Dynamic Monitoring of Circulating Tumor DNA in Patients With Metastatic Colorectal Cancer.

PURPOSE: Plasma circulating tumor DNA (ctDNA) is a valuable resource for tumor characterization and for monitoring of residual disease during treatment; however, it is not yet introduced in metastatic colorectal cancer (mCRC) routine clinical practice. In this retrospective exploratory study, we evaluated the role of ctDNA in patients with mCRC treated with chemotherapy plus bevacizumab. MATERIALS AND METHODS: Fifty-three patients were characterized for RAS and BRAF status on tumor tissue before the start of treatment. Plasma was collected at baseline, at first clinical evaluation, and at disease progression. ctDNA analysis was performed using Oncomine Colon cfDNA Assay on the Ion S5 XL instrument. RESULTS: At baseline, from a plasma sample, RAS, BRAF, or PIK3CA mutations were detected in 44 patients. A high correspondence was observed between ctDNA and tumor tissue mutations (KRAS 100%, NRAS 97.9%, BRAF 97.9%, PIK3CA 90%). Low baseline variant allele frequency (VAF) was found to be associated with longer median progression-free survival (PFS) compared with those with high VAF (15.9 v 12.2 months, P = .02). A higher PFS {12.29 months (95% CI, 9.03 to 17.9) v 8.15 months (95% CI, 2.76 to not available [NA]), P = .04} and overall survival (34.1 months [95% CI, 21.68 to NA] v 11.1 months [95% CI, 3.71 to NA], P = .003) were observed in patients with large decline in VAF at first evaluation. CONCLUSION: ctDNA analysis is useful for molecular characterization and tumor response monitoring in patients with mCRC. Quantitative variations of released ctDNA are associated with clinical outcomes.

Uncovering the expression of circPVT1 in the extracellular vesicles of acute myeloid leukemia patients.

Extracellular vesicles (EVs) act as molecular mediators in the tumor microenvironment, by shuttling information contained within malignant cells and functioning as regulators of the immune system. Circular (circ)RNAs are characterized by a closed loop-like structure that makes them more stable in the extracellular milieu and suitable to be packaged inside EVs. circPVT1 (hsa_circ_0001821) showed an oncogenic role in several cancer types and immunosuppressive properties in myeloid and lymphoid cell subsets. In this study, we characterized EVs from acute myeloid leukemia (AML) patients in terms of size, concentrations, surface markers and circPVT1 cargo. We showed that circPVT1 is overexpressed by primary blast cells from newly-diagnosed AML patients compared with hematopoietic stem-progenitor cells and is released as cell-free RNA in the plasma. We isolated EVs from the plasma of AML patients and healthy subjects by size exclusion chromatography and characterized them by nanoparticle tracking analysis. EVs from patients' plasma are larger compared with those from healthy subjects and their surface profile is characterized by higher levels of the leukemic cell markers CD133, CD105, CD49e and other immune-related epitopes, with differences according to AML molecular profile. Moreover, digital PCR analysis revealed that circPVT1 is more abundant inside EVs from the plasma of AML patients compared with healthy subjects. Our findings provide new insights on the features and content of AML EVs and suggest a role of circPVT1 in the crosstalk between AML cells and the tumor microenvironment.

Detection of a Novel MSI2-C17orf64 Transcript in a Patient with Aggressive Adenocarcinoma of the Gastroesophageal Junction: A Case Report.

