Chicago, IL.

Background:
Cetuximab in combination with chemotherapy appears promising in first line therapy for
NSCLC.1,2 EGFR gene copy number is a predictive outcome marker for treatment with EGFR
tyrosine kinase inhibitors (TKIs). Here we evaluate EGFR copy number by FISH in NSCLC
patients receiving Cetuximab with concurrent chemoradiation.

Methods:
Patients with Stage III NSCLC and PS 1-1 were treated with a loading dose C225 (400mg/m2
IV) followed by weekly doses of C225 (250mg/m2 IV) with concurrent chemoradiation (63
Gy/35 fractions) with weekly carboplatin (C), (AUC 2) and paclitaxel (P), (45 mg/m2) x 6 doses
followed by C (AUC 6) and P (200mg/m2) x 2 cycles. EGFR FISH analysis was performed on
formalin-fixed paraffin-embedded tissue sections as described previously.3 Tumors with 4 or

9
more copies of the EGFR gene in ≥ 40% of the cells (high polysomy) or tumors with EGFR gene
amplification with a gene/chromosome ratio >2 or ≥ 15 gene copies in > 10% of the cells were
considered FISH positive, while all others were considered FISH negative.

Results:
Ninety-three patients were accrued between March 2004 and June 2005, 87 of whom were
evaluable for analysis. Tissue samples were collected from 51 patients and 45 were available for
FISH analysis. Pretreatment characteristics for those patients with FISH data in comparison to
those that did not have tissue available were similar. The 24 month OS for the patients with
positive FISH scores was 61.9% compared to 53.8% in FISH negative samples (log-rank p-
value=0.95). 24 month TTP was 57.1% and 45.8% (Gray's p-value = 0.84), respectively. 24% of
evaluable FISH positive patients underwent complete/partial response in comparison to 8% of
FISH negative patients.

Conclusions:
Tissue testing for FISH is feasible in patients with Stage III NSCLC. Despite non- mandatory
collection, samples were obtained in over 50% of the patients. Patients with FISH-positive
disease appeared to have a higher response rate and tendency to better outcome. The data should
be verified in prospective studies.

1. Rosell R, Robinet G, Szczesna et al. Randomized Phase II study of cetuximab plus
cistplatin/vinorelbine compared with cisplatin/vinorelbine alone as first line therapy in EGFR
expressing advanced non-small cell lung cancer. Annals of Oncology 2007
2. Herbst RS, Chansky K, Kelly K et al. A phase II randomized trial evaluating concurrent
chemotherapy plus cetuximab or chemotherapy followed by cetuximab in patients with advanced
non-small cell lung cancer. Final report of SWOG 0342. Proceedings 2007 ASCO Annual
Meeting.
3. F Cappuzzo, FR Hirsch, E Rossi et al. Epidermal Growth Factor Receptor Gene and Protein
and Gefitinib Sensitivity in Non-Small Cell Lung Cancer . J Natl Cancer Inst. 2005 May 4;
97(9):643-55.

6) Weidhaas, J., Li, S., Winter, K., Ryu, J., Jhingran, A., Miller, B., Dicker, A. & Gaffney, D.
(2008). Changes in Gene Expression Predicting Local Control in Cervical Cancer: Results from
RTOG 0128. ASTRO, Boston, MA, Elsevier.

Purpose/Objective(s)
To evaluate the potential of gene expression signatures to predict response to treatment in locally
advanced cervical cancer treated with definitive chemotherapy and radiation.

Materials/Methods
Biopsies were collected before treatment and before the first implant (mid-treatment biopsy)
from patients participating on a phase II RTOG trial evaluating the benefit of celecoxib in
addition to cisplatin chemotherapy and radiation therapy for locally advanced cervical cancer.
Gene expression profiling was performed on all samples of adequate quality, and signatures of
pre, mid-treatment, and changing gene expression patterns between pre and mid-treatment

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samples were evaluated. The ability of the gene signatures to predict local control versus local
failure was evaluated. Two group t tests were performed to identify the initial gene set.
Supervised classification methods were used to enrich the gene sets. The results were further
validated by leave one out or 2-fold cross-validation.

