Background While a definitive genetic test for Hereditary Prostate Cancer (HPC) is not yet available, future HPC risk testing may become available. Past survey data have shown high interest in HPC testing, but without an in-depth analysis of its underlying rationale to those considering it.
Background
While a definitive genetic test for Hereditary Prostate Cancer (HPC) is not yet available, future HPC risk testing may become available. Past survey data have shown high interest in HPC testing, but without an in-depth analysis of its underlying rationale to those considering it.Methods Telephone computer-assisted interviews of 400 men were conducted in a large metropolitan East-coast city, with subsequent development of psychometric scales and their correlation with intention to receive testing.
Methods
Telephone computer-assisted interviews of 400 men were conducted in a large metropolitan East-coast city, with subsequent development of psychometric scales and their correlation with intention to receive testing.Results Approximately 82% of men interviewed expressed that they "probably" or "definitely" would get genetic testing for prostate cancer risk if offered now. Factor analysis revealed four distinct, meaningful factors for intention to receive genetic testing for prostate cancer risk. These factors reflected attitudes toward testing and were labeled "motivation to get testing," "consequences and actions after knowing the test result," "psychological distress," and "beliefs of favorable outcomes if tested" (α = 0.89, 0.73, 0.73, and 0.60, respectively). These factors accounted for 70% of the total variability. The domains of motivation (directly), consequences (inversely), distress (inversely), and positive expectations (directly) all correlated with intention to receive genetic testing (p < 0.001).
Results
Approximately 82% of men interviewed expressed that they "probably" or "definitely" would get genetic testing for prostate cancer risk if offered now. Factor analysis revealed four distinct, meaningful factors for intention to receive genetic testing for prostate cancer risk. These factors reflected attitudes toward testing and were labeled "motivation to get testing," "consequences and actions after knowing the test result," "psychological distress," and "beliefs of favorable outcomes if tested" (α = 0.89, 0.73, 0.73, and 0.60, respectively). These factors accounted for 70% of the total variability. The domains of motivation (directly), consequences (inversely), distress (inversely), and positive expectations (directly) all correlated with intention to receive genetic testing (p < 0.001).Conclusions Men have strong attitudes favoring genetic testing for prostate cancer risk. The factors most associated with testing intention include those noted in past cancer genetics studies, and also highlights the relevance in considering one's motivation and perception of positive outcomes in genetic decision-making.
Conclusions
Men have strong attitudes favoring genetic testing for prostate cancer risk. The factors most associated with testing intention include those noted in past cancer genetics studies, and also highlights the relevance in considering one's motivation and perception of positive outcomes in genetic decision-making.

Background There are several factors to consider in undergoing genetic testing for cancer risk: potential benefits, possible risks, psychological distress, and the uncertainty in subsequent decision-making about prophylactic interventions [ 1 - 9 ]. While the health professional's assessment of the potential benefits and harms frames the disclosure of informed consent, the patients' values and expectations are intrinsic on the decision-making process. Current understanding of these values and expectations has been primarily derived from patients considering genetic testing for breast and colorectal cancers [ 10 ]. It remains unclear how these same factors may influence men's decision making in testing for hereditary prostate cancer risk [ 2 ]. The question addressed in this article is what values and expectations influence the intention of men to undergo genetic testing for prostate cancer risk. A definitive genetic test for prostate cancer is not clinically available yet. Current genetic tests are only conducted in research studies. Several potential genetic loci have been identified as linked to hereditary prostate cancer, including HPC1 [ 11 ], MXI1, KAI1, [ 12 ] and 1q42.2-q43 on chromosome 1q. In the future, a test (or set of tests) for hereditary prostate cancer risk may become available. Such testing may become an important tool in preventing prostate cancer, or be useful once prostate cancer is diagnosed (e.g., for treatment decisions). Further, it is prudent for physicians to be prepared for patient requests for genetic testing, even when there are no strong clinical indications. Learning why men would accept or refuse prostate cancer genetic risk information is therefore relevant to the future of testing, and its informed consent. Informed consent for genetic testing for cancer risk is particularly controversial in cancers where knowledge of a positive test result does not provide opportunities for interventions for favorable outcomes, and a negative result does not provide reassurance [ 13 ]. High stated intention for genetic testing for prostate cancer risk (over 80%) has been reported in the past [ 14 ]. Identification of a man at genetic risk for prostate cancer presents an ambiguous dilemma: Should a positive result be followed by prophylactic surgery, medication, increased surveillance (via PSA testing or rectal examination), or standard screening recommendations? The knowledge gained through genetic screening may not necessarily lead to clear cut recommendations about what the patient should do next. This study examines men's beliefs and values toward interest in prostate cancer genetic testing. A survey instrument was developed for men between 40 and 70 years of age, exploring their beliefs, attitudes, and concerns in considering a hypothetical blood test. Exploratory factor analysis was applied to identify the underlying factor dimensions. The relative importance of these factors was then compared to testing intention.
