The EGFR Signaling Modulates in Mesenchymal Stem Cells the Expression of miRNAs Involved in the Interaction with Breast Cancer Cells.

We previously demonstrated that the epidermal growth factor receptor (EGFR) modulates in mesenchymal stem cells (MSCs) the expression of a number of genes coding for secreted proteins that promote breast cancer progression. However, the role of the EGFR in modulating in MSCs the expression of miRNAs potentially involved in the progression of breast cancer remains largely unexplored. Following small RNA-sequencing, we identified 36 miRNAs differentially expressed between MSCs untreated or treated with the EGFR ligand transforming growth factor α (TGFα), with a fold change (FC) < 0.56 or FC ≥ 1.90 (CI, 95%). KEGG analysis revealed a significant enrichment in signaling pathways involved in cancer development and progression. EGFR activation in MSCs downregulated the expression of different miRNAs, including miR-23c. EGFR signaling also reduced the secretion of miR-23c in conditioned medium from MSCs. Functional assays demonstrated that miR-23c acts as tumor suppressor in basal/claudin-low MDA-MB-231 and MDA-MB-468 cells, through the repression of IL-6R. MiR-23c downregulation promoted cell proliferation, migration and invasion of these breast cancer cell lines. Collectively, our data suggested that the EGFR signaling regulates in MSCs the expression of miRNAs that might be involved in breast cancer progression, providing novel information on the mechanisms that regulate the MSC-tumor cell cross-talk.

Challenges in bioinformatics approaches to tumor mutation burden analysis.

Several immune checkpoint inhibitors (ICIs) have already been introduced into clinical practice or are in advanced phases of clinical experimentation. Extensive efforts are being made to identify robust biomarkers to select patients who may benefit from treatment with ICIs. Tumor mutation burden (TMB) may be a relevant biomarker of response to ICIs in different tumor types; however, its clinical use is challenged by the analytical methods required for its evaluation. The possibility of using targeted next-generation sequencing panels has been investigated as an alternative to the standard whole exome sequencing approach. However, no standardization exists in terms of genes covered, types of mutations included in the estimation of TMB, bioinformatics pipelines for data analysis, and cut-offs used to discriminate samples with high, intermediate or low TMB. Bioinformatics serve a relevant role in the analysis of targeted sequencing data and its standardization is essential to deliver a reliable test in clinical practice. In the present study, cultured and formalin-fixed, paraffin-embedded cell lines were analyzed using a commercial panel for TMB testing; the results were compared with data from the literature and public databases, demonstrating a good correlation. Additionally, the correlation between high tumor mutation burden and microsatellite instability was confirmed. The bioinformatics analyses were conducted using two different pipelines to highlight the challenges associated with the development of an appropriate analytical workflow.

SARS-CoV-2 complete genome sequencing from the Italian Campania region using a highly automated next generation sequencing system.

BACKGROUND: Since the first complete genome sequencing of SARS-CoV-2 in December 2019, more than 550,000 genomes have been submitted into the GISAID database. Sequencing of the SARS-CoV-2 genome might allow identification of variants with increased contagiousness, different clinical patterns and/or different response to vaccines. A highly automated next generation sequencing (NGS)-based method might facilitate an active genomic surveillance of the virus. METHODS: RNA was extracted from 27 nasopharyngeal swabs obtained from citizens of the Italian Campania region in March-April 2020 who tested positive for SARS-CoV-2. Following viral RNA quantification, sequencing was performed using the Ion AmpliSeq SARS-CoV-2 Research Panel on the Genexus Integrated Sequencer, an automated technology for library preparation and sequencing. The SARS-CoV-2 complete genomes were built using the pipeline SARS-CoV-2 RECoVERY (REconstruction of COronaVirus gEnomes & Rapid analYsis) and analysed by IQ-TREE software. RESULTS: The complete genome (100%) of SARS-CoV-2 was successfully obtained for 21/27 samples. In particular, the complete genome was fully sequenced for all 15 samples with high viral titer (> 200 copies/µl), for the two samples with a viral genome copy number < 200 but greater than 20, and for 4/10 samples with a viral load < 20 viral copies. The complete genome sequences classified into the B.1 and B.1.1 SARS-CoV-2 lineages. In comparison to the reference strain Wuhan-Hu-1, 48 total nucleotide variants were observed with 26 non-synonymous substitutions, 18 synonymous and 4 reported in untranslated regions (UTRs). Ten of the 26 non-synonymous variants were observed in ORF1ab, 7 in S, 1 in ORF3a, 2 in M and 6 in N genes. CONCLUSIONS: The Genexus system resulted successful for SARS-CoV-2 complete genome sequencing, also in cases with low viral copies. The use of this highly automated system might facilitate the standardization of SARS-CoV-2 sequencing protocols and make faster the identification of novel variants during the pandemic.

