The Transcriptomic Portrait of Locally Advanced Breast Cancer and Its Prognostic Value in a Multi-Country Cohort of Latin American Patients

Abstract

Purposes: Most molecular-based published studies on breast cancer do not adequately represent the unique and diverse genetic admixture of the Latin American population. Searching for similarities and differences in molecular pathways associated with these tumors and evaluating its impact on prognosis may help to select better therapeutic approaches.

Patients and methods: We collected clinical, pathological, and transcriptomic data of a multi-country Latin American cohort of 1,071 stage II-III breast cancer patients of the Molecular Profile of Breast Cancer Study (MPBCS) cohort. The 5-year prognostic ability of intrinsic (transcriptomic-based) PAM50 and immunohistochemical classifications, both at the cancer-specific (OSC) and disease-free survival (DFS) stages, was compared. Pathway analyses (GSEA, GSVA and MetaCore) were performed to explore differences among intrinsic subtypes.

Results: PAM50 classification of the MPBCS cohort defined 42·6% of tumors as LumA, 21·3% as LumB, 13·3% as HER2E and 16·6% as Basal. Both OSC and DFS for LumA tumors were significantly better than for other subtypes, while Basal tumors had the worst prognosis. While the prognostic power of traditional subtypes calculated with hormone receptors (HR), HER2 and Ki67 determinations showed an acceptable performance, PAM50-derived risk of recurrence best discriminated low, intermediate and high-risk groups. Transcriptomic pathway analysis showed high proliferation (i.e. cell cycle control and DNA damage repair) associated with LumB, HER2E and Basal tumors, and a strong dependency on the estrogen pathway for LumA. Terms related to both innate and adaptive immune responses were seen predominantly upregulated in Basal tumors, and, to a lesser extent, in HER2E, with respect to LumA and B tumors.

Conclusions: This is the first study that assesses molecular features at the transcriptomic level in a multicountry Latin American breast cancer patient cohort. Hormone-related and proliferation pathways that predominate in PAM50 and other breast cancer molecular classifications are also the main tumor-driving mechanisms in this cohort and have prognostic power. The immune-related features seen in the most aggressive subtypes may pave the way for therapeutic approaches not yet disseminated in Latin America.

Clinical trial registration: ClinicalTrials.gov (Identifier: NCT02326857).

Keywords: Latin America; PAM50 subtypes; biological pathways; breast cancer; risk of recurrence.

Figure 1

Flow diagram of the MPBC Study.

Figure 2

Comparison of PAM50 subtypes (excluding normal-like) and surrogate, immunohistochemistry-based subtypes present in MPBCS patients. (A) Frequency table for each category. Row colors represent the conventional correspondence between intrinsic and surrogate subtypes.(B) Classic IHC surrogate subtypes as defined by ER and PgR hormone receptors (HRs) and HER2 receptors (n = 996). (C) St Gallen IHC surrogate subtypes as defined by HR, HER2 receptors and high (more than 20%) or low (equal or less than 20%) levels of Ki67-positive cells. (n = 975). Patients with missing Ki67 values are excluded. Percentages in the x-axis and within each bar correspond to those of PAM50 subtypes in each surrogate group. Percentages in the y-axis correspond to the proportion of each surrogate subtype in the patients’ total. The total number of patients used for each panel excludes patients with missing values in any of the IHC determinations and those who were labeled as normal-like by PAM50.

Figure 3

Cancer-related survival (OSC) and disease-free survival (DFS) of the MPBCS cohort according to different classifications. Each graph shows the Kaplan-Meier survival curves for each classification. (A) PAM50, (B) ROR-S, (C) classic IHC, (D) St Gallen IHC. Each class color is defined at the table of number at risk, below each graph. The p-value included in the graphs corresponds to the significance value of the log-rank test for all groups. Correlation (i.e., C-index) for each of the classifiers are also shown.

Figure 4

Summary of the top ten pathways enriched in each PAM50 subtype comparison according to GSEA, in the MPBCS cohort. Red and blue represent the enrichment of those terms in the first and second condition of each comparison, respectively; the color hue of circles indicate the NES magnitude and the size of the circle reflects the p-value of the enrichment.

Figure 5

Differentially activated TF among PAM50 subtypes in the MPBCS cohort. The differential activities found for each TF (columns) in each PAM50 subtype contrast (rows) are shown in this heatmap. Z-scores are shown for the second term in the comparison (e.g. the red hue in the first row correspond to a TF activated in Basal samples). Below each row of the heatmap, a square in a gradient from white to black represent the p-value and logFC of the differential activity for each TF in each comparison; white correspond to non-significant comparisons.

Figure 6

Clustering of differentially expressed genes related to immune terms in all PAM50 subtypes of the MPBCS cohort. The top panel shows the heatmap derived from a hierarchical clustering (k = 2); genes included in the enriched MetaCore pathways are in columns and tumors (grouped by PAM50 subtypes) are in rows. The bottom panel lists the immune-related enriched MetaCore pathways; black squares indicate the presence of a selected gene in any of the MetaCore terms.

Figure 7

Cytolytic score CYT and survival analysis according to PAM50 subtypes in the MPBCS cohort. (A), distribution of CYT among PAM50 subtypes. Medians were compared using the Kruskal-Wallis test (p= 2.2e-16). Adjusted p-values for the paired comparisons using Dunn’s test are defined as follows: *< 0.05, **< 0.01, ****< 0.0001. (B, C), Kaplan-Meier curves and survival analysis for cancer-related overall survival (OSC) according to a binary assignation of high (i.e. above median) and low CYT to LumA (B) and Basal (C) tumors. (D, E), Kaplan-Meier curves and survival analysis for disease-free survival (DFS) according to the same binary assignation of high (i.e. above median) and low CYT to LumA (D) and Basal (E) tumors.