Identification of functional pathways and molecular signatures in neuroendocrine neoplasms by multi-omics analysis.

BACKGROUND: Neuroendocrine neoplasms (NENs) represent a heterogeneous class of rare tumors with increasing incidence. They are characterized by the ability to secrete peptide hormones and biogenic amines but other reliable biomarkers are lacking, making diagnosis and identification of the primary site very challenging. While in some NENs, such as the pancreatic ones, next generation sequencing technologies allowed the identification of new molecular hallmarks, our knowledge of the molecular profile of NENs from other anatomical sites is still poor. METHODS: Starting from the concept that NENs from different organs may be clinically and genetically correlated, we applied a multi-omics approach by combining multigene panel testing, CGH-array, transcriptome and miRNome profiling and computational analyses, with the aim to highlight common molecular and functional signatures of gastroenteropancreatic (GEP)-NENs and medullary thyroid carcinomas (MTCs) that could aid diagnosis, prognosis and therapy. RESULTS: By comparing genomic and transcriptional profiles, ATM-dependent signaling emerged among the most significant pathways at multiple levels, involving gene variations and miRNA-mediated regulation, thus representing a novel putative druggable pathway in these cancer types. Moreover, a set of circulating miRNAs was also selected as possible diagnostic/prognostic biomarkers useful for clinical management of NENs. CONCLUSIONS: These findings depict a complex molecular and functional landscape of NENs, shedding light on novel therapeutic targets and disease biomarkers to be exploited.

miR-622 is a novel potential biomarker of breast carcinoma and impairs motility of breast cancer cells through targeting NUAK1 kinase.

BACKGROUND: Aberrant expression of microRNAs (miR) has been proposed as non-invasive biomarkers for breast cancers. The aim of this study was to analyse the miR-622 level in the plasma and in tissues of breast cancer patients and to explore the role of miR-622 and its target, the NUAK1 kinase, in this context. METHODS: miR-622 expression was analysed in plasma and in tissues samples of breast cancer patients by q-RT-PCR. Bioinformatics programs, luciferase assay, public dataset analysis and functional experiments were used to uncover the role of miR-622 and its target in breast cancer cells. RESULTS: miR-622 is downregulated in plasma and in tissues of breast cancer patients respect to healthy controls and its downregulation is significantly associated with advanced grade and high Ki67 level. Modulation of miR-622 affects the motility phenotype of breast cancer cells. NUAK1 kinase is a functional target of miR-622, it is associated with poor clinical outcomes of breast cancer patients and is inversely correlated with miR-622 level. CONCLUSIONS: miR-622/NUAK1 axis is deregulated in breast cancer patients and affects the motility phenotype of breast cancer cells. Importantly, miR-622 and NUAK1 hold promises as biomarkers and as targets for breast cancers.

Prognostic and Clinicopathological Significance of MiR-155 in Breast Cancer: A Systematic Review.

There is an unmet need for novel non-invasive prognostic molecular tumour markers for breast cancer (BC). Accumulating evidence shows that miR-155 plays a pivotal role in tumorigenesis. Generally, miR-155 is considered an oncogenic miRNA promoting tumour growth, angiogenesis and aggressiveness of BC. Therefore, many researchers have focused on its use as a prognostic biomarker and therapeutic target. However, its prognostic value for BC patients remains controversial. To address this issue, the present systematic review aims to summarize the available evidence and give a picture of a prognostic significance of miR-155 in BC pathology. All eligible studies were searched on PubMed and EMBASE databases through various search strategies. Starting from 289 potential eligible records, data were examined from 28 studies, comparing tissue and circulating miR-155 expression levels with clinicopathological features and survival rates in BC patients. We discuss the pitfalls and challenges that need to be assessed to understand the power of miR-155 to respond to real clinical needs, highlighting the consistency, robustness or lack of results obtained to sate in translating this molecule to clinical practice. Our paper suggests that the prognostic role of miR-155 in the management of BC needs to be further verified.

