Introduction

Several gene expression signatures have been proposed and demonstrated to be predictive of outcome in breast cancer. In the present article we address the following issues: Do these signatures perform similarly? Are there (common) molecular processes reported by these signatures? Can better prognostic predictors be constructed based on these identified molecular processes?

Methods

We performed a comprehensive analysis of the performance of nine gene expression signatures on seven different breast cancer datasets. To better characterize the functional processes associated with these signatures, we enlarged each signature by including all probes with a significant correlation to at least one of the genes in the original signature. The enrichment of functional groups was assessed using four ontology databases.

Results

The classification performance of the nine gene expression signatures is very similar in terms of assigning a sample to either a poor outcome group or a good outcome group. Nevertheless the concordance in classification at the sample level is low, with only 50% of the breast cancer samples classified in the same outcome group by all classifiers. The predictive accuracy decreases with the number of poor outcome assignments given to a sample. The best classification performance was obtained for the group of patients with only good outcome assignments. Enrichment analysis of the enlarged signatures revealed 11 functional modules with prognostic ability. The combination of the RNA-splicing and immune modules resulted in a classifier with high prognostic performance on an independent validation set.

Conclusions

The study revealed that the nine signatures perform similarly but exhibit a large degree of discordance in prognostic group assignment. Functional analyses indicate that proliferation is a common cellular process, but that other functional categories are also enriched and show independent prognostic ability. We provide new evidence of the potentially promising prognostic impact of immunity and RNA-splicing processes in breast cancer.

BACKGROUND: Immune-checkpoint inhibitors (ICI) have revolutionized cancer treatment by harnessing the immune system but ICI can induce life-threatening immune-related adverse events (irAE) affecting every organ. METHODS: We extracted irAE from VigiBase, the international pharmacovigilance database, first reported in 2008 until 01/2023 to characterize irAE reporting trends, clinical features, risk factors and outcomes. FINDINGS: We distinguished 25 types of irAE (n = 50,347cases, single irAE/case in 84.9%). Cases mainly involved anti-PD1 (programmed-death-1) monotherapy (62.4%) in male (61.7%) aged 64.3 ± 12.6 years. After 2020 vs. prior to 2016, proportion of anti-CTLA4 (Cytotoxic-T-Lymphocyte-Antigen-4) monotherapy prescription almost vanished (1.6% vs. 47%, respectively) contrasting with increased use of anti-PDL1 (PD1-ligand) monotherapy (18% vs. 0.9%) and anti-CTLA4+anti-PD(L)1 combination (20% vs. 8.9%). Anti-LAG3 (Lymphocyte-Activation-Gene-3) prescription was limited (<1%) in the studied timeframe. After 2020, over 14 different cancer types were treated vs. almost exclusively melanoma and lung cancers before 2016. Overall, the most reported irAE were skin reactions (22.9%), pneumonitis (18.5%), enterocolitis (14.4%) and thyroiditis (12.1%). ICI-myotoxicities (6.6%) included myositis, myocarditis and myasthenia-gravis like syndrome and were the most overlapping irAE (up to 30% overlap, vs. <3% in general for other inter-irAE overlap). The top factors associated with specific irAE (odds-ratio>5) were presence of thymic cancer for ICI-myotoxicities or hepatitis; presence of melanoma for vitiligo, uveitis or sarcoidosis; specific types of ICI regimen (anti-LAG3 for meningitis, anti-CTLA4 for hypophysitis); and specific reporting regions (eastern Asia for cholangitis). Median time-to-onset ranged from 31 to 273 days, being shortest for myotoxicities and most delayed for skin-bullous auto-immune reactions. Overall fatality was highest for myocarditis = 27.6%, myasthenia = 23.1%, severe cutaneous adverse reactions (SCAR) = 22.1%, myositis = 21.9%, pneumonitis = 21%, and encephalomyelitis = 18%; generally decreasing after 2020, except for myasthenia and SCAR. When reported, irAE recurrence rate after rechallenge was 28.9% (n = 275/951). INTERPRETATION: This up-to-date comprehensive worldwide pharmacovigilance study defines the spectrum, characteristics, and evolution of irAE reporting summarizing over a decade of use. Multiple risk factors and clinical peculiarities for specific irAE have been identified as signals to guide clinical practice and future research. FUNDING: Paul Gougis was supported by the academic program: Contrats ED: Programme blanc Institut Curie PSL for the conduct of his PhD. Baptiste Abbar was supported by the Fondation ARC Pour le Rechercher Sur le Cancer. The RT2L research group (Institut Curie) was supported by the academic program SHS INCa, Sanofi iTech award, and by Monoprix∗.

Background

Previous studies have independently validated the prognostic relevance of residual cancer burden (RCB) after neoadjuvant chemotherapy. We used results from several independent cohorts in a pooled patient-level analysis to evaluate the relationship of RCB with long-term prognosis across different phenotypic subtypes of breast cancer, to assess generalisability in a broad range of practice settings.

Methods

In this pooled analysis, 12 institutes and trials in Europe and the USA were identified by personal communications with site investigators. We obtained participant-level RCB results, and data on clinical and pathological stage, tumour subtype and grade, and treatment and follow-up in November, 2019, from patients (aged ≥18 years) with primary stage I-III breast cancer treated with neoadjuvant chemotherapy followed by surgery. We assessed the association between the continuous RCB score and the primary study outcome, event-free survival, using mixed-effects Cox models with the incorporation of random RCB and cohort effects to account for between-study heterogeneity, and stratification to account for differences in baseline hazard across cancer subtypes defined by hormone receptor status and HER2 status. The association was further evaluated within each breast cancer subtype in multivariable analyses incorporating random RCB and cohort effects and adjustments for age and pretreatment clinical T category, nodal status, and tumour grade. Kaplan-Meier estimates of event-free survival at 3, 5, and 10 years were computed for each RCB class within each subtype.

Findings

We analysed participant-level data from 5161 patients treated with neoadjuvant chemotherapy between Sept 12, 1994, and Feb 11, 2019. Median age was 49 years (IQR 20-80). 1164 event-free survival events occurred during follow-up (median follow-up 56 months [IQR 0-186]). RCB score was prognostic within each breast cancer subtype, with higher RCB score significantly associated with worse event-free survival. The univariable hazard ratio (HR) associated with one unit increase in RCB ranged from 1·55 (95% CI 1·41-1·71) for hormone receptor-positive, HER2-negative patients to 2·16 (1·79-2·61) for the hormone receptor-negative, HER2-positive group (with or without HER2-targeted therapy; p<0·0001 for all subtypes). RCB score remained prognostic for event-free survival in multivariable models adjusted for age, grade, T category, and nodal status at baseline: the adjusted HR ranged from 1·52 (1·36-1·69) in the hormone receptor-positive, HER2-negative group to 2·09 (1·73-2·53) in the hormone receptor-negative, HER2-positive group (p<0·0001 for all subtypes).

Interpretation

RCB score and class were independently prognostic in all subtypes of breast cancer, and generalisable to multiple practice settings. Although variability in hormone receptor subtype definitions and treatment across patients are likely to affect prognostic performance, the association we observed between RCB and a patient's residual risk suggests that prospective evaluation of RCB could be considered to become part of standard pathology reporting after neoadjuvant therapy.

Funding

National Cancer Institute at the US National Institutes of Health.