A PET-Surrogate Signature for the Interrogation of the Metabolic Status of Breast Cancers.

Metabolic alterations in cancers can be exploited for diagnostic, prognostic, and therapeutic purposes. This is exemplified by 18F-fluorodeoxyglucose (FDG)-positron emission tomography (FDG-PET), an imaging tool that relies on enhanced glucose uptake by tumors for diagnosis and staging. By performing transcriptomic analysis of breast cancer (BC) samples from patients stratified by FDG-PET, a 54-gene signature (PETsign) is identified that recapitulates FDG uptake. PETsign is independently prognostic of clinical outcome in luminal BCs, the most common and heterogeneous BC molecular subtype, which requires improved stratification criteria to guide therapeutic decision-making. The prognostic power of PETsign is stable across independent BC cohorts and disease stages including the earliest BC stage, arguing that PETsign is an ab initio metabolic signature. Transcriptomic and metabolomic analysis of BC cells reveals that PETsign predicts enhanced glycolytic dependence and reduced reliance on fatty acid oxidation. Moreover, coamplification of PETsign genes occurs frequently in BC arguing for their causal role in pathogenesis. CXCL8 and EGFR signaling pathways feature strongly in PETsign, and their activation in BC cells causes a shift toward a glycolytic phenotype. Thus, PETsign serves as a molecular surrogate for FDG-PET that could inform clinical management strategies for BC patients.

miRNome profiling of lung cancer metastases revealed a key role for miRNA-PD-L1 axis in the modulation of chemotherapy response.

Locally advanced non-small cell lung cancer (NSCLC) is frequent at diagnosis and requires multimodal treatment approaches. Neoadjuvant chemotherapy (NACT) followed by surgery is the treatment of choice for operable locally advanced NSCLC (Stage IIIA). However, the majority of patients are NACT-resistant and show persistent lymph nodal metastases (LNmets) and an adverse outcome. Therefore, the identification of mechanisms and biomarkers of NACT resistance is paramount for ameliorating the prognosis of patients with Stage IIIA NSCLC. Here, we investigated the miRNome and transcriptome of chemo-naïve LNmets collected from patients with Stage IIIA NSCLC (N = 64). We found that a microRNA signature accurately predicts NACT response. Mechanistically, we discovered a miR-455-5p/PD-L1 regulatory axis which drives chemotherapy resistance, hallmarks metastases with active IFN-γ response pathway (an inducer of PD-L1 expression), and impacts T cells viability and relative abundances in tumor microenvironment (TME). Our data provide new biomarkers to predict NACT response and add molecular insights relevant for improving the management of patients with locally advanced NSCLC.

Comparison of StemPrintER with Oncotype DX Recurrence Score for predicting risk of breast cancer distant recurrence after endocrine therapy.

OBJECTIVE: Molecular tests predicting the risk of distant recurrence (DR) can be used to assist therapy decision-making in oestrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancer patients after considerations of standard clinical markers. The Oncotype DX Recurrence Score (RS) is a widespread tool used for this purpose. Here, we compared the RS with the StemPrintER Risk Score (SPRS), a novel genomic predictor with a unique biological basis in its ability to measure the expression of cancer stemness genes. MATERIALS AND METHODS: We benchmarked the SPRS vs. RS, alone or in combination with clinicopathological variables expressed by the Clinical Treatment Score (CTS), for the prognostication of DR in a retrospective cohort of 776 postmenopausal patients with ER+/HER2-breast cancer enrolled in the translational arm of the randomised Arimidex, Tamoxifen, Alone or in Combination (ATAC) trial. Likelihood ratio (LR) with χ2 test and C-index were used to assess prognostic performance for the entire ten-year follow-up period and in early (0-5 years) and late (5-10 years) intervals. RESULTS: In all patients, the SPRS provided significantly more prognostic information than the RS for ten-year DR prognostication (C-index = 0.688, LR-χ2 = 33.4 vs. C-index = 0.641, LR-χ2 = 22.1) and for late (5-10 years) DR prognostication (C-index = 0.689, LR-χ2 = 18.8 vs. C-index = 0.571, LR-χ2 = 4.7). The SPRS also provided more prognostic information than the RS when added to the CTS in all patients (CTS + SPRS: LR-Δχ2 = 14.9; CTS + RS: LR-Δχ2 = 9.7) and in node-negative patients (CTS + SPRS: LR-Δχ2 = 11.7; CTS + RS: LR-Δχ2 = 6.6). CONCLUSIONS: In postmenopausal ER+/HER2- breast cancer patients, SPRS provided more prognostic information than RS for DR when used alone or in combination with the CTS. The SPRS could therefore potentially identify high-risk patients, who might benefit from aggressive treatments, from low-risk patients who might safely avoid adjuvant chemotherapy or prolongation of endocrine therapy.

