1. How Changes in Central Cancer Registries are Impacting Cancer Research Presented by: Thomas C. Tucker, PhD, MPH Director, Kentucky Cancer Registry University of Kentucky 29 th Advanced Cancer Registrars Workshop Louisville, KY– September 10-11, 2015 Kentucky Cancer Registry

2. Topics to be covered A very short history of the Kentucky Cancer Registry The importance of population-based cancer research ▫ Internal Validity ▫ External validity How population-based cancer registries can improve cancer research ▫ Providing a Population-Based Sample Frame ▫ Making Rapid Case Ascertainment Possible ▫ Serving as a Virtual Tissue Repository ▫ Measuring the last Phase of Translational Research The Kentucky model for moving evidence-based research into the population An example of the potential impact of implementing evidence- based research in the population

3. The importance of population-based cancer research

4. Two important concepts Internal validity External validity

5. Animal Studies genetically identical mice Developed Disease Did not Develop Disease Exposed Animals AB Unexposed Animals CD Relative Risk = (A/A+B)/(C/C+D)

6. Randomized Clinical Trial Randomized trial (Prospective) Study Outcome Occurred Did not Occur Exposure or Intervention AB No Exposure or Intervention CD Relative Risk = (A/A+B)/(C/C+D) Random Allocation

7. Internal Validity When differences between the experimental (exposed) group and the control group are completely accounted for, the study is said to have internal validity and causal inferences can be made. In other words, it is possible to determine whether the exposure causes some outcome (disease, etc.). Many have argued that “randomization” was the most important scientific advance of the 20 th century. Why is it that the findings from randomized clinical trials with internal validity almost never have the same effect when they are applied to general populations?

8. External Validity When the findings from a research project or study can be generalized to some defined population, they are said to have external validity. Epidemiology (population science) provides the tools to explore external validity and many argue that moving from studies with strong internal validity to studies with strong external validity is the next step in advancing our scientific understanding. The continuum from research with strong internal validity to studies with strong external validity is also part of “Translational Research”.

9. Population-based Central Cancer Registries Can Enhance Cancer Research in Several Important Ways.

10. Geographic Area Covered by the Population-Based Cancer Registry Cancer cases occurring each year The Population-Based Cancer Registry A scientific sample of data from cancer patients representing the population covered by the registry is provided to the researcher Cancer research with strong “ external validity” (the ability to generalize the findings to the underlying population) Information gathered on each cancer case 1. As a Population-Based Sample Frame

11. Intimate Partner Violence and Cancer Disparities Research Question: Is IPV associated with delayed screening, late stage Dx or poor survival among women diagnosed with breast, colorectal or cervical cancer in Kentucky? Design: Population-based prospective cohort study Methods: KCR recruitment Population-based Sample: n=1,850 Results: IPV (37% lifetime) Partner Interference (13%) A novel population-based cohort study Later Stage at Diagnosis  Suboptimal Treatment  Poorer Quality of Life  Poorer Survival Direct Pathway Indirect Pathway IPV & Partner Interference with Cancer Treatment Poverty, Risk behaviors, Access to care, Low education, Co-morbidity

12. Geographic Area Covered by the Population-Based Cancer Registry Pathology Labs The Population-Based Cancer Registry Receives EPath Reports for 95% of All New Cancer Cases Diagnoses each Year A population-based sample of cancer cases provided to the researcher Cancer research with strong “ external validity” (the ability to generalize the findings to the underlying population) Electronic Path (EPath) Reports for Cancer Patients Sent Automatically at the Time of Diagnosis 2. For Rapid Case Ascertainment Biospecimens collected

13. High Arsenic, Chromium and Radon Levels and High Lung Cancer Rates in Appalachian Kentucky (Top) Arsenic content and coal field locations in Kentucky; (Bottom) Incidence of lung cancer in the Appalachian versus Non-Appalachian region of Kentucky.