Background
There are several factors to consider in undergoing genetic testing for cancer risk: potential benefits, possible risks, psychological distress, and the uncertainty in subsequent decision-making about prophylactic interventions [ 1 - 9 ]. While the health professional's assessment of the potential benefits and harms frames the disclosure of informed consent, the patients' values and expectations are intrinsic on the decision-making process. Current understanding of these values and expectations has been primarily derived from patients considering genetic testing for breast and colorectal cancers [ 10 ]. It remains unclear how these same factors may influence men's decision making in testing for hereditary prostate cancer risk [ 2 ]. The question addressed in this article is what values and expectations influence the intention of men to undergo genetic testing for prostate cancer risk.A definitive genetic test for prostate cancer is not clinically available yet. Current genetic tests are only conducted in research studies. Several potential genetic loci have been identified as linked to hereditary prostate cancer, including HPC1 [ 11 ], MXI1, KAI1, [ 12 ] and 1q42.2-q43 on chromosome 1q. In the future, a test (or set of tests) for hereditary prostate cancer risk may become available. Such testing may become an important tool in preventing prostate cancer, or be useful once prostate cancer is diagnosed (e.g., for treatment decisions). Further, it is prudent for physicians to be prepared for patient requests for genetic testing, even when there are no strong clinical indications. Learning why men would accept or refuse prostate cancer genetic risk information is therefore relevant to the future of testing, and its informed consent.Informed consent for genetic testing for cancer risk is particularly controversial in cancers where knowledge of a positive test result does not provide opportunities for interventions for favorable outcomes, and a negative result does not provide reassurance [ 13 ]. High stated intention for genetic testing for prostate cancer risk (over 80%) has been reported in the past [ 14 ]. Identification of a man at genetic risk for prostate cancer presents an ambiguous dilemma: Should a positive result be followed by prophylactic surgery, medication, increased surveillance (via PSA testing or rectal examination), or standard screening recommendations? The knowledge gained through genetic screening may not necessarily lead to clear cut recommendations about what the patient should do next.This study examines men's beliefs and values toward interest in prostate cancer genetic testing. A survey instrument was developed for men between 40 and 70 years of age, exploring their beliefs, attitudes, and concerns in considering a hypothetical blood test. Exploratory factor analysis was applied to identify the underlying factor dimensions. The relative importance of these factors was then compared to testing intention.Methods Study population The Institutional Review Board (I.R.B.) of the University of Pennsylvania and US Department of Defense Human Subjects Review approved the study. Subjects for this study included healthy outpatient males, identified with the assistance of the institution's Office of Health Services Research for demographic characteristics of age, ethnicity, and absence of past or current history of prostate cancer. Subjects were sent a letter-invitation to participate with an opt-out telephone number to call. Inclusion criteria were that subjects must be English-speaking men in a large metropolitan East-coast city, between the ages of 40 and 70, with no current evident mental incapacity and no present or past personal history of prostate cancer. All others were excluded. Prostate cancer genetic screening survey questionnaire Survey development A 53-item attitude survey instrument was developed. The items were selected by the collaborators from a pool of more than 100 preliminary items from the data resulting from 12 focus groups of 90 lay men regarding their attitude, beliefs, and concerns about prostate cancer genetic screening [ 15 ]. The statements were answered on a 1–5 Likert-type scale ("Strongly Disagree" = 1, "Disagree" = 2, "Neutral" = 3, "Agree" = 4, and "Strongly Agree" = 5). Twenty-one items were reverse phrased to counter balance directionality in the response scale. Items 1, 51, 52, and 53 were intent items: "I would want the genetic test for prostate cancer risk when it becomes available," "I would want this test if it could tell me that prostate cancer is more likely to happen earlier in my life," "I would want this test if it could tell me that prostate cancer is more likely to be more life threatening because I have the prostate cancer risk gene," and "I would want this test even if it does not tell me new information about how early or aggressive prostate cancer may be in my future," respectively. Telephone interview The survey was conducted using Computer-Assisted Telephone Interviewing software (MacCATI, Senecio Software). The survey instrument was pilot tested in face-to-face interviews of randomly selected men, age 40–70, in a primary care office prior to data collection, to verify understandability of the survey's content and format. For the telephone survey, a recruitment packet that included an informed consent letter was first mailed to the prospective participants. Instructions explained the goals of the study and gave them an option to opt-out with a toll-free phone call prior to their interview. An oral informed consent was completed prior to the telephone interview. Missing data The number of missing observations ranged from 0 to 13, with an average of 2.38. Missing data were imputed based on an imputation model that predicts the missing values of factors as predicted by all of the other responses, including the outcome (desire to be tested). The algorithm uses Markov Chain Monte Carlo methods to select at random a value from the distribution of the possible values predicted by the missing value model. This method differs in several respects from other methods of filling in for missing data, in that with each imputation a different value will be imputed for the missing value, thus ensuring an added dimension of variability in the resulting analyses. The imputation was repeated multiple times. Each imputation generated an imputed data set. The same factor analysis was applied and no statistically reliable differences were found across the imputed data sets. Thus, only the results from the first imputed data are reported here. The imputation was carried out by SAS PROC MI. Factor analysis and reliability statistics A maximum-likelihood factor analysis with oblique rotation was applied to the 49 non-intent questions to classify men's non-intent beliefs and attitudes according to their underlying dimensions. The four questions that directly probed men's expressed intent were considered  a priori  as a separate factor. The factor analysis involved methodological criteria for data reduction, which included the rules summarized in Tabachnick [ 16 ]. Items with factor pattern loading lower than .40 were dropped (less than 16% overlapping variance between the item and the associated factor). The most salient dimensions were then retained, accounting for at least 70% of the total variability. The internal consistency reliability was assessed by Cronbach's alpha coefficient [ 17 ]. Items that showed the highest factor pattern loadings for a particular factor were considered items that measure the attitude associated with that dimension [ 18 ]. Factor scores, with estimated scores on each of the individual factors had they been measured directly, were also derived by summing the raw scores of the items [ 19 ].
Methods
Study population The Institutional Review Board (I.R.B.) of the University of Pennsylvania and US Department of Defense Human Subjects Review approved the study. Subjects for this study included healthy outpatient males, identified with the assistance of the institution's Office of Health Services Research for demographic characteristics of age, ethnicity, and absence of past or current history of prostate cancer. Subjects were sent a letter-invitation to participate with an opt-out telephone number to call. Inclusion criteria were that subjects must be English-speaking men in a large metropolitan East-coast city, between the ages of 40 and 70, with no current evident mental incapacity and no present or past personal history of prostate cancer. All others were excluded.
Study population
The Institutional Review Board (I.R.B.) of the University of Pennsylvania and US Department of Defense Human Subjects Review approved the study. Subjects for this study included healthy outpatient males, identified with the assistance of the institution's Office of Health Services Research for demographic characteristics of age, ethnicity, and absence of past or current history of prostate cancer. Subjects were sent a letter-invitation to participate with an opt-out telephone number to call. Inclusion criteria were that subjects must be English-speaking men in a large metropolitan East-coast city, between the ages of 40 and 70, with no current evident mental incapacity and no present or past personal history of prostate cancer. All others were excluded.Prostate cancer genetic screening survey questionnaire Survey development A 53-item attitude survey instrument was developed. The items were selected by the collaborators from a pool of more than 100 preliminary items from the data resulting from 12 focus groups of 90 lay men regarding their attitude, beliefs, and concerns about prostate cancer genetic screening [ 15 ]. The statements were answered on a 1–5 Likert-type scale ("Strongly Disagree" = 1, "Disagree" = 2, "Neutral" = 3, "Agree" = 4, and "Strongly Agree" = 5). Twenty-one items were reverse phrased to counter balance directionality in the response scale. Items 1, 51, 52, and 53 were intent items: "I would want the genetic test for prostate cancer risk when it becomes available," "I would want this test if it could tell me that prostate cancer is more likely to happen earlier in my life," "I would want this test if it could tell me that prostate cancer is more likely to be more life threatening because I have the prostate cancer risk gene," and "I would want this test even if it does not tell me new information about how early or aggressive prostate cancer may be in my future," respectively.
Prostate cancer genetic screening survey questionnaire
Survey development A 53-item attitude survey instrument was developed. The items were selected by the collaborators from a pool of more than 100 preliminary items from the data resulting from 12 focus groups of 90 lay men regarding their attitude, beliefs, and concerns about prostate cancer genetic screening [ 15 ]. The statements were answered on a 1–5 Likert-type scale ("Strongly Disagree" = 1, "Disagree" = 2, "Neutral" = 3, "Agree" = 4, and "Strongly Agree" = 5). Twenty-one items were reverse phrased to counter balance directionality in the response scale. Items 1, 51, 52, and 53 were intent items: "I would want the genetic test for prostate cancer risk when it becomes available," "I would want this test if it could tell me that prostate cancer is more likely to happen earlier in my life," "I would want this test if it could tell me that prostate cancer is more likely to be more life threatening because I have the prostate cancer risk gene," and "I would want this test even if it does not tell me new information about how early or aggressive prostate cancer may be in my future," respectively.