Adenocarcinoma of the esophagus (EAC) and gastroesophageal junction (GEJ-AC) is associated with poor prognosis, treatment resistance and limited systemic therapeutic options. To deeply understand the genomic landscape of this cancer type, and potentially identify a therapeutic target in a neoadjuvant chemotherapy non-responder 48-year-old man, we adopted a multi-omic approach. We simultaneously evaluated gene rearrangements, mutations, copy number status, microsatellite instability and tumor mutation burden. The patient displayed pathogenic mutations of the TP53 and ATM genes and variants of uncertain significance of three kinases genes (ERBB3, CSNK1A1 and RPS6KB2), along with FGFR2 and KRAS high copy number amplification. Interestingly, transcriptomic analysis revealed the Musashi-2 (MSI2)-C17orf64 fusion that has never been reported before. Rearrangements of the RNA-binding protein MSI2 with a number of partner genes have been described across solid and hematological tumors. MSI2 regulates several biological processes involved in cancer initiation, development and resistance to treatment, and deserves further investigation as a potential therapeutic target. In conclusion, our extensive genomic characterization of a gastroesophageal tumor refractory to all therapeutic approaches led to the discovery of the MSI2-C17orf64 fusion. The results underlie the importance of deep molecular analyses enabling the identification of novel patient-specific markers to be monitored during therapy or even targeted at disease evolution.

Molecular Landscape and Association With Crohn Disease of Poorly Cohesive Carcinomas of the Nonampullary Small Bowel.

OBJECTIVES: Poorly cohesive carcinomas (PCCs) are neoplasms defined by a predominantly dyshesive growth pattern with single cell or cord-like stromal infiltration. The -distinctive clinicopathologic and prognostic features of small bowel PCCs (SB-PCCs) in comparison with conventional-type small intestinal adenocarcinomas have only recently been characterized. However, as SB-PCCs' genetic profile is still unknown, we aimed to analyze the molecular landscape of SB-PCCs. METHODS: A next-generation sequencing analysis through Trusight Oncology 500 on a series of 15 nonampullary SB-PCCs was performed. RESULTS: The most frequently found gene alterations were TP53 (53%) and RHOA (13%) mutations and KRAS amplification (13%), whereas KRAS, BRAF, and PIK3CA mutations were not identified. Most SB-PCCs (80%) were associated with Crohn disease, including both RHOA-mutated SB-PCCs, which featured a non-SRC-type histology, and showed a peculiar appendiceal-type, low-grade goblet cell adenocarcinoma (GCA)-like component. Rarely, SB-PCCs showed high microsatellite instability, mutations in IDH1 and ERBB2 genes, or FGFR2 amplification (one case each), which are established or promising therapeutic targets in such aggressive cancers. CONCLUSIONS: SB-PCCs may harbor RHOA mutations, which are reminiscent of the diffuse subtype of gastric cancers or appendiceal GCAs, while KRAS and PIK3CA mutations, commonly involved in colorectal and small bowel adenocarcinomas, are not typical of such cancers.

From phenotypical investigation to RNA-sequencing for gene expression analysis: A workflow for single and pooled rare cells.

Combining phenotypical and molecular characterization of rare cells is challenging due to their scarcity and difficult handling. In oncology, circulating tumor cells (CTCs) are considered among the most important rare cell populations. Their phenotypic and molecular characterization is necessary to define the molecular mechanisms underlying their metastatic potential. Several approaches that require cell fixation make difficult downstream molecular investigations on RNA. Conversely, the DEPArray technology allows phenotypic analysis and handling of both fixed and unfixed cells, enabling a wider range of applications. Here, we describe an experimental workflow that allows the transcriptomic investigation of single and pooled OE33 cells undergone to DEPArray analysis and recovery. In addition, cells were tested at different conditions (unfixed, CellSearch fixative (CSF)- and ethanol (EtOH)-fixed cells). In a forward-looking perspective, this workflow will pave the way for novel strategies to characterize gene expression profiles of rare cells, both single-cell and low-resolution input.

Dissecting Molecular Heterogeneity of Circulating Tumor Cells (CTCs) from Metastatic Breast Cancer Patients through Copy Number Aberration (CNA) and Single Nucleotide Variant (SNV) Single Cell Analysis.