Results
22 patients had suitable material from pretreatment samples for analysis and there were 13 paired
samples (pre-treatment mid-treatment). Initial and mid-treatment gene expression signatures
alone were unable to separate patients by local control status. However, the altered gene
expression signatures between the initial and mid-treatment biopsies were able to predict
response to treatment, separating patients with local failures from those who achieved local
control. Importantly, the gene signature pattern achieving separation between local failure and
local control contained only 7 genes. The in-sample prediction rate, leave one out prediction rate,
and two-fold prediction rate are 100% for this seven gene set. This signature was enriched for
cell cycle genes.

Conclusions
Although the numbers in the study were small, changes in gene expression during therapy in
cervical cancer can predict outcome as measured by local control in cervical cancer. These data
support the notion that alteration of cell cycle parameters may be pivotal in successful
chemoradiation protocols. These are important first steps towards tailoring therapy to
individuals. Further translation research trials are warranted evaluating gene expression profiling
in cervix and other cancers. These data indicate that attention to changes in gene expression
patterns is important.

7) Prakash Chinnaiyan, Meihua Wang, Amyn M. Rojiani, Philip J. Tofilon, Arnab Chakravarti,
K. Kian Ang, Hua-Zhong Zhang, Elizabeth Hammond, Walter Curran, Jr., Minesh P. Mehta. The
Prognostic Value of Nestin Expression In Newly Diagnosed GBM: Report From The RTOG.
Accepted for Presentation at ASTRO 2008 (Sept), Boston, MA.

Purpose:
Nestin is an intermediate filament protein that has been implicated in early stages of neuronal
lineage commitment. Based on the heterogeneous expression of nestin in GBM and its potential
to serve as a marker for a dedifferentiated, and perhaps more aggressive phenotype, the
Radiation Therapy Oncology Group (RTOG) sought to determine the prognostic value of nestin
expression in newly diagnosed GBM patients.

Methods:
Patients in this study had been treated on previous RTOG GBM trials (RTOG 7401, 7918, 8302,
8409, 9006, 9305, 9602, and 9806). Tissue microarrays were prepared from 156 patients
enrolled in these trials. The specimens were stained using a mouse monoclonal antibody specific
for nestin and expression was measured by computerized quantitative image analysis using the
Ariol SL-50 system. The parameters measured included both staining intensity and the relative
area of expression within a specimen. This resulted into 3 categories: low, intermediate, and
high nestin expression, which was then correlated with clinical outcome.

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Results:
A total of 153 of the 156 samples were evaluable for this study. The total number of patients that
comprised the low, intermediate, and high expression groups were 17, 70, and 66, respectively.
There were no statistically significant differences seen between patient pretreatment
characteristics and nestin expression. When the three groups were compared with regards to OS
and PFS based on the log-rank test, no differences were seen at the significance level of 0.05.
The 12-month OS for patients with low, intermediate, and high nestin expression were 59%,
49%, and 48%, respectively. The 12-month PFS for patients with low, intermediate, and high
nestin expression were 29%, 27%, and 23%, respectively. Based on the Cox proportional
hazard model, no difference was found in OS with nestin expression level [intermediate vs. low:
HR=1.66 (0.94, 2.93), p=0.98; high vs. low: HR=1.47 (0.83, 2.60), p=0.18], even after adjusting
for RPA class [IV vs. III: HR=1.65 (1.03, 2.66), p=0.04; V vs. III: HR=2.58 (1.60, 4.15),
p<0.0001]. The global test for the interaction of nestin expression level and RPA class was not
statistically significant (P< 0.001). No difference was found in PFS with nestin expression level
[intermediate vs. low: HR=1.47 (0.84, 2.59), p=0.18; high vs. low: HR=1.73 (0.98, 3.06),
p=0.06] without including RPA class, which was not statistically significant.

Conclusions:
Although the correlation of nestin expression and histologic grade in glioma is of considerable
interest, it does not appear to have significant prognostic value in newly diagnosed GBM.
Further studies evaluating nestin expression may be more informative when studied in lower
grade glioma or in the context of markers more specific to tumor stem cells.