14. Environmental Exposure and Lung Cancer A population-based lung cancer case-control study By Drs. Arnold, Orren, Mellon, and Huang Epi, Blood, Urine, Hair, Toenails, Radon level, Tap water, Soil, GPS Hypothesis: Lung cancer incidence is higher than expected from smoking alone and is associated with exposure to environmental carcinogens 57 – 95 96 – 102 103 – 116 117 – 150 Lung Cancer Rate per 100,000 Appalachia 0-100 100-250 250-2200 Arsenic PPM Study Area

15. Live lymphocytes Environmental Exposure and Lung Cancer A population-based lung cancer case-control study By Drs. Arnold, Orren, Mellon, and Huang

16. Geographic Area Covered by the Population-Based Cancer Registry Pathology Labs A population-based sample of cancer case data and tissue are provided to the researcher Cancer research with strong “ external validity” (the ability to generalize the findings to the underlying population) Formalin fixed paraffin imbedded tissue samples are collected from the labs by the Registry for a population- based sample of cases 3. As a Population-Based Virtual Tissue Repository The Population-Based Cancer Registry

17. 1. A retrospective cohort study using the registry as a virtual tissue repository to explore 5 distinct proteins associated with breast cancer recurrence Determine whether female breast cancer patients who were disease-free following surgery but subsequently had a recurrence of their breast cancer within five years had altered levels or activity of one or any combination of five proteins compared to women who were disease- free and did not have a recurrence. Purpose of the Study

18. The Five Proteins Par-4: pro-apoptotic tumor suppressor protein downregulated during breast cancer recurrence Wnt/  -catenin: signaling pathway induces epithelial-mesenchymal transition (EMT) and promotes metastasis SNAIL, TWIST: transcription factors, promote EMT promote cancer progression (metastasis) elevated in metastatic and recurrent tumors c-Abl, Arg: tyrosine kinases, oncoproteins promote survival, proliferation, and metastasis activity levels measured by pCrkL activity

19. A Retrospective Cohort Study Identify the study Population Did Not Recur Recurred Tissue at the time of recurrence Using the Registry, all female breast cancer patients treated surgically between 2000 and 2007 at UK for their 1 st Ca. and determined to be disease free were identified. Tissue blocks from the initial surgery were obtained for all of these patients, TMAs were constructed and stained to determine activity levels for each protein. This cohort was then traced forward in time to determine which patients recurred and which did not. (479 patients met the study criteria). Comparisons were made between activity levels of each protein among the primary tumors of recurrent patients (62) and the non-recurrent patients (417). For patients that recurred, comparisons were made between the tumor tissue at first surgery (the primary tumor) and the tissue taken at the time of recurrence. Tissue at the time of recurrence was only available for 22 patients. 2000-20072012

20. TWISTSNAILPAR4  -catenin pCrkL IntensityHER2+ (n=36) HER2-/ER+/PR+ (n=282) H L HER2-/ER-/PR+ (n=32) HER2-/ER-/PR- (n=75) Allred ScoreHER2+ HER2-/ER+/PR+ H L HER2-/ER-/PR+ HER2-/ER-/PR- Intensity X PercentHER2+ HER2-/ER+/PR+ H L HER2-/ER-/PR+ HER2-/ER-/PR- H: Significantly high in the primary tumor of recurrent patients L: Significantly low in the primary tumor of recurrent patients PROTEIN EXPRESSION IN PRIMARY TUMORS FROM RECURRENT VS. NON-RECURRENT PATIENTS Preliminary Results

21. TWISTSNAILPAR4  -CATENIN pCrkL Intensity H Allred Score H Intensity x Percentage H H: Significantly high at the time of recurrence in the tissue sample of patient who recurred compared to their primary tumors PROTEIN EXPRESSION IN RECURRENT VS. PRIMARY TUMORS Preliminary Results

22. pCrkL EXPRESSION IN RECURRENT VS. PRIMARY TUMORS Preliminary Results

23. Conclusions Elevated levels of Twist, and low or not activated c-Abl/Arg (pCrkL) in HER2 - /ER + /PR + breast tumors may potentially serve as a novel biomarker for the recurrence of breast cancer. c-Abl/Arg was activated and over expressed in the tumors of patients at the time of recurrence. Inhibiting c-Abl/Arg activation may potentially prevent recurrence. It is difficult to imagine doing this study without using the Cancer Registry as a virtual tissue repository.