The New Paradigm of Network Medicine to Analyze Breast Cancer Phenotypes.

Breast cancer (BC) is a heterogeneous and complex disease as witnessed by the existence of different subtypes and clinical characteristics that poses significant challenges in disease management. The complexity of this tumor may rely on the highly interconnected nature of the various biological processes as stated by the new paradigm of Network Medicine. We explored The Cancer Genome Atlas (TCGA)-BRCA data set, by applying the network-based algorithm named SWItch Miner, and mapping the findings on the human interactome to capture the molecular interconnections associated with the disease modules. To characterize BC phenotypes, we constructed protein-protein interaction modules based on "hub genes", called switch genes, both common and specific to the four tumor subtypes. Transcriptomic profiles of patients were stratified according to both clinical (immunohistochemistry) and genetic (PAM50) classifications. 266 and 372 switch genes were identified from immunohistochemistry and PAM50 classifications, respectively. Moreover, the identified switch genes were functionally characterized to select an interconnected pathway of disease genes. By intersecting the common switch genes of the two classifications, we selected a unique signature of 28 disease genes that were BC subtype-independent and classification subtype-independent. Data were validated both in vitro (10 BC cell lines) and ex vivo (66 BC tissues) experiments. Results showed that four of these hub proteins (AURKA, CDC45, ESPL1, and RAD54L) were over-expressed in all tumor subtypes. Moreover, the inhibition of one of the identified switch genes (AURKA) similarly affected all BC subtypes. In conclusion, using a network-based approach, we identified a common BC disease module which might reflect its pathological signature, suggesting a new vision to face with the disease heterogeneity.

Biobanking in health care: evolution and future directions.

BACKGROUND: The aim of the present review is to discuss how the promising field of biobanking can support health care research strategies. As the concept has evolved over time, biobanks have grown from simple biological sample repositories to complex and dynamic units belonging to large infrastructure networks, such as the Pan-European Biobanking and Biomolecular Resources Research Infrastructure (BBMRI). Biobanks were established to support scientific knowledge. Different professional figures with varied expertise collaborate to obtain and collect biological and clinical data from human subjects. At same time biobanks preserve the human and legal rights of each person that offers biomaterial for research. METHODS: A literature review was conducted in April 2019 from the online database PubMed, accessed through the Bibliosan platform. Four primary topics related to biobanking will be discussed: (i) evolution, (ii) bioethical issues, (iii) organization, and (iv) imaging. RESULTS: Most biobanks were founded as local units to support specific research projects, so they evolved in a decentralized manner. The consequence is an urgent needing for procedure harmonization regarding sample collection, processing, and storage. Considering the involvement of biomaterials obtained from human beings, different ethical issues such as the informed consent model, sample ownership, veto rights, and biobank sustainability are debated. In the face of these methodological and ethical challenges, international organizations such as BBMRI play a key role in supporting biobanking activities. Finally, a unique development is the creation of imaging biobanks that support the translation of imaging biomarkers (identified using a radiomic approach) into clinical practice by ensuring standardization of data acquisition and analysis, accredited technical validation, and transparent sharing of biological and clinical data. CONCLUSION: Modern biobanks permit large-scale analysis for individuation of specific diseases biomarkers starting from biological or digital material (i.e., bioimages) with well-annotated clinical and biological data. These features are essential for improving personalized medical approaches, where effective biomarker identification is a critical step for disease diagnosis and prognosis.

A multi-parametric PET/MRI study of breast cancer: Evaluation of DCE-MRI pharmacokinetic models and correlation with diffusion and functional parameters.

46 patients with histologically confirmed breast cancer were enrolled and imaged with a 3T hybrid PET/MRI system, at staging. Diffusion, functional and perfusion parameters (measured by Tofts and shutter speed models) were compared. Results showed a good correlation between pharmacokinetic parameters and the SUV.

Relationship between functional imaging and immunohistochemical markers and prediction of breast cancer subtype: a PET/MRI study.