Survey development
A 53-item attitude survey instrument was developed. The items were selected by the collaborators from a pool of more than 100 preliminary items from the data resulting from 12 focus groups of 90 lay men regarding their attitude, beliefs, and concerns about prostate cancer genetic screening [ 15 ]. The statements were answered on a 1–5 Likert-type scale ("Strongly Disagree" = 1, "Disagree" = 2, "Neutral" = 3, "Agree" = 4, and "Strongly Agree" = 5). Twenty-one items were reverse phrased to counter balance directionality in the response scale. Items 1, 51, 52, and 53 were intent items: "I would want the genetic test for prostate cancer risk when it becomes available," "I would want this test if it could tell me that prostate cancer is more likely to happen earlier in my life," "I would want this test if it could tell me that prostate cancer is more likely to be more life threatening because I have the prostate cancer risk gene," and "I would want this test even if it does not tell me new information about how early or aggressive prostate cancer may be in my future," respectively.Telephone interview The survey was conducted using Computer-Assisted Telephone Interviewing software (MacCATI, Senecio Software). The survey instrument was pilot tested in face-to-face interviews of randomly selected men, age 40–70, in a primary care office prior to data collection, to verify understandability of the survey's content and format. For the telephone survey, a recruitment packet that included an informed consent letter was first mailed to the prospective participants. Instructions explained the goals of the study and gave them an option to opt-out with a toll-free phone call prior to their interview. An oral informed consent was completed prior to the telephone interview.
Telephone interview
The survey was conducted using Computer-Assisted Telephone Interviewing software (MacCATI, Senecio Software). The survey instrument was pilot tested in face-to-face interviews of randomly selected men, age 40–70, in a primary care office prior to data collection, to verify understandability of the survey's content and format. For the telephone survey, a recruitment packet that included an informed consent letter was first mailed to the prospective participants. Instructions explained the goals of the study and gave them an option to opt-out with a toll-free phone call prior to their interview. An oral informed consent was completed prior to the telephone interview.Missing data The number of missing observations ranged from 0 to 13, with an average of 2.38. Missing data were imputed based on an imputation model that predicts the missing values of factors as predicted by all of the other responses, including the outcome (desire to be tested). The algorithm uses Markov Chain Monte Carlo methods to select at random a value from the distribution of the possible values predicted by the missing value model. This method differs in several respects from other methods of filling in for missing data, in that with each imputation a different value will be imputed for the missing value, thus ensuring an added dimension of variability in the resulting analyses. The imputation was repeated multiple times. Each imputation generated an imputed data set. The same factor analysis was applied and no statistically reliable differences were found across the imputed data sets. Thus, only the results from the first imputed data are reported here. The imputation was carried out by SAS PROC MI.
Missing data
The number of missing observations ranged from 0 to 13, with an average of 2.38. Missing data were imputed based on an imputation model that predicts the missing values of factors as predicted by all of the other responses, including the outcome (desire to be tested). The algorithm uses Markov Chain Monte Carlo methods to select at random a value from the distribution of the possible values predicted by the missing value model. This method differs in several respects from other methods of filling in for missing data, in that with each imputation a different value will be imputed for the missing value, thus ensuring an added dimension of variability in the resulting analyses. The imputation was repeated multiple times. Each imputation generated an imputed data set. The same factor analysis was applied and no statistically reliable differences were found across the imputed data sets. Thus, only the results from the first imputed data are reported here. The imputation was carried out by SAS PROC MI.Factor analysis and reliability statistics A maximum-likelihood factor analysis with oblique rotation was applied to the 49 non-intent questions to classify men's non-intent beliefs and attitudes according to their underlying dimensions. The four questions that directly probed men's expressed intent were considered  a priori  as a separate factor. The factor analysis involved methodological criteria for data reduction, which included the rules summarized in Tabachnick [ 16 ]. Items with factor pattern loading lower than .40 were dropped (less than 16% overlapping variance between the item and the associated factor). The most salient dimensions were then retained, accounting for at least 70% of the total variability. The internal consistency reliability was assessed by Cronbach's alpha coefficient [ 17 ]. Items that showed the highest factor pattern loadings for a particular factor were considered items that measure the attitude associated with that dimension [ 18 ]. Factor scores, with estimated scores on each of the individual factors had they been measured directly, were also derived by summing the raw scores of the items [ 19 ].
Factor analysis and reliability statistics
A maximum-likelihood factor analysis with oblique rotation was applied to the 49 non-intent questions to classify men's non-intent beliefs and attitudes according to their underlying dimensions. The four questions that directly probed men's expressed intent were considered  a priori  as a separate factor. The factor analysis involved methodological criteria for data reduction, which included the rules summarized in Tabachnick [ 16 ]. Items with factor pattern loading lower than .40 were dropped (less than 16% overlapping variance between the item and the associated factor). The most salient dimensions were then retained, accounting for at least 70% of the total variability. The internal consistency reliability was assessed by Cronbach's alpha coefficient [ 17 ]. Items that showed the highest factor pattern loadings for a particular factor were considered items that measure the attitude associated with that dimension [ 18 ]. Factor scores, with estimated scores on each of the individual factors had they been measured directly, were also derived by summing the raw scores of the items [ 19 ].a prioriResults Demographics Interviews were completed with 400 respondents with a cooperation rate of 47% (1675 were contacted, 431 refused to participate either by phone prior to the interview, or at the time of the interview, and 844 were excluded due to no answer, disconnected telephones, and death). Table  1  summarizes the respondents' characteristics. Of note, another study by the authors revealed that no demographic factor had a moderating impact on intention, except one – in which higher levels of education correlated with diminished testing intention [ 20 ]. IRB constraints precluded non-respondent data collection for comparison. Table 1 Respondent characteristics Characteristics N (N = 400) % Ethnicity  White 288 72  Black 87 22  Hispanic 5 1  Asian 8 2  Other 6 2  No response 6 2 Age  40–49 133 33  50–59 143 36  60–69 124 31 Education  < High school 86 22  High school graduate/some college 149 37  College graduate 141 35  Post-graduate degree 23 6  No response 1 0 Annual household income  $15,000 or less 17 4  $15,001 – $45,000 74 19  $45,000 – 75,000 84 22  $75,000 – $105,000 90 23  More than $105,000 107 28  No response 28 7 Marital status  Married 319 80  Steady relationship but not married 23 6  Separated or divorced 26 7  Single 25 6  Widowed 7 2 Testing intention About 82% of men interviewed expressed that they "probably" or "definitely" would take the test if one were offered now. This high interest increased to 88% if a positive test result indicates elevated risk in the early onset of cancer; 93% if it indicates graver prognosis of cancer; and the stated interest dropped to a still appreciable 68% if  no new information  on timing or severity of prostate cancer is to be learned from the prospective test. Subscales Exploratory factor analysis identified four underlying factors that accounted for 76% of the total variability among the 49 items probing men's beliefs and attitudes. The four factors were 1)  Motivation , i.e., those values relating how strongly the respondent wanted the test, and how strongly the opinions of professionals, spouse, family, relatives, and friends could have influenced the respondent's own strength of intent; 2)  Consequences , which measured beliefs with respect to follow-up decision-making and management; 3)  Distress , which assessed fear of losing health and life insurance, anxiety, and worsening of quality of life if tested positive; and 4)  Positive Expectations , which described beliefs in how the test results will confer useful information in family risk and favorable outcomes. The four intent items were added separately as the fifth subscale 5)  Intention  directly probing the respondent's stated intent. Table  2  summarizes the subscales, their respective internal consistency, and the factor loadings of their constituent items. Table 2 Subscales, internal consistency, and factor item loadings Factors / statements (internal consistency statistics) Factor pattern loading Motivation Subscale 1: Motivation (alpha = 0.89, 37% variability)  Even if other relatives did not want me to, I would get genetic testing. 