Circulating tumor cells' (CTCs) heterogeneity contributes to counteract their introduction in clinical practice. Through single-cell sequencing we aim at exploring CTC heterogeneity in metastatic breast cancer (MBC) patients. Single CTCs were isolated using DEPArray NxT. After whole genome amplification, libraries were prepared for copy number aberration (CNA) and single nucleotide variant (SNV) analysis and sequenced using Ion GeneStudio S5 and Illumina MiSeq, respectively. CTCs demonstrate distinctive mutational signatures but retain molecular traces of their common origin. CNA profiling identifies frequent aberrations involving critical genes in pathogenesis: gains of 1q (CCND1) and 11q (WNT3A), loss of 22q (CHEK2). The longitudinal single-CTC analysis allows tracking of clonal selection and the emergence of resistance-associated aberrations, such as gain of a region in 12q (CDK4). A group composed of CTCs from different patients sharing common traits emerges. Further analyses identify losses of 15q and enrichment of terms associated with pseudopodium formation as frequent and exclusive events. CTCs from MBC patients are heterogeneous, especially concerning their mutational status. The single-cell analysis allows the identification of aberrations associated with resistance, and is a candidate tool to better address treatment strategy. The translational significance of the group populated by similar CTCs should be elucidated.

The role of next-generation sequencing in detecting gene fusions with known and unknown partners: a single-center experience with methodologies' integration.

AIMS: Next-generation sequencing (NGS) is becoming a new gold standard for determining molecular predictive biomarkers. This study aimed to evaluate the reliability of NGS in detecting gene fusions, focusing on comparing gene fusions with known and unknown partners. METHODS: We collected all gene fusions from a consecutive case series using an amplicon-based DNA/RNA NGS platform and subdivided them into two groups: gene fusions with known partners and gene fusions with unknown partners. Gene fusions involving ALK, ROS1 and RET were also examined by immunohistochemistry (IHC) and/or fluorescent in situ hybridization (FISH). RESULTS: Overall, 1174 malignancies underwent NGS analysis. NGS detected gene fusions in 67 cases (5.7%), further subdivided into 43 (64.2%) with known partners and 24 (35.8%) with unknown partners. Gene fusions were predominantly found in non-small cell lung carcinomas (52/67, 77.6%). Gene fusions with known partners frequently involved ALK (20/43, 46.5%) and MET (9/43, 20.9%), while gene fusions with unknown partners mostly involved RET (18/24, 75.0%). FISH/IHC confirmed rearrangement status in most (89.3%) of the gene fusions with known partners, but in only one (4.8%) of the gene fusions with unknown partners, with a significant difference (p < 0.001). In 17 patients undergoing targeted therapy, the log-rank test revealed that the overall survival was higher in the known partner group than in the unknown partner group (p = 0.002). CONCLUSIONS: NGS is a reliable method for detecting gene fusions with known partners, but it is less accurate in identifying gene fusions with unknown partners, for which further analyses (such as FISH) are required.

CNA Profiling of Single CTCs in Locally Advanced Esophageal Cancer Patients during Therapy Highlights Unexplored Molecular Pathways.

BACKGROUND: Here, we monitored the evolution of CTCs spread in 11 patients affected by locally advanced EC who were undergoing therapy. METHODS: In this perspective study, we designed multiple blood biopsies from individual patients: before and after neoadjuvant chemo-radio therapy and after surgery. We developed a multi-target array, named Grab-all assay, to estimate CTCs for their epithelial (EpCAM/E-Cadherin/Cytokeratins) and mesenchymal/stem (N-Cadherin/CD44v6/ABCG2) phenotypes. Identified CTCs were isolated as single cells by DEPArray, subjected to whole genome amplification, and copy number aberration (CNA) profiles were determined. Through bioinformatic analysis, we assessed the genomic imbalance of single CTCs, investigated specific focal copy number changes previously reported in EC and aberrant pathways using enrichment analysis. RESULTS: Longitudinal monitoring allowed the identification of CTCs in at least one time-point per patient. Through single cell CNA analysis, we revealed that CTCs showed significantly dynamic genomic imbalance during treatment. Individual CTCs from relapsed patients displayed a higher degree of genomic imbalance relative to disease-free patients' groups. Genomic aberrations previously reported in EC occurred mostly in post-neoadjuvant therapy CTCs. In-depth analysis showed that networks enrichment in all time-point CTCs were inherent to innate immune system. Transcription/gene regulation, post-transcriptional and epigenetic modifications were uniquely affected in CTCs of relapsed patients. CONCLUSIONS: Our data add clues to the comprehension of the role of CTCs in EC aggressiveness: chromosomal aberrations on genes related to innate immune system behave as relevant to the onset of CTC-status, whilst pathways of transcription/gene regulation, post-transcriptional and epigenetic modifications seem linked to patients' outcome.