PURPOSE: The aim of this study was to determine if functional parameters extracted from the hybrid positron emission tomography/magnetic resonance imaging (PET/MRI) correlate with the immunohistochemical markers of breast cancer (BC) lesions, to assess their ability to predict BC subtype. METHODS: This prospective study was approved by the institution's Ethics Committee, and all patients provided written informed consent. A total of 50 BC patients at diagnosis underwent PET/MRI before pharmacological and surgical treatment. For each primary lesion, the following data were extracted: morphological data including tumour-node-metastasis stage and lesion size; apparent diffusion coefficient (ADC); perfusion data including forward volume transfer constant (Ktrans), reverse efflux volume transfer constant (Kep) and extravascular extracellular space volume (Ve); and metabolic data including standardized uptake value (SUV), lean body mass (SUL), metabolic tumour volume and total lesion glycolysis. Immunohistochemical reports were used to determine receptor status (oestrogen, progesterone, and human epidermal growth factor receptor 2), cellular differentiation status (grade), and proliferation index (Ki67) of the tumour lesions. Correlation studies (Mann-Whitney U test and Spearman's test), receiver operating characteristic (ROC) curve analysis, and multivariate analysis were performed. RESULTS: Association studies were performed to assess the correlations between imaging and histological prognostic markers of BC. Imaging biomarkers, which significantly correlated with biological markers, were selected to perform ROC curve analysis to determine their ability to discriminate among BC subtypes. SUVmax, SUVmean and SUL were able to discriminate between luminal A and luminal B subtypes (AUCSUVmean = 0.799; AUCSUVmax = 0.833; AUCSUL = 0.813) and between luminal A and nonluminal subtypes (AUCSUVmean = 0.926; AUCSUVmax = 0.917; AUCSUL = 0.945), and the lowest SUV and SUL values were associated with the luminal A subtype. Kepmax was able to discriminate between luminal A and luminal B subtypes (AUC = 0.779), and its highest values were associated with the luminal B subtype. Ktransmax (AUC = 0.881) was able to discriminate between luminal A and nonluminal subtypes, and the highest perfusion values were associated with the nonluminal subtype. In addition, ADC (AUC = 0.877) was able to discriminate between luminal B and nonluminal subtypes, and the lowest ADCmean values were associated with the luminal B subtype. Multivariate analysis was performed to develop a prognostic model, and the best predictive model included Ktransmax and SUVmax parameters. CONCLUSION: Using multivariate analysis of both PET and MRI parameters, a prognostic model including Ktransmax and SUVmax was able to predict the tumour subtype in 38 of 49 patients (77.6%, p < 0.001), with higher accuracy for the luminal B subtype (86.2%).

Postprandial Gastrointestinal Function Differs after Acute Administration of Sourdough Compared with Brewer's Yeast Bakery Products in Healthy Adults.

Background: Europeans consume large quantities of bakery products, although these are known as one of the food categories that potentially leads to postprandial symptoms (such as fullness and bloating). Objective: The aim of this study was to evaluate the effects of sourdough baked goods on gastric emptying and gastrointestinal fermentation and symptoms in healthy people. Methods: In a double-blind, randomized crossover study, 2 sourdough croissants (SCs) or 2 brewer's yeast croissants (BCs) were served as single meals to 17 healthy adults [9 women; age range: 18-40 y; body mass index range (in kg/m2): 18-24]. Gastric volume (GV) was evaluated by magnetic resonance to calculate gastric-emptying rate in the 3-h interval after croissant ingestion. A hydrogen breath test was performed to measure hydrogen production after SC and BC ingestion. Palatability and postprandial gastrointestinal symptoms (discomfort, nausea, fullness, and bloating) over a 4-h period after the meal were evaluated. The area under the curve (AUC) was used to evaluate the overall effects on all variables tested. Results: The total GV AUC was reduced by 11% during the 3 h after the consumption of SCs compared with BCs (P = 0.02). Hydrogen production during the 4-h interval after ingestion of SCs was 30% lower than after BCs (P = 0.03). SCs were rated as being >2 times as palatable as BCs (P < 0.001). The overall severity of postprandial symptoms was 36% lower during the 4 h after intake of SCs compared with BCs (P = 0.05). Conclusion: Sourdough bakery products could promote better postprandial gastrointestinal function in healthy adults and be more acceptable than those prepared with brewer's yeast. This trial was registered at www.clinicaltrials.gov as NCT03207516.