Unraveling the role of low-frequency mutated genes in breast cancer.

Motivation: Breast cancer is the most commonly diagnosed malignancy in women and the second cause of cancer death in developed countries. While advancements in early detection and therapeutic options have led to a significant decrease in mortality, response to treatment is affected by the genetic heterogeneity of the disease. Recent genome-wide DNA mutation analyses revealed the existence of hundreds of low-frequency mutated genes, in addition to known cancer drivers: a finding that is prompting research into the impact of these genes on the pathogenesis of the disease. Results: Herein, we describe a strategy towards the characterization of the role of low-frequency mutated genes in breast cancer. Through the combined analyses of publicly available gene expression and mutational datasets, we identified several Cancer Gene Modules (CMs) that we re-organized in Gene Regulatory Networks (GRN) enriched in low-frequency mutated genes. Importantly, these low-frequency mutated genes were mutually exclusive with known cancer drivers. Finally, we provide evidence that gene expression analysis of these mutated GRNs can predict resistance/sensitivity to chemotherapeutic drugs for breast cancer treatment. Availability and implementation: Datasets are available at https://www.ncbi.nlm.nih.gov/geo/ and at https://www.ebi.ac.uk/ega/datasets/. Molecular signatures and GSEA software are available at http://www.gsea-msigdb.org/gsea/index.jsp. Source codes are available at https://github.com/EleonoraLusito/Reverse_Engineering_BC_GRNs. Supplementary information: Supplementary data are available at Bioinformatics online.

Circulating Cancer Biomarkers: The Macro-revolution of the Micro-RNA.

MicroRNAs (miRNAs) are small non-coding RNAs that act as master regulators of many cellular processes. The expression of miRNAs is often deregulated in human tumors, causing the alteration of molecular mechanisms relevant for cancer progression. Importantly, miRNAs are detectable in the blood and their quantity fluctuations are the hallmark of pathogenic conditions, including cancer. Several groups reported the identification of circulating cell-free miRNAs (cf-miRNAs) in the human serum and plasma and demonstrated their diagnostic and prognostic utility. Other studies also shown that it may be feasible to apply such cf-miRNA signatures within screening programs in order to improve cancer early detection. Circulating cf-miRNAs therefore appear to be excellent candidates for blood-borne cancer biomarkers.

Optimization and Standardization of Circulating MicroRNA Detection for Clinical Application: The miR-Test Case.

BACKGROUND: The identification of circulating microRNAs (miRNAs) in the blood has been recently exploited for the development of minimally invasive tests for the early detection of cancer. Nevertheless, the clinical transferability of such tests is uncertain due to still-insufficient standardization and optimization of methods to detect circulating miRNAs in the clinical setting. METHODS: We performed a series of tests to optimize the quantification of serum miRNAs that compose the miR-Test, a signature for lung cancer early detection, and systematically analyzed variables that could affect the performance of the test. We took advantage of a large-scale (>1000 samples) validation study of the miR-Test that we recently published, to evaluate, in clinical samples, the effects of analytical and preanalytical variables on the quantification of circulating miRNAs and the clinical output of the signature (risk score). RESULTS: We developed a streamlined and standardized pipeline for the processing of clinical serum samples that allows the isolation and analysis of circulating miRNAs by quantitative reverse-transcription PCR, with a throughput compatible with screening trials. The major source of analytical variation came from RNA isolation from serum, which could be corrected by use of external (spike-in) or endogenous miRNAs as a reference for normalization. We also introduced standard operating procedures and QC steps to check for unspecific fluctuations that arise from the lack of standardized criteria in the collection or handling of the samples (preanalytical factors). CONCLUSIONS: We propose our methodology as a reference for the development of clinical-grade blood tests on the basis of miRNA detection.

miR-Test: a blood test for lung cancer early detection.