0.80  Even if my children did not want me to, I would get genetic testing. 0.77  I would get genetic testing if my friends wanted me to. 0.73  Even if my friends did not want me to, I would get genetic testing. 0.72  I would get testing if other relatives wanted me to. 0.68  Even if my wife or partner did not want me to, I would get genetic testing. 0.68  Even if a genetic testing specialist recommended against it, I would get genetic testing. 0.60  I would get testing if my children wanted me to. 0.59  Even if my doctor recommended against it, I would get genetic testing. 0.57  I would get testing if a genetic testing specialist recommended it. 0.46  I would get testing if my wife or partner wanted me to. 0.43 Consequences Subscale 2: Consequences and actions after knowing the test result (alpha = 0.73, 23% variability)  I find that my concerns about getting prostate cancer interfere with my every day life. [R] 0.56  I don't want testing unless there is a prostate cancer cure. [R] 0.54  If I know I have the prostate cancer risk gene, it will make me feel guilty. [R] 0.53  I'll have to make a quick treatment decision if I know I have the prostate cancer risk gene. [R] 0.52  If I know I have the prostate cancer risk gene, I will make me want to end my life. [R] 0.51  If I don't have the prostate cancer risk gene, I will be able to put my mind at rest about prostate cancer. [R] 0.51  I don't want testing unless it can tell me whether I have prostate cancer now. [R] 0.49  I would not want to have children if I know I have the prostate cancer risk gene. [R] 0.44  I would want to put off testing as long as I can. 0.42 Distress Subscale 3: Psychological distress (alpha = 0.73, 10% variability)  I am concerned I will lose or not be able to get LIFE insurance if I get the genetic testing for prostate cancer risk. [R] 0.64  If I know I have the prostate cancer risk gene, it will make me anxious. [R] 0.59  I am concerned I will lose or not be able to get HEALTH insurance if I get the genetic testing for prostate cancer risk. [R] 0.57  If I know I have the prostate cancer risk gene, I will feel worse about myself. [R] 0.46  My life will get worse if I know I have the prostate cancer risk gene. [R] 0.46  If I know I have the prostate cancer risk gene, it will change the way I think about the future. 0.45 Positive expectations Subscale 4: Beliefs in favorable outcomes if tested (alpha = 0.60, 7% variability)  I believe this test could save my life. 0.52  The more I know about my risk for prostate cancer, the better I will feel about testing. 0.51  The test results might provide valuable information on prostate cancer risk to my family members. 0.45  If I know I have the prostate cancer risk gene, my doctor may want to do more tests. 0.42 Intent Subscale 5: Intention (alpha = 0.79)  I would want the genetic test for prostate cancer risk when it becomes available. -  I would want the test if it could tell me that prostate cancer is more likely to happen earlier in my life. -  I would want this test if it could tell me that prostate cancer is more likely to be more life threatening because I have the prostate cancer risk gene. -  I would want this test even if it does not tell me now information about how early or aggressive prostate cancer may be in my future. - [R] – Item reversed in coding for analysis N.B. – Intent items were not included in the factor analysis, thus there are no available data on pattern loadings and variance. The following factors did not load onto the four value-based factor domains, and were omitted from further analysis:  I want to wait on testing until it is shown to be very accurate. I will not be able to keep my job, or get a promotion, if I know I have the prostate cancer risk gene. If I know I have the prostate cancer risk gene, my doctor might pressure me to receive treatment. Nothing can be done to prevent prostate cancer. Changes in my lifestyle can reduce my risk of cancer. I only want my family doctor to do this test for prostate cancer risk. I don't want testing unless I can do something to prevent prostate cancer. The government could use my test results in ways I do not want. I often worry about getting prostate cancer If I know I do not have the prostate cancer risk gene, I won't need rectal exams or PSA tests as often. No matter my results, I would want testing if it helps find a cure. I don't want the test if my health care coverage does not pay for it. I would want to get tested because I just want to know if I have the gene for prostate No one should give out my test results to anyone else without my permission. I would get testing if my doctor recommended it. Overall, the five subscales showed satisfactory internal consistency. The four items within Intention scale, although grouped together  a priori  for their content, showed a good internal consistency alpha coefficient at 0.79. Among the 49 items that probed men's beliefs, values, and attitudes, the 11 items that loaded high on Motivation accounted for most of the variability (37%) with a very high alpha coefficient (0.89). The nine items in Consequences accounted for the next largest amount of variability (23%) with an alpha coefficient of 0.73. The six items in Distress accounted for 10% of the variability with an alpha of 0.73. Finally, the four items in Positive Expectations accounted for 7% of the variability with an alpha of 0.60. The factor pattern loadings reflect the correlation between an individual item and its subscale. For example, Table  2  shows that Motivation is strongly associated with the item "even if other relatives did not want me to, I would get genetic testing." (Loading value = 0.80). Respondents with high motivation tended not to be influenced by other relatives. Importantly, the less one is influenced by a relative's opinion, the more likely he is to be motivated to get testing. Conversely, a man who was easily influenced by his spouse or children was somewhat less likely to be motivated toward testing. This latter set of values may reflect the desire for more information and counsel. The inter-correlations between the subscales are summarized in Table  3 , and reveal how these subscales were associated with one another and how they affected intent. The respondents' motivation (regarding the influence of others in their decision) was positively correlated with intention to test ( r  = 0.69,  p  < 0.001). There was also a positive and statistically significant correlation between one's motivation and one's expectations that genetic screening may lead to favorable outcomes for the gene carrier and his family ( r  = 0.39,  p  < 0.001). Concerns about the consequences of a positive result, including the uncertainties of test validity and accuracy, and the availability of subsequent interventions, were positively correlated with distress ( r  = 0.34,  p  < 0.001) and diminished intention to test ( r  = -0.16,  p  < 0.01). Distress-based values were associated with diminished intention to test ( r  = -0.17,  p  < 0.001). Finally, respondents who expected favorable outcomes were associated with increased intention to test ( r  = 0.48,  p  < 0.001). Table 3 Inter-correlations between subscales Motivation Consequences Distress Positive Expectations Motivation - Consequences -0.08 - Distress -0.19* 0.34* - Positive Expectations 0.39* -0.02 -0.003 - Intention 0.69* -0.16* -0.17* 0.48* * p < 0.001
Results