Transcription factor PREP1 induces EMT and metastasis by controlling the TGF-ß-SMAD3 pathway in non-small cell lung adenocarcinoma.

Pre-B-cell leukemia homeobox (Pbx)-regulating protein-1 (Prep1) is a ubiquitous homeoprotein involved in early development, genomic stability, insulin sensitivity, and hematopoiesis. Previously we have shown that Prep1 is a haploinsufficient tumor suppressor that inhibits neoplastic transformation by competing with myeloid ecotropic integration site 1 for binding to the common heterodimeric partner Pbx1. Epithelial-mesenchymal transition (EMT) is controlled by complex networks of proinvasive transcription factors responsive to paracrine factors such as TGF-ß. Here we show that, in addition to inhibiting primary tumor growth, PREP1 is a novel EMT inducer and prometastatic transcription factor. In human non-small cell lung cancer (NSCLC) cells, PREP1 overexpression is sufficient to trigger EMT, whereas PREP1 down-regulation inhibits the induction of EMT in response to TGF-ß. PREP1 modulates the cellular sensitivity to TGF-ß by inducing the small mothers against decapentaplegic homolog 3 (SMAD3) nuclear translocation through mechanisms dependent, at least in part, on PREP1-mediated transactivation of a regulatory element in the SMAD3 first intron. Along with the stabilization and accumulation of PBX1, PREP1 induces the expression of multiple activator protein 1 components including the proinvasive Fos-related antigen 1 (FRA-1) oncoprotein. Both FRA-1 and PBX1 are required for the mesenchymal changes triggered by PREP1 in lung tumor cells. Finally, we show that the PREP1-induced mesenchymal transformation correlates with significantly increased lung colonization by cells overexpressing PREP1. Accordingly, we have detected PREP1 accumulation in a large number of human brain metastases of various solid tumors, including NSCLC. These findings point to a novel role of the PREP1 homeoprotein in the control of the TGF-ß pathway, EMT, and metastasis in NSCLC.

Radiogenomic Analysis of Oncological Data: A Technical Survey.

In the last few years, biomedical research has been boosted by the technological development of analytical instrumentation generating a large volume of data. Such information has increased in complexity from basic (i.e., blood samples) to extensive sets encompassing many aspects of a subject phenotype, and now rapidly extending into genetic and, more recently, radiomic information. Radiogenomics integrates both aspects, investigating the relationship between imaging features and gene expression. From a methodological point of view, radiogenomics takes advantage of non-conventional data analysis techniques that reveal meaningful information for decision-support in cancer diagnosis and treatment. This survey is aimed to review the state-of-the-art techniques employed in radiomics and genomics with special focus on analysis methods based on molecular and multimodal probes. The impact of single and combined techniques will be discussed in light of their suitability in correlation and predictive studies of specific oncologic diseases.

Phosphorylation-regulated degradation of the tumor-suppressor form of PED by chaperone-mediated autophagy in lung cancer cells.

PED/PEA-15 is a death effector domain (DED) family member with a variety of effects on cell growth and metabolism. To get further insight into the role of PED in cancer, we aimed to find new PED interactors. Using tandem affinity purification, we identified HSC70 (Heat Shock Cognate Protein of 70 kDa)-which, among other processes, is involved in chaperone-mediated autophagy (CMA)-as a PED-interacting protein. We found that PED has two CMA-like motifs (i.e., KFERQ), one of which is located within a phosphorylation site, and demonstrate that PED is a bona fide CMA substrate and the first example in which phosphorylation modifies the ability of HSC70 to access KFERQ-like motifs and target the protein for lysosomal degradation. Phosphorylation of PED switches its function from tumor suppression to tumor promotion, and we show that HSC70 preferentially targets the unphosphorylated form of PED to CMA. Therefore, we propose that the up-regulated CMA activity characteristic of most types of cancer cell enhances oncogenesis by shifting the balance of PED function toward tumor promotion. This mechanism is consistent with the notion of a therapeutic potential for targeting CMA in cancer, as inhibition of this autophagic pathway may help restore a physiological ratio of PED forms.

