Breast cancer is the leading cancer diagnosis and second most common cause of cancer deaths in sub‐Saharan Africa (SSA). Yet, there are few population‐level survival data from Africa and none on the survival differences by stage at diagnosis. Here, we estimate breast cancer survival within SSA by area, stage and country‐level human development index (HDI). We obtained data on a random sample of 2,588 breast cancer incident cases, diagnosed in 2008–2015 from 14 population‐based cancer registries in 12 countries (Benin, Cote d'Ivoire, Ethiopia, Kenya, Mali, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Uganda and Zimbabwe) through the African Cancer Registry Network. Of these, 2,311 were included for survival analyses. The 1‐, 3‐ and 5‐year observed and relative survival (RS) were estimated by registry, stage and country‐level HDI. We equally estimated the excess hazards adjusting for potential confounders. Among patients with known stage, 64.9% were diagnosed in late stages, with 18.4% being metastatic at diagnosis. The RS varied by registry, ranging from 21.6%(8.2–39.8) at Year 3 in Bulawayo to 84.5% (70.6–93.5) in Namibia. Patients diagnosed at early stages had a 3‐year RS of 78% (71.6–83.3) in contrast to 40.3% (34.9–45.7) at advanced stages (III and IV). The overall RS at Year 1 was 86.1% (84.4–87.6), 65.8% (63.5–68.1) at Year 3 and 59.0% (56.3–61.6) at Year 5. Age at diagnosis was not independently associated with increased mortality risk after adjusting for the effect of stage and country‐level HDI. In conclusion, downstaging breast cancer at diagnosis and improving access to quality care could be pivotal in improving breast cancer survival outcomes in Africa.

Breast cancer tumors are known to be highly heterogeneous and differences in their metabolic phenotypes, especially at protein level, are less well-understood. Profiling of metabolism-related proteins harbors the potential to establish new patient stratification regimes and biomarkers promoting individualized therapy. In our study, we aimed to examine the relationship between metabolism-associated protein expression profiles and clinicopathological characteristics in a large cohort of breast cancer patients. Breast cancer specimens from 801 consecutive patients, diagnosed between 2009 and 2011, were investigated using reverse phase protein arrays (RPPA). Patients were treated in accordance with national guidelines in five certified German breast centers. To obtain quantitative expression data, 37 antibodies detecting proteins relevant to cancer metabolism, were applied. Hierarchical cluster analysis and individual target characterization were performed. Clustering results and individual protein expression patterns were associated with clinical data. The Kaplan-Meier method was used to estimate survival functions. Univariate and multivariate Cox regression models were applied to assess the impact of protein expression and other clinicopathological features on survival. We identified three metabolic clusters of breast cancer, which do not reflect the receptor-defined subtypes, but are significantly correlated with overall survival (OS, p ≤ 0.03) and recurrence-free survival (RFS, p ≤ 0.01). Furthermore, univariate and multivariate analysis of individual protein expression profiles demonstrated the central role of serine hydroxymethyltransferase 2 (SHMT2) and amino acid transporter ASCT2 (SLC1A5) as independent prognostic factors in breast cancer patients. High SHMT2 protein expression was significantly correlated with poor OS (hazard ratio (HR) = 1.53, 95% confidence interval (CI) = 1.10–2.12, p ≤ 0.01) and RFS (HR = 1.54, 95% CI = 1.16–2.04, p ≤ 0.01). High protein expression of ASCT2 was significantly correlated with poor RFS (HR = 1.31, 95% CI = 1.01–1.71, p ≤ 0.05). Our data confirm the heterogeneity of breast tumors at a functional proteomic level and dissects the relationship between metabolism-related proteins, pathological features and patient survival. These observations highlight the importance of SHMT2 and ASCT2 as valuable individual prognostic markers and potential targets for personalized breast cancer therapy. ClinicalTrials.gov, NCT01592825 . Registered on 3 May 2012.

Background. Almost 500,000 women are newly diagnosed with cervical cancer (CC) every year, the majority from developing countries. There is little information on the survival of these patients. Our primary objective was to evaluate consecutive CC patients presenting over 4 years at the only radiotherapy center in Ethiopia. Methods. All patients with CC from September 2008 to September 2012 who received radiotherapy and/or surgery were included (without brachytherapy). Vital status was obtained through telephone contact or patient cards. Results. Of 2,300 CC patients, 1,059 patients with standardized treatment were included. At the end of the study, 249 patients had died; surviving patients had a median follow-up of 16.5 months; the 10% and 90% percentiles were 3.0 and 32.7 months, respectively. Mean age was 49 years (21–91 years). The majority of patients presented with International Federation of Gynecology and Obstetrics stage IIb–IIIa (46.7%). Because of progression during the waiting time (median 3.8 months), this proportion declined to 19.3% at the beginning of radiotherapy. The 1- and 2-year overall survival probabilities were 90.4% and 73.6%. If assuming a worst-case scenario (i.e., if all patients not available for follow-up after 6 months had died), the 2-year survival probability would be 45.4%. Conclusion. This study gives a thorough 4-year overview of treated patients with CC in Ethiopia. Given the limited treatment availability, a relatively high proportion of patients survived 2 years. More prevention and early detection at all levels of the health care system are needed. Increasing the capacity for external-beam radiation as well as options for brachytherapy would facilitate treatment with curative intention.