Targeted sequencing analysis of cell-free DNA from metastatic non-small-cell lung cancer patients: clinical and biological implications.

BACKGROUND: Sequencing artifacts, clonal hematopoietic mutations of indeterminate potential (CHIP) and tumor heterogeneity have been hypothesized to contribute to the low concordance between tissue and cell-free DNA (cfDNA) molecular profiling with targeted sequencing. METHODS: We analyzed by targeted sequencing cfDNA from 30 healthy individuals, and cfDNA and matched tumor samples from 30 EGFR-mutant and 77 EGFR wild-type metastatic non-small-cell lung cancer (mNSCLC) patients. Discordant cases were solved by droplet digital PCR (ddPCR). RESULTS: By testing cfDNA from healthy donors, we developed an algorithm to recognize sequencing artifacts. Applying this method to cfDNA from mNSCLC patients, EGFR mutations were detected with a good sensitivity (76.7%) and specificity (97.4%). In contrast, sensitivity and specificity for KRAS variants were 61.5% and 93.8%, respectively. All EGFR and KRAS variants detected in plasma but not in tissue were confirmed by ddPCR, thus excluding sequencing artifacts. In a fraction of cases, KRAS mutations found in plasma samples were confirmed in tumor tissue suggesting tumor heterogeneity. KRAS variants were found to be more likely sub-clonal as compared with EGFR mutations, and a correlation between clonal origin and frequency of detection in plasma was found. In a case with both EGFR and KRAS variants in cfDNA, we could demonstrate the presence of the KRAS variant in tumor tissue associated with lack of response to tyrosine kinase inhibitors (TKIs). CONCLUSIONS: Although sequencing artifacts can be identified in targeted sequencing of cfDNA, tumor heterogeneity and CHIP are likely to influence the concordance between plasma and tissue testing.

The role of circulating free DNA in the management of NSCLC.

INTRODUCTION: Circulating cell-free DNA (cfDNA) testing has emerged as an alternative to tumor tissue analyses for the management of metastatic non-small-cell lung cancer (NSCLC) patients. Analysis of cfDNA is a minimally invasive procedure that might better reflect tumor heterogeneity and allows repeated testing over the time. Areas covered: This review article covers the different applications of cfDNA testing in NSCLC: early diagnosis of the disease; detection of minimal residual disease in early lung cancer; identification of predictive and prognostic markers in advanced NSCLC patients; monitoring the response to therapy; assessment of tumor mutation burden. Expert commentary: The use of liquid biopsy is rapidly expanding to different applications. The combination of different circulating biomarkers (cfDNA, protein, miRNA) might improve the sensitivity and specificity of this approach in patients with low tumor burden. cfDNA testing is representing a valid source for molecular profiling in management of metastatic NSCLC patients and is providing important knowledge on tumor heterogeneity. Clinical trials are needed in order to transfer the information deriving from liquid biopsy testing in new therapeutic strategies.

Measuring tumor mutation burden in non-small cell lung cancer: tissue versus liquid biopsy.