CA15-3 is a useful serum tumor marker for diagnostic integration of hybrid positron emission tomography with integrated computed tomography during follow-up of breast cancer patients.

BACKGROUND: The aim of this study was to evaluate the value of CA15-3 for the diagnostic integration of molecular imaging findings performed with hybrid positron emission tomography and computed tomography (PETCT) technology. METHODS: We retrospectively selected 45 patients with a median age of 60 years (range 39-85 years) and a previous history of breast cancer (BC) who had already been treated with surgery and other treatments. Three measurements of CA15-3 were collected within 1 year before PETCT examination, at 6-9 months 3-6 months and 0-3 months before PETCT. The prolonged clinical outcome or imaging follow-up was used to define disease relapse. An increase in tumor marker value was compared with PETCT findings and disease relapse. Sensitivity and specificity for both tests were calculated with respect to clinical outcome. RESULTS: Disease relapse was detected in 16 out of 45 BC patients. CA15-3 and PETCT showed 75% sensitivity with a specificity percentage of 76% for CA15-3 and 79% for PETCT. Serum CA15-3 expression levels were significantly higher in BC patients with multiple metastatic sites with hepatic involvement. Analysis of serial CA15-3 serum levels showed an increase in CA15-3 3-6 months before PETCT could identify BC patients at risk for relapse (AUC = 0.81). Moreover, patients receiving anti-hormonal or chemotherapy medications with negative PETCT and positive CA15-3 relapsed after a median time of 158 days compared to patients who were negative for both tests and who were free from disease for at least 1 year. CONCLUSIONS: Our results showed that serial increases in CA15-3 can be used to predict positive PETCT results in BC patients during follow-up. Increased levels of CA15-3 may be considered an early warning sign in patients needing accurate molecular imaging investigations, as they are at higher risk of recurrence. In cases of elevated levels, multiple lesions or liver involvement may exist. Also, patients receiving chemotherapeutic or anti-hormonal treatment who have negative PETCT scans and increased CA15-3 serum levels should be considered at risk for relapse, because the CA15-3-linked biochemical signal of the presence of a tumor can predict positive metabolic imaging.

An Unclassified Deletion Involving the Proximal Short Arm of Chromosome 10: A New Syndrome?

To date, only 13 studies have described patients with large overlapping deletions of 10p11.2-p12. These individuals shared a common phenotype characterized by intellectual disability, developmental delay, distinct facial dysmorphic features, abnormal behaviour, visual impairment, cardiac malformation, and cryptorchidism in males. Molecular cytogenetic analysis revealed that the deletion in this chromosomal region shares a common smallest region of overlap (SRO) of 80 kb, which contains only the WAC gene (WW-domain-containing adaptor with coiled coil). In this clinical case report, we report a 5-year-old girl, born from non-consanguineous parents, with a 10p11.22p11.21 microdeletion. She presents clinical features that overlap with other patients described in the literature, such as dysmorphic traits, speech delay, and behavioural abnormalities (hyperactivity), even though the WAC gene is not involved in the microdeletion. Our results are the first to highlight that the deletion described here represents a contiguous gene syndrome that is enough to explain the distinct phenotype but partially overlaps with the previous cases reported in the literature, even though the same genes are not involved. In particular, in this study, we speculate about the role of the WAC gene that seems to be associated with normal motor development. In fact, we found that our patient is the only one described in the literature with a large deletion in the 10p11.22p11.21 region without the involvement of the WAC gene deletion, and, interestingly, the patient did not have motor delay.