Case Report: Analysis of Circulating Tumor Cells in a Triple Negative Spindle-Cell Metaplastic Breast Cancer Patient.

Circulating tumor cells (CTCs) are a rare population of cells found in the bloodstream and represent key players in the metastatic cascade. Their analysis has proved to provide further core information concerning the tumor. Herein, we aim at investigating CTCs isolated from a 32-year-old patient diagnosed with triple negative spindle-shaped metaplastic breast cancer (MpBC), a rare tumor poorly responsive to therapies and with a dismal prognosis. The molecular analysis performed on the primary tumor failed to underline effective actionable targets to address the therapeutic strategy. Besides the presence of round-shaped CTCs, cells with a spindle shape were present as well, and through molecular analysis, we confirmed their malignant nature. This aspect was coherent with the primary tumor histology, proving that CTCs are released regardless of their morphology. Copy number aberration (CNA) profiling and variant analysis using next-generation sequencing (NGS) showed that these cells did not harbor the alterations exhibited by the primary tumor (PIK3CA G1049A mutation, MYC copy number gain). However, despite the great heterogeneity observed, the amplification of regions involved in metastasis emerged (8q24.22-8q24.23). Our findings support the investigation of CTCs to identify alterations that could have a role in the metastatic process. To the best of our knowledge, this is the first examination of CTCs in an MpBC patient.

Adrenomedullin Expression Characterizes Leukemia Stem Cells and Associates With an Inflammatory Signature in Acute Myeloid Leukemia.

Adrenomedullin (ADM) is a hypotensive and vasodilator peptide belonging to the calcitonin gene-related peptide family. It is secreted in vitro by endothelial cells and vascular smooth muscle cells, and is significantly upregulated by a number of stimuli. Moreover, ADM participates in the regulation of hematopoietic compartment, solid tumors and leukemias, such as acute myeloid leukemia (AML). To better characterize ADM involvement in AML pathogenesis, we investigated its expression during human hematopoiesis and in leukemic subsets, based on a morphological, cytogenetic and molecular characterization and in T cells from AML patients. In hematopoietic stem/progenitor cells and T lymphocytes from healthy subjects, ADM transcript was barely detectable. It was expressed at low levels by megakaryocytes and erythroblasts, while higher levels were measured in neutrophils, monocytes and plasma cells. Moreover, cells populating the hematopoietic niche, including mesenchymal stem cells, showed to express ADM. ADM was overexpressed in AML cells versus normal CD34+ cells and in the subset of leukemia compared with hematopoietic stem cells. In parallel, we detected a significant variation of ADM expression among cytogenetic subgroups, measuring the highest levels in inv(16)/t(16;16) or complex karyotype AML. According to the mutational status of AML-related genes, the analysis showed a lower expression of ADM in FLT3-ITD, NPM1-mutated AML and FLT3-ITD/NPM1-mutated cases compared with wild-type ones. Moreover, ADM expression had a negative impact on overall survival within the favorable risk class, while showing a potential positive impact within the subgroup receiving a not-intensive treatment. The expression of 135 genes involved in leukemogenesis, regulation of cell proliferation, ferroptosis, protection from apoptosis, HIF-1α signaling, JAK-STAT pathway, immune and inflammatory responses was correlated with ADM levels in the bone marrow cells of at least two AML cohorts. Moreover, ADM was upregulated in CD4+ T and CD8+ T cells from AML patients compared with healthy controls and some ADM co-expressed genes participate in a signature of immune tolerance that characterizes CD4+ T cells from leukemic patients. Overall, our study shows that ADM expression in AML associates with a stem cell phenotype, inflammatory signatures and genes related to immunosuppression, all factors that contribute to therapy resistance and disease relapse.