The introduction in the clinic of immune checkpoint inhibitors (IOs) has represented an important improvement for the treatment of patients with advanced non-small cell lung cancer (NSCLC). These drugs have shown a higher activity as compared with chemotherapy in both first- and second-line of treatment, with some patients experiencing a long-lasting response. More recently, combinations of IOs have entered clinical trials in different tumor types including NSCLC. Nevertheless, IOs are active only in a subgroup of patients and biomarkers for appropriate patients' selection are urgently needed to offer the patients an effective therapy, and also to manage the costs. Tumor mutation burden (TMB) has powerfully emerged as a potential biomarker for immunotherapy and might enter the clinic in the next months, although different challenges are still unsolved. Different methods exist to evaluate TMB in tissue, ranging from whole exome sequencing (WES) to targeted sequencing of smaller sets of genes, which need to be fully standardized to ensure that patients receive an appropriate TMB test with clear clinical interpretation. In addition, as already happened for the implementation of liquid biopsy testing from NSCLC patients to identify targetable alterations, researchers are also evaluating the possibility to calculate TMB in blood, to further enlarge the number of NSCLC patients who may benefit from immunotherapy. Preliminary data highlight the difficulty to develop targeted sequencing panels for the assessment of TMB starting from the circulating cell free DNA (cfDNA). The applicability of TMB testing on liquid biopsy needs further investigation and may be clarified within the ongoing clinical trials.

Human lung adenocarcinoma cell cultures derived from malignant pleural effusions as model system to predict patients chemosensitivity.

BACKGROUND: Lung cancer is the leading cause of cancer related deaths and Malignant Pleural Effusion (MPE) is a frequent complication. Current therapies suffer from lack of efficacy in a great percentage of cases, especially when cancer is diagnosed at a late stage. Moreover patients' responses vary and the outcome is unpredictable. Therefore, the identification of patients who will benefit most of chemotherapy treatment is important for accurate prognostication and better outcome. In this study, using malignant pleural effusions (MPE) from non-small cell lung cancer (NSCLC) patients, we established a collection of patient-derived Adenocarcinoma cultures which were characterized for their sensitivity to chemotherapeutic drugs used in the clinical practice. METHODS: Tumor cells present in MPEs of patients with NSCLC were isolated by density gradient centrifugation, placed in culture and genotyped by next generation sequencing. In a subset of cases patient derived xenografts (PDX) were obtained upon tumor cell inoculation in rag2/IL2 knock-out mice. Isolated primary cultures were characterized and tested for drug sensitivity by in vitro proliferation assays. Additivity, antagonism or synergy for combinatorial treatments were determined by analysis with the Calcusyn software. RESULTS: We have optimized isolation procedures and culture conditions to expand in vitro primary cultures from Malignant Pleural Effusions (MPEs) of patients affected by lung adenocarcinomas, the most frequent form of non small cell lung cancer. Using this approach we have been able to establish 16 primary cultures from MPEs. Cells were banked at low passages and were characterized for their mutational pattern by next generation sequencing for most common driver mutations in lung cancer. Moreover, amplified cultures were shown to engraft with high efficiency when injected in immunocompromised mice. Cancer cell sensitivity to drugs used in standard chemotherapy regimens was assessed either individually or in combination. Differential chemosensitivity and different mutation profiles were observed which suggests that this isolation method could provide a platform for predicting the efficacy of chemotherapy in the clinical setting. Most importantly for six patients it was possible to establish a correlation between drug response in vitro and response to therapy in the clinic. CONCLUSIONS: Results obtained using primary cultured cells from MPEs underscore the heterogeneity of NSCLC in advanced stage as indicated by drug response and mutation profile. Comparison of data obtained from in vitro assays with patients' responses to therapy leads to the conclusion that this strategy may provide a potentially useful approach for evaluating individual chemosensitivity profile and tailor the therapy accordingly. Furthermore, combining MPE-derived primary cultures with their genomic testing allows to identify patients eligible to trials with novel targeted agents.