24. 2. Pre-Invasive Cervical Cancer HPV Genotyping Study: Research Questions Are the HPV genotypes different for non-Appalachian white women diagnosed with pre-invasive cervical cancer (CIN-3) compared to Appalachian white women? Are the HPV genotypes different for non-Appalachian white women diagnosed with pre-invasive cervical cancer (CIN-3) compared to non-Appalachian black women? Are the HPV genotypes different for white women diagnosed with CIN-3 compared to white women diagnosed with AIS?

25. Study Population All Kentucky women age 18 or older diagnosed with CIN-3 or AIS between January 1, 2009 and December 31, 2012 were available for this study. The cases were divided into four strata (non-Appalachian white women, non-Appalachian black women, Appalachian white women and AIS cases). A total of 4903 pre-invasive cervical cancer cases fell into one of these strata. 3099 were non-Appalachian white women diagnosed with CIN-3. 290 were non-Appalachian black women diagnosed with CIN-3. 1360 were Appalachian white women diagnosed with CIN-3. 154 were white women diagnosed with AIS. The recruitment goal was to obtain tissue specimens from a random sample of 150 cases in each strata (for a total of 600 cases). A random sample of 200 cases was drawn from each strata except AIS to allow replacement for cases for which tissue could not be obtained.

26. Study Procedures The Kentucky Cancer Registry (KCR) served as the “Honest Broker” for this study. KCR solicited the required tissue blocks from each of 48 the labs where the tissue was stored. Tissue blocks were sent directly to KCR, the blocks were anonymized and given a unique code. The coded blocks were cut by the Markey Cancer Center, Biospecimens and Tissue Procurement Research Lab and the tissue specimens sent to CDC for genotyping. The original blocks were returned to the contributing lab by KCR. All of the HPV genotyping was done at CDC. The HPV genotype or types for each specimen and the associated unique code were then returned to KCR and linked with other data in the pre- invasive cervical cancer surveillance database to create a research data set.

27. Pre-Invasive Cervical Cancer HPV Genotyping Study: # and % of Cases Currently Available for Analysis GroupingsFrequency + (% of 421) Available for study421 (100%) Appalachian white121 (28.7%) Non-Appal white113 (26.8%) Non-Appal black105 (24.9%) AIS white82(19.5%)

28. Pre-Invasive Cervical Cancer HPV Genotyping Study: Research Question 1 Are HPV genotypes different for Appalachian white vs non-Appalachian white females? HPV Genotype Region% with genotype p-value Any oncogenic HPV Appalachian22%0.0588 except 16 & 18Non-Appalachian34%

29. Pre-Invasive Cervical Cancer HPV Genotyping Study: Research Question 2 Are HPV genotypes different for non-Appalachian white vs non-Appalachian black females? HPV Genotype RACE% with genotypep-value 16 (alone or White61.1%0.0208 with any other HPV)Black44.8% 16 alone White46.9%0.0120 Black29.5% 35 (alone or White2.7%0.0043 with any other HPV)Black13.3% 35 alone White1.8%0.0158 Black9.5% Any oncogenic HPVWhite33.6%0.0539 except 16 & 18Black46.7%