Lung cancer is the leading cause of cancer death worldwide. Low-dose computed tomography screening (LDCT) was recently shown to anticipate the time of diagnosis, thus reducing lung cancer mortality. However, concerns persist about the feasibility and costs of large-scale LDCT programs. Such concerns may be addressed by clearly defining the target "high-risk" population that needs to be screened by LDCT. We recently identified a serum microRNA signature (the miR-Test) that could identify the optimal target population. Here, we performed a large-scale validation study of the miR-Test in high-risk individuals (n = 1115) enrolled in the Continuous Observation of Smoking Subjects (COSMOS) lung cancer screening program. The overall accuracy, sensitivity, and specificity of the miR-Test are 74.9% (95% confidence interval [CI] = 72.2% to 77.6%), 77.8% (95% CI = 64.2% to 91.4%), and 74.8% (95% CI = 72.1% to 77.5%), respectively; the area under the curve is 0.85 (95% CI = 0.78 to 0.92). These results argue that the miR-Test might represent a useful tool for lung cancer screening in high-risk individuals.

DEPDC1B coordinates de-adhesion events and cell-cycle progression at mitosis.

Cells entering mitosis become rounded, lose attachment to the substrate, and increase their cortical rigidity. Pivotal to these events is the dismantling of focal adhesions (FAs). How mitotic reshaping is linked to commitment to divide is unclear. Here, we show that DEPDC1B, a protein that accumulates in G2, coordinates de-adhesion events and cell-cycle progression at mitosis. DEPDC1B functions as an inhibitor of a RhoA-based signaling complex, which assembles on the FA-associated protein tyrosine phosphatase, receptor type, F (PTPRF) and mediates the integrity of FAs. By competing with RhoA for the interaction with PTPRF, DEPDC1B promotes the dismantling of FAs, which is necessary for the morphological changes preceding mitosis. The circuitry is relevant in whole organisms, as shown by the control exerted by the DEPDC1B/RhoA/PTPRF axis on mitotic dynamics during zebrafish development. Our results uncover an adhesion-dependent signaling mechanism that coordinates adhesion events with the control of cell-cycle progression.

Recessive cancer genes engage in negative genetic interactions with their functional paralogs.

Cancer genetic heterogeneity offers a wide repertoire of molecular determinants to be screened as therapeutic targets. Here, we identify potential anticancer targets by exploiting negative genetic interactions between genes with driver loss-of-function mutations (recessive cancer genes) and their functionally redundant paralogs. We identify recessive genes with additional copies and experimentally test our predictions on three paralogous pairs. We confirm digenic negative interactions between two cancer genes (SMARCA4 and CDH1) and their corresponding paralogs (SMARCA2 and CDH3). Furthermore, we identify a trigenic negative interaction between the cancer gene DNMT3A, its functional paralog DNMT3B, and a third gene, DNMT1, which encodes the only other human DNA-methylase domain. Although our study does not exclude other causes of synthetic lethality, it suggests that functionally redundant paralogs of cancer genes could be targets in anticancer therapy.

Oscillations in Cdc14 release and sequestration reveal a circuit underlying mitotic exit.

In budding yeast, the phosphatase Cdc14 orchestrates progress through anaphase and mitotic exit, thereby resetting the cell cycle for a new round of cell division. Two consecutive pathways, Cdc fourteen early anaphase release (FEAR) and mitotic exit network (MEN), contribute to the progressive activation of Cdc14 by regulating its release from the nucleolus, where it is kept inactive by Cfi1. In this study, we show that Cdc14 activation requires the polo-like kinase Cdc5 together with either Clb-cyclin-dependent kinase (Cdk) or the MEN kinase Dbf2. Once active, Cdc14 triggers a negative feedback loop that, in the presence of stable levels of mitotic cyclins, generates periodic cycles of Cdc14 release and sequestration. Similar phenotypes have been described for yeast bud formation and centrosome duplication. A common theme emerges where events that must happen only once per cycle, although intrinsically capable of oscillations, are limited to one occurrence by the cyclin-Cdk cell cycle engine.

Protein phosphatases take the mitotic stage.

Following the identification of cyclin-dependent kinases in the 1980s, kinases were hailed as the directors of mitosis. Although the action of kinases must necessarily be reversible, only recently has the involvement of specific phosphatases in mitosis become appreciated. Studies are now revealing how the timely execution of mitotic events depends on the delicate interplay between kinases and phosphatases. To date, the best-characterized mitotic phosphatases are Cdc25, that is required for entry into mitosis and Cdc14, that controls exit from mitosis in budding yeast. Recent work has now exposed the conserved serine-threonine phosphatases PP1 and PP2A as key regulators of various mitotic processes.