A three-gene signature marks the time to locoregional recurrence in luminal-like breast cancer.

BACKGROUND: Gene expression profiling (GEP)-based prognostic signatures are being rapidly integrated into clinical decision making for systemic management of breast cancer patients. However, GEP remains relatively underdeveloped for locoregional risk assessment. Yet, locoregional recurrence (LRR), especially early after surgery, is associated with poor survival. PATIENTS AND METHODS: GEP was carried out on two independent luminal-like breast cancer cohorts of patients developing early (≤5 years after surgery) or late (>5 years) LRR and used, by a training and testing approach, to build a gene signature able to intercept women at risk of developing early LRR. The GEP data of two in silico datasets and of a third independent cohort were used to explore its prognostic value. RESULTS: Analysis of the first two cohorts led to the identification of three genes, CSTB, CCDC91 and ITGB1, whose expression, derived by principal component analysis, generated a three-gene signature significantly associated with early LRR in both cohorts (P value <0.001 and 0.005, respectively), overcoming the discriminatory capability of age, hormone receptor status and therapy. Remarkably, the integration of the signature with these clinical variables led to an area under the curve of 0.878 [95% confidence interval (CI) 0.810-0.945]. In in silico datasets we found that the three-gene signature retained its association, showing higher values in the early relapsed patients. Moreover, in the third additional cohort, the signature significantly associated with relapse-free survival (hazard ratio 1.56, 95% CI 1.04-2.35). CONCLUSIONS: Our three-gene signature represents a new exploitable tool to aid treatment choice in patients with luminal-like breast cancer at risk of developing early recurrence.

PEOPLE (NCT03447678), a first-line phase II pembrolizumab trial, in negative and low PD-L1 advanced NSCLC: clinical outcomes and association with circulating immune biomarkers.

BACKGROUND: The PEOPLE trial aimed to identify new immune biomarkers in negative and low programmed death-ligand 1 (PD-L1) (0%-49%) advanced non-small-cell lung cancer (aNSCLC) patients treated with first-line pembrolizumab. Here we report the main outcomes and the circulating immune biomarkers analysis. PATIENTS AND METHODS: The primary endpoint of this phase II trial was the identification of immune biomarkers associated with progression-free survival (PFS). Overall survival (OS), objective response rate (ORR), disease control rate (DCR), duration of response (DoR) and safety were secondary endpoints. Absolute cell counts for 36 subsets belonging to innate and adaptive immunity were determined by multiparametric flow cytometry in peripheral blood at baseline and at first radiologic evaluation. An orthoblique principal components-based clustering approach and multivariable Cox regression model adjusted for clinical variables were used to analyze immune variables and their correlation with clinical endpoints. RESULTS: From May 2018 to October 2020, 65 patients were enrolled. After a median follow-up of 26.4 months, the median PFS was 2.9 months [95% confidence interval (CI) 1.8-5.6 months] and median OS was 12.1 months (95% CI 8.7-17.1 months). The ORR was 21.5%, DCR was 47.7% and median DoR was 14.5 months (95% CI 6.4-24.9 months). Drug-related grade 3-4 adverse events were 9.2%. Higher T cell and natural killer (NK) cell count at baseline and at the first radiologic evaluation were associated with improved PFS, DCR and OS. On the contrary, higher myeloid cell count at baseline or at the first radiologic evaluation was significantly associated with worse OS and DCR. CONCLUSIONS: Circulating immune biomarkers can contribute to predict outcomes in negative and low PD-L1 aNSCLC patients treated with first-line single-agent pembrolizumab.

Pathobiological implications of the d16HER2 splice variant for stemness and aggressiveness of HER2-positive breast cancer.

We have previously shown that the d16HER2 splice variant is linked to HER2-positive breast cancer (BC) tumorigenesis, progression and response to Trastuzumab. However, the mechanisms by which d16HER2 contributes to HER2-driven aggressiveness and targeted therapy susceptibility remain uncertain. Here, we report that the d16HER2-positive mammary tumor cell lines MI6 and MI7, derived from spontaneous lesions of d16HER2 transgenic (tg) mice and resembling the aggressive features of primary lesions, are enriched in the expression of Wnt, Notch and epithelial-mesenchymal transition pathways related genes compared with full-length wild-type (WT) HER2-positive cells (WTHER2_1 and WTHER2_2) derived from spontaneous tumors arising in WTHER2 tg mice. MI6 cells exhibited increased resistance to anoikis and significantly higher mammosphere-forming efficiency (MFE) and self-renewal capability than the WTHER2-positive counterpart. Furthermore, d16HER2-positive tumor cells expressed a higher fraction of CD29High/CD24+/SCA1Low cells and displayed greater in vivo tumor engraftment in serial dilution conditions than WTHER2_1 cells. Accordingly, NOTCH inhibitors impaired mammosphere formation only in MI6 cells. A comparative analysis of stemness-related features driven by d16HER2 and WTHER2 in ad hoc engineered human BC cells (MCF7 and T47D) revealed a higher MFE and aldehyde dehydrogenase-positive staining in d16HER2- vs WTHER2-infected cells, sustaining consistent BC-initiating cell enrichment in the human setting. Moreover, marked CD44 expression was found in MCF7_d16 and T47D_d16 cells vs their WTHER2 and Mock counterparts. Clinically, BC cases from two distinct HER2-positive cohorts characterized by high levels of expression of the activated-d16HER2 metagene were significantly enriched in the Notch family and signal transducer genes vs those with low levels of the metagene.

Extracellular matrix signature identifies breast cancer subgroups with different clinical outcome.

Prediction of the clinical outcome of breast cancer is multi-faceted and challenging. There is growing evidence that the complexity of the tumour micro-environment, consisting of several cell types and a complex mixture of proteins, plays an important role in development, progression, and response to therapy. In the current study, we investigated whether invasive breast tumours can be classified on the basis of the expression of extracellular matrix (ECM) components and whether such classification is representative of different clinical outcomes. We first examined the matrix composition of 28 primary breast carcinomas by morphology and gene expression profiling using 22K oligonucleotide Agilent microarrays. Hierarchical clustering of the gene expression profile of 278 ECM-related genes derived from the literature divided the tumours into four main groups (ECM1-4). A set of selected differentially expressed genes was validated by immunohistochemistry. The robustness of the ECM classification was confirmed by studying the four ECM groups in a previously published gene expression data set of 114 early-stage primary breast carcinomas profiled using cDNA arrays. Univariate survival analysis showed significant differences in clinical outcome among the various ECM subclasses. One set of tumours, designated ECM4, had a favourable outcome and was defined by the overexpression of a set of protease inhibitors belonging to the serpin family, while tumours with an ECM1 signature had a poorer prognosis and showed high expression of integrins and metallopeptidases, and low expression of several laminin chains. Furthermore, we identified three surrogate markers of ECM1 tumours: MARCO, PUNC, and SPARC, whose expression levels were associated with breast cancer survival and risk of recurrence. Our findings suggest that primary breast tumours can be classified based upon ECM composition and that this classification provides relevant information on the biology of breast carcinomas, further supporting the hypothesis that clinical outcome is strongly related to stromal characteristics.