Gene-expression profiling has had a considerable impact on our understanding of breast cancer biology. During the last 15 years, 5 intrinsic molecular subtypes of breast cancer (Luminal A, Luminal B, HER2-enriched, Basal-like and Claudin-low) have been identified and intensively studied. In this review, we will focus on the current and future clinical implications of the intrinsic molecular subtypes beyond the current pathological-based classification endorsed by the 2013 St. Gallen Consensus Recommendations. Within hormone receptor-positive and HER2-negative early breast cancer, the Luminal A and B subtypes predict 10-year outcome regardless of systemic treatment administered as well as residual risk of distant recurrence after 5 years of endocrine therapy. Within clinically HER2-positive disease, the 4 main intrinsic subtypes can be identified and dominate the biological and clinical phenotype. From a clinical perspective, patients with HER2+/HER2-enriched disease seem to benefit the most from neoadjuvant trastuzumab, or dual HER2 blockade with trastuzumab/lapatinib, in combination with chemotherapy, and patients with HER2+/Luminal A disease seem to have a relative better outcome compared to the other subtypes. Finally, within triple-negative breast cancer (TNBC), the Basal-like disease predominates (70-80%) and, from a biological perspective, should be considered a cancer-type by itself. Importantly, the distinction between Basal-like versus non-Basal-like within TNBC might predict survival following (neo)adjvuvant multi-agent chemotherapy, bevacizumab benefit in the neoadjuvant setting (CALGB40603), and docetaxel vs. carboplatin benefit in first-line metastatic disease (TNT study). Overall, this data suggests that intrinsic molecular profiling provides clinically relevant information beyond current pathology-based classifications.

Predicting treatment benefit and/or outcome before any therapeutic intervention has taken place would be clinically very useful. Herein, we evaluate the ability of the intrinsic subtypes and the risk of relapse score at diagnosis to predict survival and response following neoadjuvant chemotherapy. In addition, we evaluated the ability of the Claudin-low and 7-TNBCtype classifications to predict response within triple-negative breast cancer (TNBC). Gene expression and clinical-pathological data were evaluated in a combined dataset of 957 breast cancer patients, including 350 with TNBC, treated with sequential anthracycline and anti-microtubule-based neoadjuvant regimens. Intrinsic subtype, risk of relapse score based on subtype and proliferation (ROR-P), the Claudin-low subtype and the 7-TNBCtype subtype classification were evaluated. Logistic regression models for pathological complete response (pCR) and Cox models for distant relapse-free survival (DRFS) were used. Basal-like, Luminal A, Luminal B, and HER2-enriched subtypes represented 32.7 %, 30.6 %, 18.2 %, and 10.3 % of cases, respectively. Intrinsic subtype was independently associated with pCR in all patients, in hormone receptor-positive/HER2-negative disease, in HER2-positive disease, and in TNBC. The pCR rate of Basal-like disease was >35 % across all clinical cohorts. Neither the Claudin-low nor the 7-TNBCtype subtype classifications predicted pCR within TNBCs after accounting for intrinsic subtype. Finally, intrinsic subtype and ROR-P provided independent prognostic information beyond clinicopathological variables and type of pathological response. A 5-year DRFS of 97.5 % (92.8–100.0 %) was observed in these neoadjuvant-treated and clinically node-negative patients predicted to be low risk by ROR-P (i.e. 57.4 % of Luminal A tumors with clinically node-negative disease). Intrinsic subtyping at diagnosis provides prognostic and predictive information for patients receiving neoadjuvant chemotherapy. Although we could not exclude a survival benefit of neoadjuvant chemotherapy in patients with early breast cancer with clinically node-negative and ROR-low disease at diagnosis, the absolute benefit of cytotoxic therapy in this group might be rather small (if any).