Urinary Nucleic Acid in Tumor: Bioinformatics Approaches.

Application of next generation sequencing techniques in the field of liquid biopsy, in particular urine, requires specific bioinformatics methods in order to deal with its peculiarity. Many aspects of cancer can be explored starting from nucleic acids, especially from cell-free DNA and circulating tumor DNA in order to characterize cancer. It is possible to detect small mutations, as single nucleotide variants, small insertions and deletions, copy-number alterations, and epigenetic profiles. Due to the low fraction of circulating tumor DNA over the whole cell-free DNA, some methods have been exploited. One of them is the application of unique barcodes to each DNA fragment in order to lower the limit of detection of cancer-related variants. Some bioinformatics workflows and tools are the same of a classic analysis of tumor tissue, but there are some steps in which specific algorithms have to be introduced.

Estrogen and Androgen Receptor Inhibitors: Unexpected Allies in the Fight Against COVID-19.

TRANSLATIONAL RELEVANCE: No prophylactic treatments for COVID-19 have been clearly proven and found. In this pandemic context, cancer patients constitute a particularly fragile population that would benefit the best from such treatments, a present unmet need. TMPRSS2 is essential for COVID-19 replication cycle and it is under androgen control. Estrogen and androgen receptor dependent cues converge on TMPRSS2 regulation through different mechanisms of action that can be blocked by the use of hormonal therapies. We believe that there is enough body of evidence to foresee a prophylactic use of hormonal therapies against COVID-19 and this hypothesis can be easily tested on cohorts of breast and prostate cancer patients who follow those regimens. In case of pandemic, if the protective effect of hormonal therapies will be proven on cancer patients, the use of specific hormonal therapies could be extended to other oncological groups and to healthy individuals to decrease the overall risk of infection by SARS-CoV-2.Given the COVID-19 coronavirus emergency, a special focus is needed on the impact of this rapidly spreading viral infection on cancer patients. Androgen receptor (AR) signaling in the transmembrane protease serine 2 (TMPRSS2) regulation is emerging as an important determinant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) susceptibility. In our study, we analyzed AR and TMPRSS2 expression in 17,352 normal and 9,556 cancer tissues from public repositories and stratified data according to sex and age. The emerging picture is that some patient groups may be particularly susceptible to SARS-CoV-2 infection and may benefit from antiandrogen- or tamoxifen-based therapies. These findings are relevant to choose proper treatments in order to protect cancer patients from concomitant SARS-CoV-2 contagion and related symptoms and put forward the idea that hormonal therapies could be used as prophylactic agents against COVID-19.

ACE2 and TMPRSS2 Potential Involvement in Genetic Susceptibility to SARS-COV-2 in Cancer Patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic. One open question is whether genetics could influence the severity of symptoms. Considering the limited data on cancer patients, we analyzed public data repositories limited to investigate angiotensin-converting enzyme 2 (ACE2) and the transmembrane serine protease 2 (TMPRSS2) expressions and genetic variants to identify the basis of individual susceptibility to SARS-CoV-2.Gene expression and variant data were retrieved from Tissue Cancer Genome Atlas, Genotype-Tissue Expression, and gnomAD. Differences in gene expression were tested with Mann-Whitney U-test. Allele frequencies of germline variants were explored in different ethnicities, with a special focus on ACE2 variants located in the binding site to SARS-CoV-2 spike protein.The analysis of ACE2 and TMPRSS2 expressions in healthy tissues showed a higher expression in the age class 20 to 59 years (false discovery rate [FDR] < 0.0001) regardless of gender. ACE2 and TMPRSS2 were more expressed in tumors from males than females (both FDR < 0.0001) and, opposite to the regulation in tissues from healthy individuals, more expressed in elderly patients (FDR = 0.005; FDR < 0.0001, respectively). ACE2 and TMPRSS2 expressions were higher in cancers of elderly patients compared with healthy individuals (FDR < 0.0001). Variants were present at low frequency (range 0% to 3%) and among those with the highest frequency, the variant S19P belongs to the SARS-CoV-2 spike protein binding site and it was exclusively present in Africans with a frequency of 0.2%.The mechanisms of ACE2 and TMPRSS2 regulation could be targeted for preventive and therapeutic purposes in the whole population and especially in cancer patients.Further studies are needed to show a direct correlation of ACE2 and TMPRSS2 expressions in cancer patients and the incidence of COVID-19.