8) Chakravarti, A.; Wang, M.; Mischel, P.; Robins, I.; Guha, A.; Machtay, M.; Curran, W.;
Roach, M.; Mehta, M.; Dicker, A. An Update on Correlative Molecular Endpoints from RTOG
0211: Phase I/II Study of Gefitinib + Radiation for Newly Diagnosed Glioblastoma Patients.
Accepted for Presentation at ASTRO 2008 (Sept), Boston, MA.

Purpose:
The RTOG 0211 clinical data revealed that the addition of Gefitinib was generally well-tolerated
in combination with radiation, but that survival times were not significantly improved compared
to historical controls (ASTRO 2006). Based on these data, the vital question becomes what
molecular subgroups of GBM patients are likely to benefit from anti-EGFR therapies so that
such therapies can be more appropriately directed. The present report is the first to report on
molecular correlates of clinical outcome in GBM patients treated by anti-EGFR therapies in the
upfront setting and represents the most comprehensive correlative analysis performed on GBM
patients treated by anti-EGFR therapies.

Methods:
Tissue blocks were prospectively collected on 74 out of the 148 RTOG 0211 cases, which were
used to generate tissue microarrays (TMAs). The respective predictive values of 12 molecules
integral to EGFR signaling either have been examined or will be examined by the time of the
ASTRO annual meeting (EGFR, pEGFR, EGFRvIII, PTEN, pAKT, pMAPK, pmTor, IGFR1,
NFKB, Survivin, MGMT, and pSrc). The molecules that have been examined to-date include
EGFR, EGFRvIII, PTEN, and pAKT. The present study was performed using the Histo-Rx

12
AQUA platform, which is a multi-tissue proteomic tissue analysis platform using a fluorescence-
based image analysis to quantify protein expression in subcellular compartments. In addition to
AQUA analysis, EGFRvIII and PTEN were analyzed using traditional immunohistochemical
staining and manual scored scoring to reproduce the technique that was used in the Mischel
NEJM report.

Results:
Neither total EGFR, EGFRvIII, nor PTEN expression as single markers was significantly
associated with either overall (OS) or progression-free survival (PFS) in GBM patients treated on
RTOG 0211. Patients with co-expression of EGFRvIII and intact PTEN as determined by
manual scoring had 12-month overall and 5.4-month progression-free survivals, respectively,
compared to 9.5 months and 4.7 months in non-co-expressing patients treated on RTOG 0211
[OS: HR=1.462 (95% CI: 0.689-3.10); PFS: HR=1.836 (95%CI: 0.797-4.23), p=NS (study
underpowered to detect significant difference)]. Likewise, AQUA scoring failed to find any
significant correlation with outcome in co-expressors of EGFRvIII and PTEN. Patients
expressing high versus low levels of pAKT had significantly shorter survival times (p=0.047).

Conclusions:
In the upfront setting, activation of AKT signaling appears to be associated with adverse
outcome in Gefitinib-treated GBM patients. The complete RTOG 0211 correlative data based on
the 12-marker panel will be presented at the time of the 2008 ASTRO annual meeting.

9) Giannini, C., B. Berkey, G. Cairncross, P. Burger, R. Jenkins, M. Mehta, W. Curran, K.
Aldape (2008). "Anaplastic Oligodendroglial Tumors: Refining the Correlation among
Histopathology, 1p 19q Deletion and Clinical Outcome in Intergroup Radiation Therapy
Oncology Group Trial 9402." Brain Pathology 18(3): 360-369.