Purpose: Bevacizumab regimens are approved for the treatment of recurrent glioblastoma in many countries. Aberrant MET expression has been reported in glioblastoma and may contribute to bevacizumab resistance. The phase II study GO27819 investigated the monovalent MET inhibitor onartuzumab plus bevacizumab (Ona + Bev) versus placebo plus bevacizumab (Pla + Bev) in recurrent glioblastoma. Methods: At first recurrence after chemoradiation, bevacizumab-naïve patients with glioblastoma were randomly assigned 1:1 to receive Ona (15 mg/kg, once every 3 weeks) + Bev (15 mg/kg, once every 3 weeks) or Pla + Bev until disease progression. The primary end point was progression-free survival by response assessment in neuro-oncology criteria. Secondary end points were overall survival, objective response rate, duration of response, and safety. Exploratory biomarker analyses correlated efficacy with expression levels of MET ligand hepatocyte growth factor, O ⁶ -methylguanine–DNA methyltransferase promoter methylation, and glioblastoma subtype. Results: Among 129 patients enrolled (Ona + Bev, n = 64; Pla + Bev, n = 65), baseline characteristics were balanced. The median progression-free survival was 3.9 months for Ona + Bev versus 2.9 months for Pla + Bev (hazard ratio, 1.06; 95% CI, 0.72 to 1.56; P = .7444). The median overall survival was 8.8 months for Ona + Bev and 12.6 months for Pla + Bev (hazard ratio, 1.45; 95% CI, 0.88 to 2.37; P = .1389). Grade ≥ 3 adverse events were reported in 38.5% of patients who received Ona + Bev and 35.9% of patients who received Pla + Bev. Exploratory biomarker analyses suggested that patients with high expression of hepatocyte growth factor or unmethylated O ⁶ -methylguanine–DNA methyltransferase may benefit from Ona + Bev. Conclusion: There was no evidence of further clinical benefit with the addition of onartuzumab to bevacizumab compared with bevacizumab plus placebo in unselected patients with recurrent glioblastoma in this phase II study; however, further investigation into biomarker subgroups is warranted.

The molecular classification of glioblastoma (GBM) based on gene expression might better explain outcome and response to treatment than clinical factors. Whole transcriptome sequencing using next-generation sequencing platforms is rapidly becoming accepted as a tool for measuring gene expression for both research and clinical use. Fresh frozen (FF) tissue specimens of GBM are difficult to obtain since tumor tissue obtained at surgery is often scarce and necrotic and diagnosis is prioritized over freezing. After diagnosis, leftover tissue is usually stored as formalin-fixed paraffin-embedded (FFPE) tissue. However, RNA from FFPE tissues is usually degraded, which could hamper gene expression analysis. We compared RNA-Seq data obtained from matched pairs of FF and FFPE GBM specimens. Only three FFPE out of eleven FFPE-FF matched samples yielded informative results. Several quality-control measurements showed that RNA from FFPE samples was highly degraded but maintained transcriptomic similarities to RNA from FF samples. Certain issues regarding mutation analysis and subtype prediction were detected. Nevertheless, our results suggest that RNA-Seq of FFPE GBM specimens provides reliable gene expression data that can be used in molecular studies of GBM if the RNA is sufficiently preserved.

A mesenchymal transition occurs both during the natural evolution of glioblastoma (GBM) and in response to therapy. Here, we report that the adhesion G-protein-coupled receptor, GPR56/ADGRG1, inhibits GBM mesenchymal differentiation and radioresistance. GPR56 is enriched in proneural and classical GBMs and is lost during their transition toward a mesenchymal subtype. GPR56 loss of function promotes mesenchymal differentiation and radioresistance of glioma initiating cells both in vitro and in vivo. Accordingly, a low GPR56-associated signature is prognostic of a poor outcome in GBM patients even within non-G-CIMP GBMs. Mechanistically, we reveal GPR56 as an inhibitor of the nuclear factor kappa B (NF-κB) signaling pathway, thereby providing the rationale by which this receptor prevents mesenchymal differentiation and radioresistance. A pan-cancer analysis suggests that GPR56 might be an inhibitor of the mesenchymal transition across multiple tumor types beyond GBM.

We explored predictive factors of pseudoprogression (PsP) and its impact on prognosis in a retrospective series of uniformly treated glioblastoma patients. Patients were classified as having PsP, early progression (eP) or neither (nP). We examined potential associations with clinical, molecular, and basal imaging characteristics and compared overall survival (OS), progression‐free survival (PFS), post‐progression survival (PPS) as well as the relationship between PFS and PPS in the three groups. Of the 256 patients studied, 56 (21.9%) were classified as PsP, 70 (27.3%) as eP, and 130 (50.8%) as nP. Only MGMT methylation status was associated to PsP. MGMT methylated patients had a 3.5‐fold greater possibility of having PsP than eP (OR: 3.48; 95% CI: 1.606–7.564; P = 0.002). OS was longer for PsP than eP patients (18.9 vs. 12.3 months; P = 0.0001) but was similar for PsP and nP patients (P = 0.91). OS was shorter–though not significantly so—for PsP than nP patients (OS: 19.5 vs. 27.9 months; P = 0.63) in methylated patients. PPS was similar for patients having PsP, eP or nP (PPS: 7.2 vs. 5.4 vs. 6.7; P = 0.43). Neurological deterioration occurred in 64.3% of cases at the time they were classified as PsP and in 72.8% of cases of eP (P = 0.14). PsP confounds the evaluation of disease and does not confer a survival advantage in glioblastoma.