Single-Cell NGS-Based Analysis of Copy Number Alterations Reveals New Insights in Circulating Tumor Cells Persistence in Early-Stage Breast Cancer.

Circulating tumor cells (CTCs) are a rare population of cells representing a key player in the metastatic cascade. They are recognized as a validated tool for the identification of patients with a higher risk of relapse, including those diagnosed with breast cancer (BC). However, CTCs are characterized by high levels of heterogeneity that also involve copy number alterations (CNAs), structural variations associated with gene dosage changes. In this study, single CTCs were isolated from the peripheral blood of 11 early-stage BC patients at different time points. A label-free enrichment of CTCs was performed using OncoQuick, and single CTCs were isolated using DEPArray. Libraries were prepared from single CTCs and DNA extracted from matched tumor tissues for a whole-genome low-coverage next-generation sequencing (NGS) analysis using the Ion Torrent S5 System. The analysis of the CNA burden highlighted that CTCs had different degrees of aberration based on the time point and subtype. CTCs were found even six months after surgery and shared CNAs with matched tumor tissue. Tumor-associated CNAs that were recurrent in CTCs were patient-specific, and some alterations involved regions associated with BC and survival (i.e., gains at 1q21-23 and 5p15.33). The enrichment analysis emphasized the involvement of aberrations of terms, associated in particular with interferon (IFN) signaling. Collectively, our findings reveal that these aberrations may contribute to understanding the molecular mechanisms involving CTC-related processes and their survival ability in occult niches, supporting the goal of exploiting their application in patients' surveillance and follow-up.

Fully Human Antibodies for Malignant Pleural Mesothelioma Targeting.

Immunotherapy is the most promising therapeutic approach against malignant pleural mesothelioma (MPM). Despite technological progress, the number of targetable antigens or specific antibodies is limited, thus hindering the full potential of recent therapeutic interventions. All possibilities of finding new targeting molecules must be exploited. The specificity of targeting is guaranteed by the use of monoclonal antibodies, while fully human antibodies are preferred, as they are functional and generate no neutralizing antibodies. The aim of this review is to appraise the latest advances in screening methods dedicated to the identification and harnessing of fully human antibodies. The scope of identifying useful molecules proceeds along two avenues, i.e., through the antigen-first or binding-first approaches. The first relies on screening human antibody libraries or plasma from immunized transgenic mice or humans to isolate binders to specific antigens. The latter takes advantage of specific binding to tumor cells of antibodies present in phage display libraries or in responders' plasma samples without prior knowledge of the antigens. Additionally, next-generation sequencing analysis of B-cell receptor repertoire pre- and post-therapy in memory B-cells from responders allows for the identification of clones expanded and matured upon treatment. Human antibodies identified can be subsequently reformatted to generate a plethora of therapeutics like antibody-drug conjugates, immunotoxins, and advanced cell-therapeutics such as chimeric antigen receptor-transduced T-cells.

Genetic Predisposition to Breast and Ovarian Cancers: How Many and Which Genes to Test?