Demographics Interviews were completed with 400 respondents with a cooperation rate of 47% (1675 were contacted, 431 refused to participate either by phone prior to the interview, or at the time of the interview, and 844 were excluded due to no answer, disconnected telephones, and death). Table  1  summarizes the respondents' characteristics. Of note, another study by the authors revealed that no demographic factor had a moderating impact on intention, except one – in which higher levels of education correlated with diminished testing intention [ 20 ]. IRB constraints precluded non-respondent data collection for comparison. Table 1 Respondent characteristics Characteristics N (N = 400) % Ethnicity  White 288 72  Black 87 22  Hispanic 5 1  Asian 8 2  Other 6 2  No response 6 2 Age  40–49 133 33  50–59 143 36  60–69 124 31 Education  < High school 86 22  High school graduate/some college 149 37  College graduate 141 35  Post-graduate degree 23 6  No response 1 0 Annual household income  $15,000 or less 17 4  $15,001 – $45,000 74 19  $45,000 – 75,000 84 22  $75,000 – $105,000 90 23  More than $105,000 107 28  No response 28 7 Marital status  Married 319 80  Steady relationship but not married 23 6  Separated or divorced 26 7  Single 25 6  Widowed 7 2
Demographics
Interviews were completed with 400 respondents with a cooperation rate of 47% (1675 were contacted, 431 refused to participate either by phone prior to the interview, or at the time of the interview, and 844 were excluded due to no answer, disconnected telephones, and death). Table  1  summarizes the respondents' characteristics. Of note, another study by the authors revealed that no demographic factor had a moderating impact on intention, except one – in which higher levels of education correlated with diminished testing intention [ 20 ]. IRB constraints precluded non-respondent data collection for comparison.Respondent characteristicsTesting intention About 82% of men interviewed expressed that they "probably" or "definitely" would take the test if one were offered now. This high interest increased to 88% if a positive test result indicates elevated risk in the early onset of cancer; 93% if it indicates graver prognosis of cancer; and the stated interest dropped to a still appreciable 68% if  no new information  on timing or severity of prostate cancer is to be learned from the prospective test.
Testing intention
About 82% of men interviewed expressed that they "probably" or "definitely" would take the test if one were offered now. This high interest increased to 88% if a positive test result indicates elevated risk in the early onset of cancer; 93% if it indicates graver prognosis of cancer; and the stated interest dropped to a still appreciable 68% if  no new information  on timing or severity of prostate cancer is to be learned from the prospective test.no new informationSubscales Exploratory factor analysis identified four underlying factors that accounted for 76% of the total variability among the 49 items probing men's beliefs and attitudes. The four factors were 1)  Motivation , i.e., those values relating how strongly the respondent wanted the test, and how strongly the opinions of professionals, spouse, family, relatives, and friends could have influenced the respondent's own strength of intent; 2)  Consequences , which measured beliefs with respect to follow-up decision-making and management; 3)  Distress , which assessed fear of losing health and life insurance, anxiety, and worsening of quality of life if tested positive; and 4)  Positive Expectations , which described beliefs in how the test results will confer useful information in family risk and favorable outcomes. The four intent items were added separately as the fifth subscale 5)  Intention  directly probing the respondent's stated intent. Table  2  summarizes the subscales, their respective internal consistency, and the factor loadings of their constituent items. Table 2 Subscales, internal consistency, and factor item loadings Factors / statements (internal consistency statistics) Factor pattern loading Motivation Subscale 1: Motivation (alpha = 0.89, 37% variability)  Even if other relatives did not want me to, I would get genetic testing. 0.80  Even if my children did not want me to, I would get genetic testing. 0.77  I would get genetic testing if my friends wanted me to. 0.73  Even if my friends did not want me to, I would get genetic testing. 0.72  I would get testing if other relatives wanted me to. 0.68  Even if my wife or partner did not want me to, I would get genetic testing. 0.68  Even if a genetic testing specialist recommended against it, I would get genetic testing. 0.60  I would get testing if my children wanted me to. 0.59  Even if my doctor recommended against it, I would get genetic testing. 0.57  I would get testing if a genetic testing specialist recommended it. 0.46  I would get testing if my wife or partner wanted me to. 0.43 Consequences Subscale 2: Consequences and actions after knowing the test result (alpha = 0.73, 23% variability)  I find that my concerns about getting prostate cancer interfere with my every day life. [R] 0.56  I don't want testing unless there is a prostate cancer cure. [R] 0.54  If I know I have the prostate cancer risk gene, it will make me feel guilty. [R] 0.53  I'll have to make a quick treatment decision if I know I have the prostate cancer risk gene. [R] 0.52  If I know I have the prostate cancer risk gene, I will make me want to end my life. [R] 0.51  If I don't have the prostate cancer risk gene, I will be able to put my mind at rest about prostate cancer. [R] 0.51  I don't want testing unless it can tell me whether I have prostate cancer now. [R] 0.49  I would not want to have children if I know I have the prostate cancer risk gene. [R] 0.44  I would want to put off testing as long as I can. 0.42 Distress Subscale 3: Psychological distress (alpha = 0.73, 10% variability)  I am concerned I will lose or not be able to get LIFE insurance if I get the genetic testing for prostate cancer risk. [R] 0.64  If I know I have the prostate cancer risk gene, it will make me anxious. [R] 0.59  I am concerned I will lose or not be able to get HEALTH insurance if I get the genetic testing for prostate cancer risk. [R] 0.57  If I know I have the prostate cancer risk gene, I will feel worse about myself. [R] 0.46  My life will get worse if I know I have the prostate cancer risk gene. [R] 0.46  If I know I have the prostate cancer risk gene, it will change the way I think about the future. 0.45 Positive expectations Subscale 4: Beliefs in favorable outcomes if tested (alpha = 0.60, 7% variability)  I believe this test could save my life. 0.52  The more I know about my risk for prostate cancer, the better I will feel about testing. 0.51  The test results might provide valuable information on prostate cancer risk to my family members. 0.45  If I know I have the prostate cancer risk gene, my doctor may want to do more tests. 0.42 Intent Subscale 5: Intention (alpha = 0.79)  I would want the genetic test for prostate cancer risk when it becomes available. -  I would want the test if it could tell me that prostate cancer is more likely to happen earlier in my life. -  I would want this test if it could tell me that prostate cancer is more likely to be more life threatening because I have the prostate cancer risk gene. -  I would want this test even if it does not tell me now information about how early or aggressive prostate cancer may be in my future. - [R] – Item reversed in coding for analysis N.B. – Intent items were not included in the factor analysis, thus there are no available data on pattern loadings and variance. The following factors did not load onto the four value-based factor domains, and were omitted from further analysis:  I want to wait on testing until it is shown to be very accurate. I will not be able to keep my job, or get a promotion, if I know I have the prostate cancer risk gene. If I know I have the prostate cancer risk gene, my doctor might pressure me to receive treatment. Nothing can be done to prevent prostate cancer. Changes in my lifestyle can reduce my risk of cancer. I only want my family doctor to do this test for prostate cancer risk. I don't want testing unless I can do something to prevent prostate cancer. The government could use my test results in ways I do not want. I often worry about getting prostate cancer If I know I do not have the prostate cancer risk gene, I won't need rectal exams or PSA tests as often. No matter my results, I would want testing if it helps find a cure. I don't want the test if my health care coverage does not pay for it. I would want to get tested because I just want to know if I have the gene for prostate No one should give out my test results to anyone else without my permission. I would get testing if my doctor recommended it. Overall, the five subscales showed satisfactory internal consistency. The four items within Intention scale, although grouped together  a priori  for their content, showed a good internal consistency alpha coefficient at 0.79. Among the 49 items that probed men's beliefs, values, and attitudes, the 11 items that loaded high on Motivation accounted for most of the variability (37%) with a very high alpha coefficient (0.89). The nine items in Consequences accounted for the next largest amount of variability (23%) with an