Background Recent epidemiological studies suggest that reproductive factors are associated with breast cancer (BC) molecular subtypes. However, these associations have not been thoroughly studied in the African populations. The present study aimed to investigate the prevalence of BC molecular subtypes and assess their association with reproductive factors in Tanzanian BC patients. Methods This hospital-based case-only cross-sectional study consisted of 263 histologically confirmed BC patients in Tanzania. Clinico-pathological data, socio-demographic characteristics, anthropometric measurements, and reproductive risk factors were examined using the Chi-square test and one-way ANOVA. The association among reproductive factors and BC molecular subtypes was analyzed using multinomial logistic regression. The heterogeneity of the associations was assessed using the Wald test. Results We found evident subtype heterogeneity for reproductive factors. We observed that post-menopausal status was more prevalent in luminal-A subtype, while compared to luminal-A subtype, luminal-B and HER-2 enriched subtypes were less likely to be found in post-menopausal women (OR: 0.21, 95%CI 0.10–0.41, p = 0.001; OR: 0.39, 95%CI 0.17–0.89, p = 0.026, respectively). Also, the luminal-B subtype was more likely to be diagnosed in patients aged ≤ 40 years than the luminal-A subtype (OR: 2.80, 95%CI 1.46–5.32, p = 0.002). Women who had their first full-term pregnancy at < 30 years were more likely to be of luminal-B (OR: 2.71, 95%CI 1.18–4.17, p = 0.018), and triple-negative (OR: 2.28, 95%CI 1.02–4.07, p = 0.044) subtypes relative to luminal-A subtype. Furthermore, we observed that breastfeeding might have reduced odds of developing luminal-A, luminal-B and triple-negative subtypes. Women who never breastfed were more likely to be diagnosed with luminal-B and triple-negative subtypes when compared to luminal-A subtype (OR: 0.46, 95%CI 0.22–0.95, p = 0.035; OR: 0.41, 95%CI 0.20–0.85, p = 0.017, respectively). . Conclusion Our results are the first data reporting reproductive factors heterogeneity among BC molecular subtypes in Tanzania. Our findings suggest that breast-feeding may reduce the likelihood of developing luminal-A, luminal-B, and triple-negative subtypes. Meanwhile, the first full-term pregnancy after 30 years of age could increase the chance of developing luminal-A subtype, a highly prevalent subtype in Tanzania. More interventions to promote modifiable risk factors across multiple levels may most successfully reduce BC incidence in Africa.

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Background: During cancer growth, immunosuppressive microenvironment is created that enables tumour cells to evade an eliminative immune response and hence manage to grow into malignancy. HLA-G, existing as either membrane-bound (mHLA-G) or soluble (sHLA-G) molecule is thought to be immunosuppressive and produced more by tumor cells. The +3142G/C polymorphism in HLA-G gene affects its expression, and G allele is considered to be a protective mutant allele associated with less expression of HLA-G. The implication of HLA-G in cancer development has been reported in different cancers and populations. But, its implication in most African populations has not yet been investigated. The aim of this study was to determine the possible associations of soluble HLA-G and HLA-G +3142G/C SNP with breast cancer. Materials and Methods: 75 breast cancer patients and 84 normal controls were recruited in this study. The genotyping of HLA-G +3142G/C polymorphism was determined by LightSNiP typing assay using quantitative Real-Time PCR and sHLA-G levels were determined by ELISA. Results: The sHLA-G levels were significantly lower in breast cancer patients than in controls (p<0.001). Also, they were significantly lower in mastectomized patients compared to non-mastectomized patients (p=0.018). The ROC analysis revealed a significant ability of sHLA-G to differentiate breast cancer patients versus normal controls (AUC=0.697, 95% CI= 0.619-0.767, p<0.001) and identify mastectomized patients (AUC=0.667, 95% CI= 0.549 to 0.772, p=0.041). The assessment of +3142G/C polymorphism revealed a relatively similar distribution of frequencies of genotypes and alleles between breast cancer patients and normal controls (p>0.05) and was neither associated with sHLA-G levels. Conclusion: While the +3142G/C SNP was found not to be relevant to breast cancer, the changes of sHLA-G levels in response to medical interventions such as mastectomy may be translated into its potential prognostic utility for breast cancer. More studies are needed to provide clear evidence of sHLA-G as a diagnostic and prognostic marker of breast cancer in Tanzania.

Genome-wide association studies (GWAS) have recently confirmed a strong association of the 9p21.3 locus with Coronary Artery Disease (CAD) in different populations but no data has been reported for the Tanzanian population. This study aimed to investigate the 9p21.3 locus harboring the diseasecausing hotspot variations in Tanzanian CAD patients and their associations with the risk factors. 135 patients with CAD and 140 non-CAD patients were enrolled into the study. Further the biochemical analysis, the genotyping assays were performed by the use of qRT-PCR. The genotype and allele frequencies of rs1333049, rs2383207, rs2383206, rs10757274, rs10757278, and rs10811656 were significantly different between the groups (p<0.005). The genotype distribution of rs1333049, rs10757278 and rs10811656 polymorphisms were significantly different among patients with one, two, three stenotic vessels (p<0.05). For rs10757274 and rs10757278, the GG genotype indicated a significant 3-fold and 4-fold increased risk of CAD (p<0.0001,respectively). Additionally, haplotype analysis revealed that AAGCAG, AAACAG, GGGTGC haplotypes of 9p21.3 locus polymorphisms are associated with CAD risk. The GGGTGC haplotype was over-represented while the other two underrepresented in patients as compared to controls (p<0.00001,respectively) suggesting the first one a high-risk and the other two low-risk haplotypes for Tanzanian population. The AUC of a risk model based on non-genetic risk factors was 0.954 (95% CI: 0.930-0.977) and the combination with genetic risk factors improved the AUC to 0.982 (95% CI: 0.954-0.985) (p<0.012), indicating good diagnostic accuracy. Our results are the first data reporting statistically significant associations between 9p21.3 polymorphisms and CAD, and the very first haplotype block harboring the disease-causing variations in Tanzanian population.