The gene expression profiling of hepatocellular carcinoma by a network analysis approach shows a dominance of intrinsically disordered proteins (IDPs) between hub nodes.

We have analyzed the transcriptomic data from patients with hepatocellular carcinoma (HCC) after viral HCV infection at the various stages of the disease by means of a networking analysis using the publicly available E-MTAB-950 dataset. The data was compared with those obtained in our group from HepG2 cells, a cancer cell line that lacks the viral infection. By sequential pruning of data, and also taking into account the data from cells of healthy patients as blanks, we were able to obtain a distribution of hub genes for the various stages that characterize the disease and finally, we isolated a metabolic sub-net specific to HCC alone. The general picture is that the basic organization to energetically and metabolically sustain the cells in both the normal and diseased conditions is the same, but a complex cluster of sub-networks controlled by hub genes drives the HCC progression with high metabolic flexibility and plasticity. In particular, we have extracted a sub-net of genes strictly correlated to other hub genes of the network from HepG2 cells, but specific for the HCC and mainly devoted to: (i) control at chromatin levels of cell division; (ii) control of ergastoplasmatic stress through protein degradation and misfolding; (iii) control of the immune response also through an increase of mature T-cells in the thymus. This sub-net is characterized by 26 hub genes coding for intrinsically disordered proteins with a high ability to interact with numerous molecular partners. Moreover, we have also noted that periphery molecules, that is, with one or very few interactions (e.g., cytokines or post-translational enzymes), which do not have a central role in the clusters that make up the global metabolic network, essentially have roles as information transporters. The results evidence a strong presence of intrinsically disordered proteins with key roles as hubs in the sub-networks that characterize the various stages of the disease, conferring a structural plasticity to the net nodes but an inherent functional versatility to the whole metabolic net. Thus, our present article provides a novel way of targeting the intrinsic disorder in HCC networks to dampen the cancer effects and provides new insight into the potential mechanisms of HCC. Taken together, the present findings suggest novel targets to design strategies for drug design and may support a rational intervention in the pharmacotherapy of HCC and other associated diseases.

Structure-fluctuation-function relationships of seven pro-angiogenic isoforms of VEGFA, important mediators of tumorigenesis.

Vascular endothelial growth factor A (VEGFA) has different biological activities and plays a central role in tumor proliferation, angiogenesis and metastasis. Different VEGFA isoforms are generated by alternative splice site selection of exons 6, 7 and 8. In this paper, we analyzed the physical and chemical properties of the VEGFA exon 6 sequence, and modeled the three-dimensional structures of the regions corresponding to exons 6, 7 and 8 of six different pro-angiogenic isoforms of VEGFA in comparison to the experimental structure of VEGFA_165 by a combined approach of fold recognition and comparative modeling strategies and molecular dynamics simulations. Our results showed that i) exon 6 is a very flexible polycation with high disordered propensity, features well conserved in all mammals, ii) the structures of all the isoforms are stabilized by H-bond sub-networks organized around HUB residues and, iii) the charge content of exon 6 modulates the intrinsic structural preference of its flexible backbone, which can be described as an ensemble of conformations. Moreover, complexes between NRP-1 and VEGFA isoforms were modeled by molecular docking to study what isoforms are able to bind NRP-1. The analysis of complexes evidenced that VEGFA_121, VEGFA_145, VEGFA_183, VEGFA_189 and VEGFA_206, containing exons 7 and 8a, are able to interact with NRP-1 because they have the key regions of exons 7b and/or 8a. An overview of the isoforms shows how the fluctuations are the main guidance of their biological function. MD simulations also provide insights into factors that stabilize the binding regions of isoforms.

RNA-seq analysis reveals significant effects of EGFR signalling on the secretome of mesenchymal stem cells.