alpha coefficient of 0.73. The six items in Distress accounted for 10% of the variability with an alpha of 0.73. Finally, the four items in Positive Expectations accounted for 7% of the variability with an alpha of 0.60. The factor pattern loadings reflect the correlation between an individual item and its subscale. For example, Table  2  shows that Motivation is strongly associated with the item "even if other relatives did not want me to, I would get genetic testing." (Loading value = 0.80). Respondents with high motivation tended not to be influenced by other relatives. Importantly, the less one is influenced by a relative's opinion, the more likely he is to be motivated to get testing. Conversely, a man who was easily influenced by his spouse or children was somewhat less likely to be motivated toward testing. This latter set of values may reflect the desire for more information and counsel. The inter-correlations between the subscales are summarized in Table  3 , and reveal how these subscales were associated with one another and how they affected intent. The respondents' motivation (regarding the influence of others in their decision) was positively correlated with intention to test ( r  = 0.69,  p  < 0.001). There was also a positive and statistically significant correlation between one's motivation and one's expectations that genetic screening may lead to favorable outcomes for the gene carrier and his family ( r  = 0.39,  p  < 0.001). Concerns about the consequences of a positive result, including the uncertainties of test validity and accuracy, and the availability of subsequent interventions, were positively correlated with distress ( r  = 0.34,  p  < 0.001) and diminished intention to test ( r  = -0.16,  p  < 0.01). Distress-based values were associated with diminished intention to test ( r  = -0.17,  p  < 0.001). Finally, respondents who expected favorable outcomes were associated with increased intention to test ( r  = 0.48,  p  < 0.001). Table 3 Inter-correlations between subscales Motivation Consequences Distress Positive Expectations Motivation - Consequences -0.08 - Distress -0.19* 0.34* - Positive Expectations 0.39* -0.02 -0.003 - Intention 0.69* -0.16* -0.17* 0.48* * p < 0.001
Subscales
Exploratory factor analysis identified four underlying factors that accounted for 76% of the total variability among the 49 items probing men's beliefs and attitudes. The four factors were 1)  Motivation , i.e., those values relating how strongly the respondent wanted the test, and how strongly the opinions of professionals, spouse, family, relatives, and friends could have influenced the respondent's own strength of intent; 2)  Consequences , which measured beliefs with respect to follow-up decision-making and management; 3)  Distress , which assessed fear of losing health and life insurance, anxiety, and worsening of quality of life if tested positive; and 4)  Positive Expectations , which described beliefs in how the test results will confer useful information in family risk and favorable outcomes. The four intent items were added separately as the fifth subscale 5)  Intention  directly probing the respondent's stated intent. Table  2  summarizes the subscales, their respective internal consistency, and the factor loadings of their constituent items.MotivationConsequencesDistressPositive ExpectationsIntentionSubscales, internal consistency, and factor item loadingsFactors / statements (internal consistency statistics)Factor pattern loadingMotivationConsequencesDistressPositive expectationsIntentThe following factors did not load onto the four value-based factor domains, and were omitted from further analysis:Overall, the five subscales showed satisfactory internal consistency. The four items within Intention scale, although grouped together  a priori  for their content, showed a good internal consistency alpha coefficient at 0.79. Among the 49 items that probed men's beliefs, values, and attitudes, the 11 items that loaded high on Motivation accounted for most of the variability (37%) with a very high alpha coefficient (0.89). The nine items in Consequences accounted for the next largest amount of variability (23%) with an alpha coefficient of 0.73. The six items in Distress accounted for 10% of the variability with an alpha of 0.73. Finally, the four items in Positive Expectations accounted for 7% of the variability with an alpha of 0.60.a prioriThe factor pattern loadings reflect the correlation between an individual item and its subscale. For example, Table  2  shows that Motivation is strongly associated with the item "even if other relatives did not want me to, I would get genetic testing." (Loading value = 0.80). Respondents with high motivation tended not to be influenced by other relatives. Importantly, the less one is influenced by a relative's opinion, the more likely he is to be motivated to get testing. Conversely, a man who was easily influenced by his spouse or children was somewhat less likely to be motivated toward testing. This latter set of values may reflect the desire for more information and counsel.The inter-correlations between the subscales are summarized in Table  3 , and reveal how these subscales were associated with one another and how they affected intent. The respondents' motivation (regarding the influence of others in their decision) was positively correlated with intention to test ( r  = 0.69,  p  < 0.001). There was also a positive and statistically significant correlation between one's motivation and one's expectations that genetic screening may lead to favorable outcomes for the gene carrier and his family ( r  = 0.39,  p  < 0.001). Concerns about the consequences of a positive result, including the uncertainties of test validity and accuracy, and the availability of subsequent interventions, were positively correlated with distress ( r  = 0.34,  p  < 0.001) and diminished intention to test ( r  = -0.16,  p  < 0.01). Distress-based values were associated with diminished intention to test ( r  = -0.17,  p  < 0.001). Finally, respondents who expected favorable outcomes were associated with increased intention to test ( r  = 0.48,  p  < 0.001).rprprprprprpInter-correlations between subscalesMotivationConsequencesDistressPositive Expectations* p < 0.001Discussion These data demonstrate that men in the general public, aged 40 to 70 years without a personal history of prostate cancer, consider prostate cancer genetic testing related to four value-based factor domains, similar to past literature findings on genetic testing for hereditary cancer risk. The motivation factor, which measures values of influence by others, is the strongest decision factor in guiding their opting for the test. More than 80% of men interviewed would consider getting tested if the test was available now. Their stated intention, as measured by the four intent items, is highly correlated with how strongly they feel they are motivated toward the test and inversely related to family influences. Men with strong motivation to get tested also have significantly lower concerns about psychological distress and higher levels of positive expectations. The recommendations of physicians and geneticists are important to men's expressed motivation, although the professionals did not appear to be more influential than their kin. A respondent is more likely to want the test if he believes that the test may be informative of  family risk  and may lead to early identification and prevention of cancer (as part of the Positive Expectations domain). The influences of kin, along with beliefs in family risk, highlight the importance of reviewing family-related risk information as part of genetic consultation and informed consent. Men undergoing informed consent for hereditary prostate cancer risk in the future not only should be provided information on what genetic testing can and cannot do for them, but also what the test results could mean for others surrounding them (as evidenced by the influences of family, etc.). Prior hereditary breast cancer (BRCA) and colorectal cancer (CRC) literature has noted anecdotally that perception of benefit to one's family influences genetic test uptake. Eliciting patient perceptions of concerns regarding their family may be beneficial to consider in oncology genetic testing generally. Similar to this literature, intention was found to be influenced by the respondent's concerns about test validity, test accuracy, and by the availability of interventions that may lead to favorable outcomes. Not surprisingly, men who were concerned about potential psychological distress were less likely to want the test. One unanswered question is how men's anticipatory distress and expected adverse consequences may affect how family risk information is interpreted and discussed. Few men in our study anticipated high levels of distress. Although literature data clearly show elevated distress among patients and their family members [ 21 ]. More research is needed to better establish the family-risk construct and how it may be influenced by other beliefs and values. The present study has limitations. Given the exploratory nature of factor analysis, these data are aimed at identifying coherent subsets of variables for data reduction, not at identifying specific attitude statements that discriminate skeptics from supporters. Nevertheless, the reduced set of 34 items is the most important among the administered 57 items, and comprises a coherent and reliable assessment tool of eliciting values and intention toward testing. This item set can thereby serve as a foundation for a confirmatory health beliefs model, using Structural Equation Modeling techniques to better elucidate the interactions of these value-based domains [ 22 ]. Also, we noted that this population had somewhat higher income and education levels than the overall Philadelphia Consolidated Metropolitan Statistical Area (CMSA). 