Intergroup Radiation Therapy Oncology Group Trial 9402 study, a phase III trial of
chemotherapy plus radiotherapy (PCV-plus-RT) vs. radiotherapy alone for pure and mixed
anaplastic oligodendroglioma confirmed the prognostic significance of 1p 19q deletion and
showed that only progression-free survival (PFS) was prolonged in PCV-plus-RT-treated
patients and only in association with 1p 19q deletion. We reviewed tumor histopathology,
separating 115 tumors deemed to be classic for oligodendroglioma (CFO) from 132 lacking
classic features of oligodendroglioma (NCFO) and evaluated the relationship of histopathology
and 1p 19q status to treatment and outcome. The study disclosed: (i) overall survival (OS) of
patients with CFO was significantly longer than for patients with NCFO (P < 0.0001) and was
not affected by necrosis. Median OS for CFO patients with and without necrosis was 6.6 and 6.3
years (OS log-rank P = not significant), respectively, in contrast to NCFO showing 1.9 and 3.3
years respectively (OS log-rank P = 0.014). (ii) Classic oligodendroglial morphology was highly
associated with 1p 19q deletion, present in 80% of CFO and only in 13% of NCFO. (iii) On
multivariate analysis, both classic oligodendroglial morphology and 1p 19q deletion remained
significantly associated with PFS and OS. (iv) Patients with CFO treated with PCV-plus-RT
showed a trend toward increased survival compared with CFO treated with RT (P = 0.08).
Median OS was not reached in the PCV-plus-RT group and was 6.3 years in RT group. These

13
findings suggest that classic oligodendroglial morphology combined with 1p 19q deletion may in
the future be predictive of chemotherapeutic response and survival.

10) Konski, A., Winter, K., Khor, L.-Y., Al-Saleem, T., Abrams, R., Small Jr, W., Rich, T. &
Willett, C. (2006). Over-Expression of RIa Subunit (RIas) of Protein Kinase A May be a Marker
for Favorable Pancreatic Cancer: An Analysis of Patients Treated on Radiation Therapy
Oncology Group (RTOG) 98-12. 2006 ASCO Gastrointestinal Cancer Symposium, San
Francisco, CA.

Introduction:
The specific aim of this study was to investigate the relationship of expression of RIas of PKA to
outcome in patients with pancreatic cancer treated on RTOG 98-12.

Methods:
RTOG 98-12 was a phase II study of external irradiation, 50.4 Gy in 28 fractions, with weekly
paclitaxel, 50 mg/m2, for pts. with nonmetastatic, unresectable (PCA). Paraffin-embedded
formalin-fixed tissues were processed and stained with antibody to RIas of PKA. Normal and
tumor tissue were graded for intensity of staining using 4 categories: 0 (no staining), 1 (weak
staining), 2 (moderate staining) and 3 (strong staining) and reported in four categories: under,
normal/under, normal and over. Between group differences in selected pt. characteristics were
evaluated with a Chi-square test, overall survival was estimated using Kaplan-Meier methods
and a Cox proportional hazards model was used to assess PKA RIa expression with observed
survival.

Results:
One-hundred and twenty-two pts. were accrued and 109 were eligible and analyzable for
outcome; PKA RIa status was determined for 41 pts. Clinical N0 status was significantly
associated with normal and over expression vs. under, normal/under of PKA RIas, p=0.0480. No
significant associations in RIas PKA expression were identified with the characteristics
examined. Results are shown in the table below.

14
Univariate Endpoint Analyses of RIas 1-Year Rate*
n Failures HR** p-value***
PKA Staining (%)
Survival
Under, Normal/Under 10 10 40 0.757 0.4567
(0.364-
vs. Normal, Over 31 28 45.2
1.576)
Under, Normal/Under, Normal 32 29 43.8 0.895 0.7741
(0.419-
vs. Over 9 9 44.4
1.910)

Progression-free survival
Under, Normal/Under 10 10 0 0.628 0.2207
(0.298-
vs. Normal, Over 31 31 16
1.323)
Under, Normal/Under, Normal 32 32 9 0.992 0.9824
(0.465-
vs. Over 9 9 22
2.113)

Conclusions:
Pts. with normal/over-expression of RIa PKA had significantly less clinical involvement of
lymph nodes. No significant associations between RIas PKA expression and outcome were
found, however the sample size is small and therefore the power to detect differences, if they
actually exist, is limited. Further study with larger samples is warranted to assess the relationship
of RIas PKA expression and outcome in pts. with (PCA). Univariate Endpoint Analyses of RIas
PKA Staining

11) Zempolich, K., Milash, B., Fuhrman, C., Robert, F., Greven, K., Ryu, J., Forbes, A., Kerlin,
K., Nicholas, R. & Gaffney, D. (2005). Changes in Gene Expression Induced by Chemoradiation
in Advanced Cervical Carcinoma: A Microarray Study of RTOG C-0128. Proc Amer Soc Thera
Rad Onc (ASTRO), Denver, CO, Elsevier.

