The gut microbiota may play a role in breast cancer etiology by regulating hormonal, metabolic and immunologic pathways. We investigated associations of fecal bacteria with breast cancer and nonmalignant breast disease in a case‐control study conducted in Ghana, a country with rising breast cancer incidence and mortality. To do this, we sequenced the V4 region of the 16S rRNA gene to characterize bacteria in fecal samples collected at the time of breast biopsy (N = 379 breast cancer cases, N = 102 nonmalignant breast disease cases, N = 414 population‐based controls). We estimated associations of alpha diversity (observed amplicon sequence variants [ASVs], Shannon index, and Faith's phylogenetic diversity), beta diversity (Bray‐Curtis and unweighted/weighted UniFrac distance), and the presence and relative abundance of select taxa with breast cancer and nonmalignant breast disease using multivariable unconditional polytomous logistic regression. All alpha diversity metrics were strongly, inversely associated with odds of breast cancer and for those in the highest relative to lowest tertile of observed ASVs, the odds ratio (95% confidence interval) was 0.21 (0.13‐0.36; Ptrend < .001). Alpha diversity associations were similar for nonmalignant breast disease and breast cancer grade/molecular subtype. All beta diversity distance matrices and multiple taxa with possible estrogen‐conjugating and immune‐related functions were strongly associated with breast cancer (all Ps < .001). There were no statistically significant differences between breast cancer and nonmalignant breast disease cases in any microbiota metric. In conclusion, fecal bacterial characteristics were strongly and similarly associated with breast cancer and nonmalignant breast disease. Our findings provide novel insight into potential microbially‐mediated mechanisms of breast disease.
The gut microbiome likely plays a role in the etiology of multiple health conditions, especially those affecting the gastrointestinal tract. Little consensus exists as to the best, standard methods to collect fecal samples for future microbiome analysis. We evaluated three distinct populations (N = 132 participants) using 16S rRNA gene amplicon sequencing data to investigate the reproducibility, stability, and accuracy of microbial profiles in fecal samples collected and stored via fecal occult blood test (FOBT) or Flinders Technology Associates (FTA) cards, fecal immunochemical tests (FIT) tubes, 70% and 95% ethanol, RNAlater, or with no solution. For each collection method, based on relative abundance of select phyla and genera, two alpha diversity metrics, and four beta diversity metrics, we calculated intraclass correlation coefficients (ICCs) to estimate reproducibility and stability, and Spearman correlation coefficients (SCCs) to estimate accuracy of the fecal microbial profile. Comparing duplicate samples, reproducibility ICCs for all collection methods were excellent (ICCs ≥75%). After 4–7 days at ambient temperature, ICCs for microbial profile stability were excellent (≥75%) for most collection methods, except those collected via no-solution and 70% ethanol. SCCs comparing each collection method to immediately-frozen no-solution samples ranged from fair to excellent for most methods; however, accuracy of genus-level relative abundances differed by collection method. Our findings, taken together with previous studies and feasibility considerations, indicated that FOBT/FTA cards, FIT tubes, 95% ethanol, and RNAlater are excellent choices for fecal sample collection methods in future microbiome studies. Furthermore, establishing standard collection methods across studies is highly desirable.
Background Previous studies suggested associations between the oral microbiome and lung cancer, but studies were predominantly cross-sectional and underpowered. Methods Using a case-cohort design, 1,306 incident lung cancer cases were identified in the Agricultural Health Study, NIH-AARP Diet and Health Study, and Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Referent subcohorts were randomly selected by strata of age, sex, and smoking history. DNA was extracted from oral wash specimens using the DSP DNA Virus Pathogen kit, the 16S rRNA gene V4 region was amplified and sequenced, and bioinformatics were conducted using QIIME 2. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated using weighted Cox proportional hazards models. Results Higher alpha diversity was associated with lower lung cancer risk (Shannon index HR 0.90; 95% CI: 0.84–0.96). Specific principal component vectors of the microbial communities were also significantly associated with lung cancer risk. After multiple testing adjustment, greater relative abundance of three genera and presence of one genus were associated with greater lung cancer risk, while presence of three genera were associated with lower risk. For example, every standard deviation increase in Streptococcus abundance was associated with 1.14 times the risk of lung cancer (95% CI: 1.06–1.22). Associations were strongest among squamous cell carcinoma cases and former smokers. Conclusions Multiple oral microbial measures were prospectively associated with lung cancer risk in three US cohort studies with associations varying by smoking history and histologic subtype. The oral microbiome may offer new opportunities for lung cancer prevention.
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