Urinary miRNAs as a Diagnostic Tool for Bladder Cancer: A Systematic Review.

Bladder cancer is the 10th most common cancer type worldwide. Cystoscopy represents the gold standard for bladder cancer diagnosis, but this procedure is invasive and painful, hence the need to identify new biomarkers through noninvasive procedures. microRNAs (miRNAs) are considered to be promising diagnostic molecules, because they are very stable in biological fluids (including urine) and easily detectable. This systematic review analyses the power of urine miRNAs as bladder cancer diagnostic markers. We conducted this systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A total of 293 records related to miRNAs and their diagnostic significance in BC were retrieved from the PubMed and Embase databases. A systematic search of the literature was performed, and a total of 25 articles (N = 4054 participants) were identified and reviewed. Although many of the selected studies were of high scientific quality, the results proved to be quite heterogeneous, because we did not identify a univocal consensus for a specific miRNA signature but only isolated the signatures. We did not identify a univocal consensus for a specific diagnostic miRNA signature but only isolated the signatures, some of them with better diagnostic power compared to the others.

Discovering Common miRNA Signatures Underlying Female-Specific Cancers via a Machine Learning Approach Driven by the Cancer Hallmark ERBB.

Big data processing, using omics data integration and machine learning (ML) methods, drive efforts to discover diagnostic and prognostic biomarkers for clinical decision making. Previously, we used the TCGA database for gene expression profiling of breast, ovary, and endometrial cancers, and identified a top-scoring network centered on the ERBB2 gene, which plays a crucial role in carcinogenesis in the three estrogen-dependent tumors. Here, we focused on microRNA expression signature similarity, asking whether they could target the ERBB family. We applied an ML approach on integrated TCGA miRNA profiling of breast, endometrium, and ovarian cancer to identify common miRNA signatures differentiating tumor and normal conditions. Using the ML-based algorithm and the miRTarBase database, we found 205 features and 158 miRNAs targeting ERBB isoforms, respectively. By merging the results of both databases and ranking each feature according to the weighted Support Vector Machine model, we prioritized 42 features, with accuracy (0.98), AUC (0.93-95% CI 0.917-0.94), sensitivity (0.85), and specificity (0.99), indicating their diagnostic capability to discriminate between the two conditions. In vitro validations by qRT-PCR experiments, using model and parental cell lines for each tumor type showed that five miRNAs (hsa-mir-323a-3p, hsa-mir-323b-3p, hsa-mir-331-3p, hsa-mir-381-3p, and hsa-mir-1301-3p) had expressed trend concordance between breast, ovarian, and endometrium cancer cell lines compared with normal lines, confirming our in silico predictions. This shows that an integrated computational approach combined with biological knowledge, could identify expression signatures as potential diagnostic biomarkers common to multiple tumors.

In silico recognition of a prognostic signature in basal-like breast cancer patients.

BACKGROUND: Triple-negative breast cancers (TNBCs) display poor prognosis, have a high risk of tumour recurrence, and exhibit high resistance to drug treatments. Based on their gene expression profiles, the majority of TNBCs are classified as basal-like breast cancers. Currently, there are not available widely-accepted prognostic markers to predict outcomes in basal-like subtype, so the selection of new prognostic indicators for this BC phenotype represents an unmet clinical challenge. RESULTS: Here, we attempted to address this challenging issue by exploiting a bioinformatics pipeline able to integrate transcriptomic, genomic, epigenomic, and clinical data freely accessible from public repositories. This pipeline starts from the application of the well-established network-based SWIM methodology on the transcriptomic data to unveil important (switch) genes in relation with a complex disease of interest. Then, survival and linear regression analyses are performed to associate the gene expression profiles of the switch genes with both the patients' clinical outcome and the disease aggressiveness. This allows us to identify a prognostic gene signature that in turn is fed to the last step of the pipeline consisting of an analysis at DNA level, to investigate whether variations in the expression of identified prognostic switch genes could be related to genetic (copy number variations) or epigenetic (DNA methylation differences) alterations in their gene loci, or to the activities of transcription factors binding to their promoter regions. Finally, changes in the protein expression levels corresponding to the so far identified prognostic switch genes are evaluated by immunohistochemical staining results taking advantage of the Human Protein Atlas. CONCLUSION: The application of the proposed pipeline on the dataset of The Cancer Genome Atlas (TCGA)-Breast Invasive Carcinoma (BRCA) patients affected by basal-like subtype led to an in silico recognition of a basal-like specific gene signature composed of 11 potential prognostic biomarkers to be further investigated.