51% of men had over $75,000 income, compared with the 32% in the Philadelphia CMSA 2000 census year dataset, and 41% had completed a Bachelor's degree or higher, compared with 28% in the CMSA. These differences may be due to affluent subjects living in suburban counties in the metropolitan Philadelphia area, who then self-select to be seen by physicians in the University of Pennsylvania system. As noted above, our prior work demonstrated no demographic differences except education (with more education correlating with diminished intention). Thus, we do not foresee an adverse impact of these discrepancies on the overall outcomes of our analysis [ 20 ]. Future directions of this research may include exploring the relationship between stated intent in prostate cancer genetic screening and actual testing behavior when testing is available. Studies have shown that expressed intention does not necessarily translate to actual behavior in taking genetic tests for breast and colorectal cancers [ 10 , 23 - 29 ]. The same discrepancy between attitude and behavior may exist when a test for prostate cancer is available for the general public. Our data suggest that potential psychological distress, worries about test validity, insurance, confidentiality, and the uncertainties in subsequent intervention decisions may need to be balanced with family considerations when testing becomes available [ 30 ].
Discussion
These data demonstrate that men in the general public, aged 40 to 70 years without a personal history of prostate cancer, consider prostate cancer genetic testing related to four value-based factor domains, similar to past literature findings on genetic testing for hereditary cancer risk. The motivation factor, which measures values of influence by others, is the strongest decision factor in guiding their opting for the test. More than 80% of men interviewed would consider getting tested if the test was available now. Their stated intention, as measured by the four intent items, is highly correlated with how strongly they feel they are motivated toward the test and inversely related to family influences. Men with strong motivation to get tested also have significantly lower concerns about psychological distress and higher levels of positive expectations. The recommendations of physicians and geneticists are important to men's expressed motivation, although the professionals did not appear to be more influential than their kin.A respondent is more likely to want the test if he believes that the test may be informative of  family risk  and may lead to early identification and prevention of cancer (as part of the Positive Expectations domain). The influences of kin, along with beliefs in family risk, highlight the importance of reviewing family-related risk information as part of genetic consultation and informed consent. Men undergoing informed consent for hereditary prostate cancer risk in the future not only should be provided information on what genetic testing can and cannot do for them, but also what the test results could mean for others surrounding them (as evidenced by the influences of family, etc.).family riskPrior hereditary breast cancer (BRCA) and colorectal cancer (CRC) literature has noted anecdotally that perception of benefit to one's family influences genetic test uptake. Eliciting patient perceptions of concerns regarding their family may be beneficial to consider in oncology genetic testing generally. Similar to this literature, intention was found to be influenced by the respondent's concerns about test validity, test accuracy, and by the availability of interventions that may lead to favorable outcomes. Not surprisingly, men who were concerned about potential psychological distress were less likely to want the test. One unanswered question is how men's anticipatory distress and expected adverse consequences may affect how family risk information is interpreted and discussed. Few men in our study anticipated high levels of distress. Although literature data clearly show elevated distress among patients and their family members [ 21 ]. More research is needed to better establish the family-risk construct and how it may be influenced by other beliefs and values.The present study has limitations. Given the exploratory nature of factor analysis, these data are aimed at identifying coherent subsets of variables for data reduction, not at identifying specific attitude statements that discriminate skeptics from supporters. Nevertheless, the reduced set of 34 items is the most important among the administered 57 items, and comprises a coherent and reliable assessment tool of eliciting values and intention toward testing. This item set can thereby serve as a foundation for a confirmatory health beliefs model, using Structural Equation Modeling techniques to better elucidate the interactions of these value-based domains [ 22 ]. Also, we noted that this population had somewhat higher income and education levels than the overall Philadelphia Consolidated Metropolitan Statistical Area (CMSA). 51% of men had over $75,000 income, compared with the 32% in the Philadelphia CMSA 2000 census year dataset, and 41% had completed a Bachelor's degree or higher, compared with 28% in the CMSA. These differences may be due to affluent subjects living in suburban counties in the metropolitan Philadelphia area, who then self-select to be seen by physicians in the University of Pennsylvania system. As noted above, our prior work demonstrated no demographic differences except education (with more education correlating with diminished intention). Thus, we do not foresee an adverse impact of these discrepancies on the overall outcomes of our analysis [ 20 ].Future directions of this research may include exploring the relationship between stated intent in prostate cancer genetic screening and actual testing behavior when testing is available. Studies have shown that expressed intention does not necessarily translate to actual behavior in taking genetic tests for breast and colorectal cancers [ 10 , 23 - 29 ]. The same discrepancy between attitude and behavior may exist when a test for prostate cancer is available for the general public. Our data suggest that potential psychological distress, worries about test validity, insurance, confidentiality, and the uncertainties in subsequent intervention decisions may need to be balanced with family considerations when testing becomes available [ 30 ].Conclusions Men in this survey voiced strong attitudes favoring future genetic testing for prostate cancer risk. In the past decade and a half, genetic testing for a variety of cancers concentrated on several key concepts: i.e., stigmatization, privacy, anxiety/stress, and the need to know. These notions of stigma and psychological impact were not as relevant in this population regarding prostate cancer risk genetic testing. For examples, the following statements did not show strong enough factor loadings to warrant their inclusion, such as "I will not be able to keep my job, or get a promotion, if I know I have the prostate cancer risk gene," "The government could use my test results in ways I do not want," "I often worry about getting prostate cancer," and "I would want to get tested because I just want to know if I have the gene for prostate cancer." The most relevant aspect of data reported herein is that they begin to shed new light on the relevance of "others." How men were concerned about the impact on and the effects upon one's family were reflected in the factor analysis. As a result, future informed consent may likely include considerations of 1) how the test results will affect their own future lives, and 2) how the test results will affect their family members. The latter consideration is seldom brought into the informed consent process in the genetic counseling but may be relevant to the patient.