Purpose/Objective:
To evaluate gene expression patterns in patients with advanced cervix cancer before and during
chemoradiation in a multi-institutional cooperative group setting.

Materials/Methods:
RTOG C0128 was designed to look at the safety and efficacy of radiation therapy with
concomitant 5-FU and cisplatin chemotherapy, and Celecoxib at 400 mg twice daily for one
year. Patients had the option of participating in a tissue collection portion of the protocol to be
utilized for micro-array gene expression analysis before treatment and at the time of the first

15
implant (paired sample). RNA was extracted, linearly amplified, and purity was assessed by gel
electrophoresis. Each sample was hybridized against a universal RNA mixture on a customized
spotted array consisting of > 10,000 genes. We compared gene expression profiles with pre-
treatment characteristics (FIGO stage, age, race, and histology), and changes with
chemoradiation in individual patients. Data were normalized using the AROMA software, and
clustering analysis was performed using Ward's method in Spotfire. Differences in paired
samples were calculated with Significance Analysis of Microarrays (SAM).

Results:
From August 2001 to March 2004, 84 patients were accrued to the trial, and tissue was obtained
prior to initiation of therapy on 34 patients (40%). FIGO stages for the patients who provided
tissue were IB (23%), II (57%), and IIIA-IVA (20%). RNA quality was sufficient to proceed to
microarray analysis in 22 pre-treatment and 14 post-treatment samples. Gene expression profiles
were correlated to pre-treatment characteristics. No significant differences were observed by
FIGO stage, age, or race; however, histology (adenocarcinoma, n=5, versus squamous cell
carcinoma, n=17) yielded 45 genes differentially expressed with a false discovery rate of 0.018.
Cluster analysis segregated unpaired samples into 2 groups; 18 of 22 samples comprising pre-
treatment samples and 10 of 14 in the other group representing post-treatment samples. Among
13 paired samples, gene expression after chemoradiation was upregulated in 91 genes and down
regulated in 251 genes, with a false discovery rate of 0.0018. Genes significantly upregulated
included bax, cdk inhibitor 1, MMP2, and adhesion molecules PECAM1, VCAM1, and ICAM2.
Genes significantly downregulated included topoisomerase II alpha, myc, H2AX, MSH2,
RAD51, RAD53, PCNA, and cell cycle-regulating molecules chk1, CDK2, cyclinB1, cyclin D3,
cdc2, and cdc25.

Conclusions:
Microarray analysis was successfully performed in a multinational cooperative group trial.
Patterns of gene expression significantly correlated with histologic subtype, but not stage, age or
race. Cluster analysis identified two groups of gene expression profiles correlating with pre or
post-treatment acquisition of tissue. Notably, paired samples showed significant changes in gene
expression following chemoradiation. Quantitative PCR can be utilized to confirm these changes
in gene expression. Further analysis comparing gene expression to clinical outcomes, acute and
late toxicities awaits maturation of clinical data. Hopefully, this information will lead to targeted
therapy based on expression profiles.

12) Zhang, M., Ho, A., Hammond, E., Roach III, M., Sause, W., Pilepich, M., Shipley, W.,
Sandler, H., Pollack, A. & Chakravarti, A. (2005). The Prognostic Value of Surviving in Locally
Advanced Prostate Cancer: A Study Based on RTOG 8610. Proc Amer Soc Thera Rad Onc
(ASTRO), Denver, CO, Elsevier.