Breast and ovarian cancers are some of the most common tumors in females, and the genetic predisposition is emerging as one of the key risk factors in the development of these two malignancies. BRCA1 and BRCA2 are the best-known genes associated with hereditary breast and ovarian cancer. However, recent advances in molecular techniques, Next-Generation Sequencing in particular, have led to the identification of many new genes involved in the predisposition to breast and/or ovarian cancer, with different penetrance estimates. TP53, PTEN, STK11, and CDH1 have been identified as high penetrance genes for the risk of breast/ovarian cancers. Besides them, PALB2, BRIP1, ATM, CHEK2, BARD1, NBN, NF1, RAD51C, RAD51D and mismatch repair genes have been recognized as moderate and low penetrance genes, along with other genes encoding proteins involved in the same pathways, possibly associated with breast/ovarian cancer risk. In this review, we summarize the past and more recent findings in the field of cancer predisposition genes, with insights into the role of the encoded proteins and the associated genetic disorders. Furthermore, we discuss the possible clinical utility of genetic testing in terms of prevention protocols and therapeutic approaches.

Combinations of immuno-checkpoint inhibitors predictive biomarkers only marginally improve their individual accuracy.

BACKGROUND: There are no accepted universal biomarkers capable to accurately predict response to immuno-checkpoint inhibitors (ICI). Although recent literature has been flooded with studies on ICI predictive biomarkers, available data show that currently approved companion diagnostics either leave out many possible responders, as in the case of PD-L1 testing for first-line metastatic lung cancer, or apply to a small subset of patients, such as the recently approved treatment for microsatellite instability-high or mismatch repair deficiency tumors. In this study, we conducted a survey of the available data on ICI trials with matched genomic or transcriptomic datasets in order to cross-validate the proposed biomarkers, to assess whether their prediction power was confirmed and, mainly, to investigate if their combination was able to generate a better predictive tool. METHODS: We extracted clinical information and sequencing data details from publicly available datasets, along with a list of possible biomarkers obtained from the recent literature. After an operation of data harmonization, we validated the performance of all the biomarkers taken individually. Furthermore, we tested two strategies to combine the best performing biomarkers in order to improve their predictive value. RESULTS: When considered individually, some of the biomarkers, such as the ImmunoPhenoScore, and the IFN-γ signature, did not confirm their originally proposed predictive power. The best absolute scoring biomarkers are TIDE, one of the ICB resistance signatures and CTLA4 with a mean AUC > 0.66. Among the combinations tested, generalized linear models showed the best performance with an AUC of 0.78. CONCLUSIONS: We confirmed that the available biomarkers, taken individually, fail to provide a satisfactory predictive value. Unfortunately, also combination of some of them only provides marginal improvements. Hence, in order to generate a more robust way to predict ICI efficacy it is necessary to analyze and combine additional biomarkers and interrogate a wider set of clinical data.

Reverse Engineering Cancer: Inferring Transcriptional Gene Signatures from Copy Number Aberrations with ICAro.

The characterization of a gene product function is a process that involves multiple laboratory techniques in order to silence the gene itself and to understand the resulting cellular phenotype via several omics profiling. When it comes to tumor cells, usually the translation process from in vitro characterization results to human validation is a difficult journey. Here, we present a simple algorithm to extract mRNA signatures from cancer datasets, where a particular gene has been deleted at the genomic level, ICAro. The process is implemented as a two-step workflow. The first one employs several filters in order to select the two patient subsets: the inactivated one, where the target gene is deleted, and the control one, where large genomic rearrangements should be absent. The second step performs a signature extraction via a Differential Expression analysis and a complementary Random Forest approach to provide an additional gene ranking in terms of information loss. We benchmarked the system robustness on a panel of genes frequently deleted in cancers, where we validated the downregulation of target genes and found a correlation with signatures extracted with the L1000 tool, outperforming random sampling for two out of six L1000 classes. Furthermore, we present a use case correlation with a published transcriptomic experiment. In conclusion, deciphering the complex interactions of the tumor environment is a challenge that requires the integration of several experimental techniques in order to create reproducible results. We implemented a tool which could be of use when trying to find mRNA signatures related to a gene loss event to better understand its function or for a gene-loss associated biomarker research.