Bone marrow-derived mesenchymal stem cells (MSCs) contribute to breast cancer progression by releasing soluble factors that sustain tumor progression. MSCs express functional epidermal growth factor receptor (EGFR) and breast cancer cells secrete EGFR-ligands including transforming growth factor-α (TGFα). Using RNA-sequencing, we analysed the whole transcriptome of MSCs stimulated with TGFα. We identified 1,640 highly differentially regulated genes: 967 genes up-regulated with Fold Induction (FI) ≥ 1.50 and 673 genes down-regulated with FI ≤ 0.50. When highly regulated genes were categorized according to GO molecular function classification and KEGG pathways analysis, a large number of genes coding for potentially secreted proteins or surface receptors resulted enriched following TGFα treatment, including VEGFA, IL6, EREG, HB-EGF, LIF, NGF, NRG1, CCL19, CCL2, CCL25 and CXCL3. Secretion of corresponding proteins was confirmed for selected factors. Finally, we identified 4,377 and 4,262 alternatively spliced genes in untreated and TGFα-treated MSCs, respectively. Among these, an unannotated splice variant of VEGFA coding for a secreted VEGF protein of 172 amino acids (VEGFA(172)), was found only in MSCs stimulated with TGFα. These findings suggest that EGFR activation in MSCs leads to a significant change in the expression of a wide array of genes coding for secreted proteins that can significantly enhance tumor progression.

Structure-function relationship and evolutionary history of the human selenoprotein M (SelM) found over-expressed in hepatocellular carcinoma.

In humans we know 25 selenoproteins that play important roles in redox regulation, detoxification, immune-system protection and viral suppression. In particular, selenoprotein M (SelM) may function as thiol disulfide oxidoreductase that participates in the formation of disulfide bonds, and can be implicated in calcium responses. However, it presents a redox motif (CXXU), where U is a selenocysteine, and may also function as redox regulator because its decreased or increased expression regulated by dietary selenium alters redox homeostasis. No data are reported in literature about its involvement in cancer but only in neurodegenerative diseases. In this paper we evaluated the SelM expression in two hepatoma cell lines, HepG2 and Huh7, compared to normal hepatocytes. The results suggested its involvement in hepatocellular carcinoma (HCC) as well as its possible use to follow the progression of this cancer as putative marker. The aim of this study has been to analyze the structure-function relationships of SelM. Hence, firstly we studied the evolutionary history of this protein by phylogenetic analysis and GC content of genes from various species. So, we modeled the three-dimensional structure of the human SelM evaluating its energetic stability by molecular dynamics simulations. Moreover, we modeled some of its mutants to obtain structural information helpful for structure-based drug design.

Molecular diagnostics and personalized medicine in oncology: challenges and opportunities.

Increasing evidence demonstrates that target-based agents are active only in molecularly selected populations of patients. Therefore, the identification of predictive biomarkers has become mandatory to improve the clinical development of these novel drugs. Mutations of the epidermal growth factor receptor (EGFR) or rearrangements of the ALK gene in non-small-cell lung cancer, and BRAF mutations in melanoma are clear examples of driver mutations and predictive biomarkers of response to treatment with specific inhibitors. Predictive biomarkers might also identify subgroups of patients that are not likely to respond to specific drugs, as shown for KRAS mutations and anti-EGFR monoclonal antibodies in colorectal carcinoma. The discovery of novel driver molecular alterations and the availability of drugs capable to selectively block such oncogenic mechanisms are leading to a rapid increase in the number of putative biomarkers that need to be assessed in each single patient. In this respect, two different approaches are being developed to introduce a comprehensive molecular characterization in clinical practice: high throughput genotyping platforms, which allow the detection of recognized genetic aberrations in clinical samples, and next generation sequencing that can provide information on all the different types of cancer-causing alterations. The introduction of these techniques in clinical practice will increase the possibility to identify molecular targets in each individual patient, and will also allow to follow the molecular evolution of the disease during the treatment. By using these approaches, the development of personalized medicine for patients with cancer will finally become possible.