Purpose

The term cancer survivor can refer to individuals from diagnosis through the rest of their life. However, not all people with cancer identify as a survivor, and underlying factors and correlates are yet to be well-explored empirically.

Methods

Study 1 surveyed men in a prostate cancer peer support network (n = 514), exploring psychosocial variables related to adopting a survivor identity. Study 2 interviewed 160 women with breast cancer in an online support group and collected observational data, assessing how survivor identity relates to perceptions of and participation in online support groups.

Results

For men, survivor identity (35 %) was related to lower levels of threat appraisal (p = .000), more deliberate rumination (p = .042), gaining greater understanding of cancer experience through peers (p = .041) and a higher, though marginally significant, level of posttraumatic growth (p = .052). Women adopting a survivor identity (50 %) had higher rates of online support group posts (p = .048), a greater feeling of mattering to the group (p = .002), rated the group as more helpful (p = .004 to .01) and had less difficulty in relating to the group (p = .002) than women not identifying as a survivor.

Conclusions

Survivor identity was related to active and positive engagement with peers, and cognitive processing.

Implications for cancer survivors

While the cancer survivor metaphor may be salient for some people diagnosed with cancer, many did not associate with the term, highlighting the complexity surrounding survivorship discourse and the need to be sensitive to unique individual needs in psychosocial interventions that involve groups.

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10^-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10^-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10^-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa¹.

The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.