30. Pre-Invasive Cervical Cancer HPV Genotyping Study: Research Question 3 Are HPV genotypes different for white females with CIN-3 vs white females with AIS? HPV GenotypeCIN-3 Vs. AIS% with genotypep-value 18 (alone or CIN-33.0%<0.0001 with any other HPV)AIS39.0% 18 aloneCIN-31.7%<0.0001 AIS32.9% 31 (alone or CIN-310.3%0.001 with any other HPV)AIS0.0% 31 aloneCIN-37.3%0.0084 AIS0.0% 52 (alone orCIN-36.8%0.0829 with any other HPV)AIS1.2% 52 aloneCIN-33.4%0.1177 AIS0.0% 33 (alone orCIN-30.0%0.0689 with any other HPV)AIS4.3%

31. Preliminary Conclusions HPV oncogenic types other than 16 and 18 were more common among non-Appalachian white women diagnosed with CIN-3 compared to Appalachian white women HPV 16 alone or with any other HPV type was more common among white women diagnosed with CIN-3 compared to black women. HPV 35 alone or with any other HPV type was more common among black women diagnosed with CIN-3 compared to white women. HPV 18 alone or with any other HPV type was more common among white women diagnosed with AIS compared to white women diagnosed with CIN-3.

32. The final step in translational research is the broad based implementation of cancer research findings in the genral population and measuring the impact of these interventions.

33. From the Laboratory to the Population GenesCellsAnimalsHumansPopulations Basic Science Clinical Science Epidemiology Translational Research

34. EXAMPLE Quercitrin, a natural product from apple peel, is tested in an animal model to determine if it prevents UV exposure induced skin cancer Randomized trials in human populations Broad application of the findings to the general population

35. From the Population to the Laboratory GenesCellsAnimalsHumansPopulations Basic Science Clinical Science Epidemiology And back again Translational Research

36. Example Epidemiologic studies show that colorectal cancer is excessively high in the Appalachian area of Kentucky and this same population has high exposure to arsenic and chromium. Cell line and animal studies are conducted to determine if exposure to arsenic and chromium contributes to the onset of colon cancer.

38. Example Cell line and animal studies are conducted to determine if exposure to arsenic and chromium contributes to the onset of colon cancer. Human trials Epidemiologic studies show that colorectal cancer is excessively high in the Appalachian area of Kentucky and this same population has high exposure to arsenic and chromium.

39. From the Laboratory or the Population GenesCellsAnimalsHumans Populations Basic Science Clinical Science Epidemiology Translational Research

40. The ultimate goal of translational cancer research is the adoption and wide-spread use of evidence- based research findings that significantly reduce the cancer burden in the population. This includes the wide-spread implementation of evidence-based cancer control interventions.

41. The Kentucky Model for Moving Evidence-based Cancer Research Findings into to the Population Kentucky Cancer Registry (KCR) Kentucky Cancer Program (KCP)Kentucky Cancer Consortium (KCC) Lung Cancer by Area Development District in KY, 2005-2009 Area Development District High School Education 2006- 2010 Current Smokers 2001-2005 Age- Adjusted Incidence Age- Adjusted Mortality Overall Rank PercentRankPercentRankRateRankRateRank Kentucky River65.6135.71124.7299.815 Big Sandy69.0335.52131.7196.228 Cumberland Valley67.8235.53117.2386.0311 Gateway73.7632.06102.1679.9422 Buffalo Trace73.3533.0496.91178.3525 Barren River78.6831.87105.8478.0625 Lake Cumberland70.9431.110101.2777.7728 Fivco78.2732.5599.9871.01030 Green River83.01130.311105.0576.1835 Pennyrile80.1931.3897.21070.11138 Lincoln Trail82.71031.1996.31266.41546 Purchase83.01228.51497.7969.41247 Northern Kentucky86.41529.01296.21371.4949 Kipda86.41428.61394.91466.61455 Bluegrass84.71328.21592.61568.01356

42. Source: Kentucky Cancer Registry (KCR)

44. Demographic Characteristics Contribute to Risk Factors Contribute to Incidence and Late Stage DX Contribute to Cancer Mortality Combining Data from Multiple Sources Logic Model