Conclusions
Men in this survey voiced strong attitudes favoring future genetic testing for prostate cancer risk. In the past decade and a half, genetic testing for a variety of cancers concentrated on several key concepts: i.e., stigmatization, privacy, anxiety/stress, and the need to know. These notions of stigma and psychological impact were not as relevant in this population regarding prostate cancer risk genetic testing. For examples, the following statements did not show strong enough factor loadings to warrant their inclusion, such as "I will not be able to keep my job, or get a promotion, if I know I have the prostate cancer risk gene," "The government could use my test results in ways I do not want," "I often worry about getting prostate cancer," and "I would want to get tested because I just want to know if I have the gene for prostate cancer."The most relevant aspect of data reported herein is that they begin to shed new light on the relevance of "others." How men were concerned about the impact on and the effects upon one's family were reflected in the factor analysis. As a result, future informed consent may likely include considerations of 1) how the test results will affect their own future lives, and 2) how the test results will affect their family members. The latter consideration is seldom brought into the informed consent process in the genetic counseling but may be relevant to the patient.Competing interests The author(s) declare that they have no competing interests.
Competing interests
The author(s) declare that they have no competing interests.Authors' contributions DD designed the overall project study, collaborated in the data analysis, and participated in its coordination. YL designed and carried out the factor analysis statistics. Both authors drafted, read, and approved the final manuscript.
Authors' contributions
DD designed the overall project study, collaborated in the data analysis, and participated in its coordination. YL designed and carried out the factor analysis statistics. Both authors drafted, read, and approved the final manuscript.Pre-publication history The pre-publication history for this paper can be accessed here:
Pre-publication history
The pre-publication history for this paper can be accessed here:


At a fundamental level, the continuity of life depends on cell division. Humans generate many millions of cells per second just to stay alive, with most cell types dividing and multiplying repeatedly during a lifetime. Details of cell division vary from cell to cell and organism to organism, but certain features are universal, including what is arguably a cell's most crucial task: the faithful duplication and segregation of its genetic material.During mitosis, a cell copies its nuclear DNA, then splits into two identical daughter cells, a process that involves moving the replicated chromosomes (called sister chromatids) toward opposite ends of the cell. After chromosomes replicate, a protein complex called cohesin binds the sister chromatids together. Cohesion helps the cell distinguish between the copies, which in turn aids proper distribution. Improper sister chromatid segregation can yield an abnormal number of chromosomes (called aneuploidy) in the daughter cells, a condition associated with cancer. During meiosis—the cell division that produces egg and sperm cells—aneuploidy causes a number of congenital disorders, including Down's syndrome.To end up in their appropriate positions, sister chromatids must establish attachments to tentacle-like protein polymers called spindle microtubules, which emanate from spindle poles at opposite ends of a cell. Cohesion between the chromatids makes these bipolar attachments possible and keeps sister chromatids from separating after they attach to the spindle. Cohesion occurs along the length of a chromosome and is particularly strong around centromeres, the pinched region of a chromosome. Centromeres, in turn, assemble another protein complex called the kinetochore, which mediates the attachment of chromosomes to spindle microtubules; together, they guide chromosomes to their respective destinations.Cohesin's binding locations were discovered by removing chromatin—the mass of DNA and proteins that forms chromosomes—from cells, and purifying the regions associated with cohesin. These studies looked at cohesin's binding distribution either genome-wide or at select regions of a few chromosomes. Here, two research groups use a similar approach to provide a broader picture in their analysis of cohesin binding in the budding yeast  Saccharomyces cerevisiae , a favorite system for cell biologists. In the first paper, Jennifer Gerton and colleagues generated a map for the entire yeast genome of locations where cohesin binds to chromosomes during meiosis and mitosis. In the second paper, Paul Megee and colleagues found that centromeres attract large concentrations of cohesin to their flanks and that the assembly of these cohesin domains is mediated by centromere–kinetochore complexes.Gerton's group reports that large regions surrounding centromeres have “intense” cohesin binding. These binding sites correlate with DNA base composition—DNA is composed of four chemical bases, or nucleotides, that are referred to as A, C, G, and T—showing a strong association with AT-rich regions. In meiotic chromosomes, cohesin binding sites are interspersed between the DNA double-strand breaks that initiate the exchange of genetic information characteristic of meiosis, perhaps keeping the chromatids attached without interfering with genetic recombination.Most striking, the authors note, is the observation that cohesin binding changes according to the cell's gene transcription program. Cohesin prefers DNA that lies between active transcription zones and is unceremoniously displaced from regions where RNA transcripts are being made (a process called elongation). This suggests that elongation through a region and cohesion binding may be incompatible. These observations support previous work indicating that DNA sequences required for the replication and segregation of chromosomes must be protected from transcription to function properly. Whatever the explanation, this finding begs the question of how more complicated genomes can accommodate these two seemingly contradictory processes.Megee's group investigated whether all yeast chromosomes have these large centromere-flanking cohesin regions and whether the centromeres and DNA sequences that surround them somehow facilitate the assembly of cohesin complexes. By removing centromeres and generating cells incapable of assembling kinetochores, the researchers show that the assembly of these cohesin regions is mediated solely by the centromere–kinetochore complex.What's more, inserting centromeric DNA sequences in abnormal chromosomal locations produced new cohesin-assembling regions around these “neo” centromeres. The kinetochores' influence appears to stretch over tens of thousands of DNA bases and serves chromatid segregation in two crucial ways: by recruiting high levels of cohesin to centromeres' sides, which attaches chromatids to their bipolar spindles, and by attaching chromatids to microtubules, which provides their passage to the cell's opposite sides. The maintenance of genomic integrity, the authors conclude, likely relies on the coordination of these essential functions.