A Complex Radiomic Signature in Luminal Breast Cancer from a Weighted Statistical Framework: A Pilot Study.

Radiomics is rapidly advancing in precision diagnostics and cancer treatment. However, there are several challenges that need to be addressed before translation to clinical use. This study presents an ad-hoc weighted statistical framework to explore radiomic biomarkers for a better characterization of the radiogenomic phenotypes in breast cancer. Thirty-six female patients with breast cancer were enrolled in this study. Radiomic features were extracted from MRI and PET imaging techniques for malignant and healthy lesions in each patient. To reduce within-subject bias, the ratio of radiomic features extracted from both lesions was calculated for each patient. Radiomic features were further normalized, comparing the z-score, quantile, and whitening normalization methods to reduce between-subjects bias. After feature reduction by Spearman's correlation, a methodological approach based on a principal component analysis (PCA) was applied. The results were compared and validated on twenty-seven patients to investigate the tumor grade, Ki-67 index, and molecular cancer subtypes using classification methods (LogitBoost, random forest, and linear discriminant analysis). The classification techniques achieved high area-under-the-curve values with one PC that was calculated by normalizing the radiomic features via the quantile method. This pilot study helped us to establish a robust framework of analysis to generate a combined radiomic signature, which may lead to more precise breast cancer prognosis.

SARS-CoV-2 antibody responses before and after a third dose of the BNT162b2 vaccine in Italian healthcare workers aged ≤60 years: One year of surveillance.

This study monitored the anti-spike-receptor-binding domain (RBD) and neutralizing antibodies induced by the Pfizer/BioNTech mRNA BNT162b2 vaccine in a cohort of 163 healthcare workers aged ≤60 years. We have taken advantage of two study groups, both of whom received the first two doses in the same time window, but Group 1 (54 HCWs) received the third dose 2 months before Group 2 (68 HCWs) did. The cohorts were monitored from the 12th day after the first vaccine dose up to 1 month after the third vaccine dose for a total of eight time points and about 1 year of surveillance (T1 = 12 days after the first dose; T2 = 10 days after the second dose; T3 = 1 month after the second dose; T4 = 3 months after the second dose; T5 = 4 months after the second dose; T6 = 5 months after the second dose; T7 = 7 months after the second dose; T8 = 1 month after the third dose for Group 1; T8* = 9 months after the second dose for Group 2; T9 = 1 month after the third dose for Group 2). The mean value of anti-spike antibodies decreased faster over time, but at T7, its decline was significantly slowed (T7 vs. T8*). After the third dose, the anti-spike titer rose about 34-fold (T7 vs. T8 and T8* vs. T9) and the booster improved the anti-spike titer by about three times compared with that of the second dose (T3 vs. T8 and T3 vs. T9), and no difference was noted between the two groups. The neutralizing titer was evaluated at T3, T7, T8, and T9. Anti-spike and neutralizing antibodies were found to be strongly correlated (r2 = 0.980; p < 0.001). At T3, 70% of the participants had a neutralizing antibody titer >91% of total anti-spike antibodies that increased to 90% after the third dose (T8 and T9). However, when the anti-spike titer reached its lowest value (T7), the neutralizing antibody levels decreased even further, representing only 44% of total anti-spike antibodies (p < 0.0001). Our findings show that the third vaccine dose improves the humoral response, but the wane of the anti-spike and neutralizing antibody titers over time is more marked in the neutralizing antibodies.

miRNA-Based Therapeutics in Breast Cancer: A Systematic Review.

