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Continued smoking after a cancer diagnosis adversely affects outcomes, including recurrence of the primary cancer and/or the development of second primary cancers. Despite this, prevalence of smoking is high in cancer survivors and higher in survivors of tobacco-related cancers. The diagnosis of cancer provides a teachable moment, and social networks, such as family, friends, and social groups, seem to play a significant role in smoking habits of cancer patients. Interventions that involve members of patients’ social network, especially those who also smoke, might improve tobacco cessation rates. Very few studies have been conducted to evaluate and target patients’ social networks. Yet, many studies have demonstrated that cancer survivors who received higher levels of social support were less likely to be current smokers. Clinicians should be doing as much as they can to encourage smoking cessation in both patients and relevant family members. Research aimed at influencing smoking behavioral change in the entire family is needed to increase cessation intervention success rate, which can ultimately improve the health and longevity of patients as well as their family members.

Patients, Materials, and Methods: Presented is the differential expression of mRNA and miRNA in 44 Stage I and Stage II patients, 21 who developed metastasis within 5 years of nephrectomy, compared to 23 patients who remained disease free for more than 5 years. Extracted RNA from nephrectomy specimens preserved in FFPE blocks was sequenced using RNAseq. MiRNA expression was performed using the TaqMan OpenArray qPCR protocol. Results: One hundred thirty one genes and 2 miRNA were differentially expressed between the two groups. Canonical correlation (CC) analysis was applied and four CCs (CC32, CC20, CC9, and CC7) have an AUC > 0.65 in our dataset with similar predictive power in the TCGA-KIRC dataset. Gene set enrichment showed CC9 as kidney development/adhesion, CC20 as oxidative phosphorylation pathway, CC32 as RNA binding/spindle and CC7 as immune response. In a multivariate Cox model, the four CCs were able to identify high/low risk groups for metastases in the TCGA-KIRC (p < 0.05) with odds ratios of CC32 = 5.7, CC20 = 4.4, CC9 = 3.6, and CC7 = 2.7. Conclusion: These results identify molecular signatures for more aggressive tumors in clinically low risk ccRCC patients who have a higher potential of metastasis than would be expected.