Purpose/Objective:
Survivin is a member of the inhibitor of apoptosis family that has been implicated in both control
of apoptosis and regulation of cell division. Growing evidence suggests that nuclear Survivin
expression may represent an important prognostic marker to predict disease outcome for cancer
patients. Current reports in this field, however, are controversial and propose opposing

16
conclusions regarding the significance and prognostic value of nuclear Survivin expression. To
our knowledge, no study has previously examined the predictive value of nuclear Survivin
expression in men with prostate cancer. We examined the association between nuclear Survivin
expression and overall survival, prostate cancer survival, distant metastasis, and local
progression in men treated with radiotherapy (RT) alone or RT + short term androgen
deprivation (STAD) who were enrolled in Radiation Therapy Oncology Group (RTOG) protocol
8610.

Materials/Methods:
Of the 456 eligible and analyzable cases (parent cohort), 68 patients had adequate and suitably-
stained tumor material for nuclear Survivin analysis (Survivin cohort). Of these, 38 were
randomized to RT alone and to RT+STAD. Pretreatment characteristics of the parent and
Survivin cohorts were not statistically different. Expression levels of nuclear Survivin were
determined by immunohistochemical staining (DAKO Envision+, DakoCytomation, Carpinteria,
CA) using anti-Survivin polyclonal antibody (Novus Biologicals, Littleton, CO). An image-
analysis system (ACIS, Chromavision Medical Systems, San Juan Capistrano, CA) was used to
measure the percentage of cells with nuclear staining and the intensity of nuclear staining. The
five-year actuarial estimates for overall and prostate cancer survival were calculated using the
Kaplan-Meier method and the cumulative incidence method was used to estimate the five-year
local progression and distant metastasis failure rates. The univariate analyses were done using
Survivin ACIS Mean Index % as a continuous variable and an additional cutpoint of a median,
<=74.1 vs. >74.1, or using Survivin ACIS Intensity Score as a continuous variable and an
additional cutpoint of median, <=191.2 vs. >191.2. Moreover, Survivin ACIS Mean Index % was
modeled in multivariate analysis using Cox proportional hazards models to identify the impact of
nuclear Survivin on the four endpoints in the presence of other covariates such as Gleason score,
clinical stage, and assigned treatment.

Results:
Higher levels of nuclear Survivin appeared to be associated with improved outcome in this
patient population. Our analysis indicated that the cutpoint intensity score of 191.2 was most
informative in this regard. Compared to those with Survivin ACIS Intensity Score <=191.2,
those who had Survivin ACIS Intensity Score >191.2 showed a significantly improved prostate
cancer survival with a p-value of 0.05 (relative risk=0.45). On multivariate analysis, Survivin
ACIS Intensity Score >191.2 was significantly associated with improved overall survival
(p=0.02) and prostate cancer survival (p=0.02).

Conclusions:
Nuclear Survivin ACIS scores of >191.2 were associated with improved overall and prostate
cancer survivals on multivariate analysis in patients with locally advanced prostate cancer treated
on RTOG 8610. A separate analysis of the prognostic value of cytoplasmic Survivin expression
is ongoing.

13) Che, M., DeSilvio, M., Pollack, A., Grignon, D., Venkatesan, V., Hanks, G. & Sandler, H.
(2005). Prognostic Value of Abnormal P53 Expression in Locally Advanced Prostate Cancer

17
Treated with Androgen Deprivation and Radiotherapy: A Study Based on RTOG 9202.
Multidisciplinary Prostate Cancer Symposium, Orlando, FL, ASCO and ASTRO co-sponsored.

Background:
In a prior phase III clinical trial (RTOG 8610) that tested the benefits of short -term androgen
deprivation (STAD) with radiation therapy (RT) in treating men with locally advanced prostate
cancer (Pca), p53 accumulation was found to be an independent adverse prognostic factor. The
goal of this study was to verify the significance of p53 as a prognostic factor in RTOG 9202,
which extended RTOG 8610 in comparing STAD+RT to long-term androgen deprivation
(LTAD) + RT in men with locally advanced Pca. To our knowledge, this is the largest analysis
of p53 ever performed in men with Pca.