BACKGROUND: Breast cancer (BC) is the most common cancer in females and despite advances in treatment, it represents the leading cause of cancer mortality in women worldwide. Conventional therapeutic modalities have significantly improved the management of BC patients, but subtype heterogeneity, drug resistance, and tumor relapse remain the major factors to hamper the effectiveness of therapy for BC. In this scenario, miRNA(miR)-based therapeutics offer a very attractive area of study. However, the use of miR-based therapeutics for BC treatment still represents an underdeveloped topic. Therefore, this systematic review aims at summarizing current knowledge on promising miR-based therapeutics for BC exploring original articles focusing on in vivo experiments. METHODS: The current systematic review was performed according to PRISMA guidelines. PubMed and EMBASE databases were comprehensively explored to perform the article search. RESULTS: Twenty-one eligible studies were included and analyzed: twelve focused on antitumor miR-based therapeutics and nine on metastatic miR-based therapeutics. We found 18 different miRs tested as potential therapeutic molecules in animal model experiments. About 90% of the selected studies evaluate the efficiency and the safety of miRs as therapeutic agents in triple-negative (TN)-BC mouse models. Among all founded miR-based therapeutics, miR-21 emerged to be the most investigated and proposed as a potential antitumoral molecule for TNBC treatment. Besides, miR-34a and miR-205a appeared to be successful antitumoral and antimetastatic molecules. CONCLUSIONS: Our analysis provides a snapshot of the current scenario regarding the miRs as therapeutic molecules in BC. Nevertheless, despite many efforts, none of the selected studies goes beyond preclinical studies, and their translatability in the clinical practice seems quite premature.

An Integrative Computational Approach Based on Expression Similarity Signatures to Identify Protein-Protein Interaction Networks in Female-Specific Cancers.

Breast, ovarian, and endometrial cancers have a major impact on mortality in women. These tumors share hormone-dependent mechanisms involved in female-specific cancers which support tumor growth in a different manner. Integrated computational approaches may allow us to better detect genomic similarities between these different female-specific cancers, helping us to deliver more sophisticated diagnosis and precise treatments. Recently, several initiatives of The Cancer Genome Atlas (TCGA) have encouraged integrated analyses of multiple cancers rather than individual tumors. These studies revealed common genetic alterations (driver genes) even in clinically distinct entities such as breast, ovarian, and endometrial cancers. In this study, we aimed to identify expression similarity signatures by extracting common genes among TCGA breast (BRCA), ovarian (OV), and uterine corpus endometrial carcinoma (UCEC) cohorts and infer co-regulatory protein-protein interaction networks that might have a relationship with the estrogen signaling pathway. Thus, we carried out an unsupervised principal component analysis (PCA)-based computational approach, using RNA sequencing data of 2,015 female cancer and 148 normal samples, in order to simultaneously capture the data heterogeneity of intertumors. Firstly, we identified tumor-associated genes from gene expression profiles. Secondly, we investigated the signaling pathways and co-regulatory protein-protein interaction networks underlying these three cancers by leveraging the Ingenuity Pathway Analysis software. In detail, we discovered 1,643 expression similarity signatures (638 downregulated and 1,005 upregulated genes, with respect to normal phenotype), denoted as tumor-associated genes. Through functional genomic analyses, we assessed that these genes were involved in the regulation of cell-cycle-dependent mechanisms, including metaphase kinetochore formation and estrogen-dependent S-phase entry. Furthermore, we generated putative co-regulatory protein-protein interaction networks, based on upstream regulators such as the ERBB2/HER2 gene. Moreover, we provided an ad-hoc bioinformatics workflow with a manageable list of intertumor expression similarity signatures for the three female-specific cancers. The expression similarity signatures identified in this study might uncover potential estrogen-dependent molecular mechanisms promoting carcinogenesis.