45. What are the common sources of data that can be used for defining the cancer burden? Demographic data (Census U.S) Risk factor data (BRFSS) Incidence data (KCR) Mortality data (State Vital Records)

46. Lung Cancer by Area Development District in KY, 2006-2010 Area Development District High School Education (%) 2006-2010 Poverty Rate (%) 2006- 2010 Smoking Rate (%) 2001- 2005 Age-Adjusted Incidence Late Stage Incidence % Age-Adjusted Mortality NumberRateNumberRate U.S. 87.615.1 19.96292,49567.079.7229,10352.5 Kentucky81.017.430.423077100.580.71670173.2 Barren River78.619.131.81569105.883.1114878.0 Big Sandy69.025.235.51155131.782.983596.2 Bluegrass84.716.928.2344992.681.1251068.0 Buffalo Trace73.322.433.032196.980.525678.3 Cumberland Valley 67.828.735.51590117.281.6115386.0 Fivco78.219.532.586699.979.161371.0 Gateway73.725.232.0442102.179.534279.9 Green River83.015.530.31284105.080.293376.1 Kentucky River65.629.235.7840124.784.465899.8 Kipda86.414.328.6460294.977.9322366.6 Lake Cumberland 70.924.331.11295101.280.299277.7 Lincoln Trail82.714.831.1129196.379.887366.4 Northern Kentucky 86.411.429.0192196.280.8141371.4 Pennyrile80.118.531.3122097.283.587370.1 Purchase83.016.328.5123297.781.287969.4

50. Lung Cancer by Area Development District in KY, 2006-2010 Area Development District High School Education, 2006-2010 Current Smoker, 2001-2005 Age- Adjusted Incidence Age- Adjusted Mortality Overall Rank PercentRankPercentRankRateRankRateRank Kentucky River65.6135.71124.7299.815 Big Sandy69.0335.52131.7196.228 Cumberland Valley 67.8235.53117.2386.0311 Gateway73.7632.06102.1679.9422 Buffalo Trace73.3533.0496.91178.3525 Barren River78.6831.87105.8478.0625 Lake Cumberland70.9431.110101.2777.7728 Fivco78.2732.5599.9871.01030 Green River83.01130.311105.0576.1835 Pennyrile80.1931.3897.21070.11138 Lincoln Trail82.71031.1996.31266.41546 Purchase83.01228.51497.7969.41247 Northern Kentucky 86.41529.01296.21371.4949 Kipda86.41428.61394.91466.61455 Bluegrass84.71328.21592.61568.01356

51. An Example In 2001, Kentucky had the highest colorectal cancer incidence rate in the U.S. compared to all of the other states

52. In 2001, it was also noted that Kentucky was ranked 49 th in colorectal cancer screening compared to all other states with the second to the lowest rate (34.7% of the age eligible population).

53. Using the process previously described, data about the burden of colorectal cancer was assembled and presented to each of the 15 District Cancer Councils. Following these presentations, all 15 of the District Cancer Councils implemented evidence based cancer control intervention programs aimed at increasing colorectal cancer screening for age eligible people living in their District. What happened following the implementation of these colorectal cancer screening programs?

54. Source: http://cdc.gov/brfss accessed August 2014http://cdc.gov/brfss

55. P<.05 Source: http://cancer-rates.info/ky, Accessed January 2014http://cancer-rates.info/ky

56. P<.05 Source: http://cancer-rates.info/ky, Accessed January 2014http://cancer-rates.info/ky

57. A 24% reduction in colorectal cancer incidence and a 28% reduction in colorectal cancer mortality is a significant public health success. It is important to note that we would not have seen this problem without data from our population-based Cancer Registry and we could not have measured the impact of our interventions without data from our population-based Cancer Registry

58. Thank You! Questions? Kentucky Cancer Registry