Methods:
RTOG 9202 was begun in June 1992 and completed in April 1995, accruing 1,514 assessable
patients. Tumor tissue was sufficient for p53 analysis in 777 cases, with 398 and 379 from the
LTAD+RT and STAD+RT treatment arms respectively. p53 status was determined by
immunohistochemistry according to standard protocol. Abnormal p53 expression was defined as
20% or more tumor cells with positive nuclei. Univariate and multivariate Cox proportional
hazards models were used to evaluate the relationships of p53 status to overall death, cancer-
specific death (CSD), disease-free death, distant metastasis (DM), and local and biochemical
progression.

Results:
Abnormal p53 was detected in 168 of 777 (21.6%) cases analyzed. p53 status was significantly
associated with Gleason score (GS); 41% of cases with abnormal, as opposed to 24.7% of cases
with normal, p53 had GS 8-10. Univariate and multivariate analyses showed that abnormal p53
expression was significantly associated with increased CSD and DM. The unadjusted relative
risk (RR) of abnormal versus normal p53 was 1.92 for both CSD (range 1.18-3.11) and DM
(range, 1.29-2.85). The adjusted RR was 1.77 (range, 1.06-2.95) for CSD and 1.60 (range, 1.05-
2.45) for DM.

Conclusion:
The study confirms that abnormal p53 expression is a significant and independent adverse
prognostic factor in patients with locally advanced Pca, which provides a rationale for stratifying
patients according to p53 status in future prospective clinical trials.

18. Extent of Clinical Activities Initiated and Completed. Items 18(A) and 18(B) should be
completed for all research projects. If the project was restricted to secondary analysis of
clinical data or data analysis of clinical research, then responses to 18(A) and 18(B) should
be “No.”

18(A) Did you initiate a study that involved the testing of treatment, prevention or
diagnostic procedures on human subjects?
______ Yes
__ x____No

18
18(B) Did you complete a study that involved the testing of treatment, prevention or
diagnostic procedures on human subjects?
______ Yes
__ x____No

If “Yes” to either 18(A) or 18(B), items 18(C) – (F) must also be completed. (Do NOT
complete 18(C-F) if 18(A) and 18(B) are both “No.”)

18(C) How many hospital and health care professionals were involved in the research
project?
______Number of hospital and health care professionals involved in the research
project

18(D) How many subjects were included in the study compared to targeted goals?

______Number of subjects originally targeted to be included in the study
______Number of subjects enrolled in the study

18(E) How many subjects were enrolled in the study by gender, ethnicity and race?

Gender:
______Males
______Females
______Unknown

Ethnicity:
______Latinos or Hispanics
______Not Latinos or Hispanics
______Unknown

Race:
______American Indian or Alaska Native
______Asian
______Blacks or African American
______Native Hawaiian or Other Pacific Islander
______White
______Other, specify:
______Unknown

18(F) Where was the research study conducted? (List the county where the research
study was conducted. If the treatment, prevention and diagnostic tests were offered in
more than one county, list all of the counties where the research study was
conducted.)

19
19. Human Embryonic Stem Cell Research. Item 19(A) should be completed for all research
projects. If the research project involved human embryonic stem cells, items 19(B) and
19(C) must also be completed.

19(A) Did this project involve, in any capacity, human embryonic stem cells?
______ Yes
___x ___ No

19(B) Were these stem cell lines NIH-approved lines that were derived outside of
Pennsylvania?
______Yes
______ No

19(C) Please describe how this project involved human embryonic stem cells:

20. Articles Submitted to Peer-Reviewed Publications.

20(A) Identify all publications that resulted from the research performed during the funding
period and that have been submitted to peer-reviewed publications. Do not list journal
abstracts or presentations at professional meetings. Include only those publications that
acknowledge the Pennsylvania Department of Health as a funding source (as required in
the grant agreement). List the title of the journal article, the authors, the name of the peer-
reviewed publication, the month and year when it was submitted, and the status of
publication (submitted for publication, accepted for publication or published.). Submit an
electronic copy of each publication, listed in the table, in a PDF version 5.0.5 format, 1,200
dpi. Filenames for each publication should include the number of the research project, the
last name of the PI, the number of the publication and an abbreviated research project title.
For example, if you submit two publications for PI Smith for the “Cognition and MRI in
Older Adults” research project (Project 1), and two publications for PI Zhang for the “Lung
Cancer” research project (Project 3), the filenames should be:
Project 1 – Smith – Publication 1 – Cognition and MRI
Project 1 – Smith – Publication 2 – Cognition and MRI
Project 3 – Zhang – Publication 1 – Lung Cancer
Project 3 – Zhang – Publication 2 – Lung Cancer
If the publication is not available electronically, provide 5 paper copies of the publication.

Note: The grant agreement requires that recipients acknowledge the Pennsylvania
Department of Health funding in all publications. Please ensure that all publications listed
acknowledge the Department of Health funding. If a publication does not acknowledge the
funding from the Commonwealth, do not list the publication.

20
Title of Journal Authors: Name of Peer- Month and Publication
Article: reviewed Year Status (check
Publication: Submitted: appropriate box
below):
1. Changes in Gene J. B. Weidhaas, S. Clinical Cancer October Submitted
Expression Li, K. Winter, J. Research 2008 xAccepted
Predicting Local Ryu, A. Jhingran, Published
Control in Cervical B. Miller, A. P.
Cancer: Results from Dicker, D. Gaffney
RTOG 0128

20(B) Based on this project, are you planning to submit articles to peer-reviewed publications
in the future?

Yes____x_____ No__________

If yes, please describe your plans:

Manuscripts for several of the projects described in #17 will be submitted to peer-reviewed
journals.

21. Changes in Outcome, Impact and Effectiveness Attributable to the Research Project.
Describe the outcome, impact, and effectiveness of the research project by summarizing its
impact on the incidence of disease, death from disease, stage of disease at time of diagnosis,
or other relevant measures of outcome, impact or effectiveness of the research project. If
there were no changes, insert “None”; do not use “Not applicable.” Responses must be
single-spaced below, and no smaller than 12-point type. DO NOT DELETE THESE
INSTRUCTIONS. There is no limit to the length of your response.

The results from these projects have been hypothesis generating for the RTOG Translational
Research Program.

22. Major Discoveries, New Drugs, and New Approaches for Prevention Diagnosis and
Treatment. Describe major discoveries, new drugs, and new approaches for prevention,
diagnosis and treatment that are attributable to the completed research project. If there were
no major discoveries, drugs or approaches, insert “None”; do not use “Not applicable.”
Responses must be single-spaced below, and no smaller than 12-point type. DO NOT
DELETE THESE INSTRUCTIONS. There is no limit to the length of your response.

None

23. Inventions, Patents and Commercial Development Opportunities.

23(A) Were any inventions, which may be patentable or otherwise protectable under Title 35
of the United States Code, conceived or first actually reduced to practice in the performance
of work under this health research grant? Yes No x

21
If “Yes” to 23(A), complete items a – g below for each invention. (Do NOT complete items
a - g if 23(A) is “No.”)

a. Title of Invention:

b. Name of Inventor(s):

c. Technical Description of Invention (describe nature, purpose, operation and physical,
chemical, biological or electrical characteristics of the invention):

d. Was a patent filed for the invention conceived or first actually reduced to practice in
the performance of work under this health research grant?
Yes No

If yes, indicate date patent was filed:

e. Was a patent issued for the invention conceived or first actually reduced to practice in
the performance of work under this health research grant?
Yes No
If yes, indicate number of patent, title and date issued:
Patent number:
Title of patent:
Date issued:

f. Were any licenses granted for the patent obtained as a result of work performed under
this health research grant? Yes No

If yes, how many licenses were granted?

g. Were any commercial development activities taken to develop the invention into a
commercial product or service for manufacture or sale? Yes No

If yes, describe the commercial development activities:

23(B) Based on the results of this project, are you planning to file for any licenses or patents,
or undertake any commercial development opportunities in the future?

Yes_________ No ___x _______

If yes, please describe your plans: