Preclinical efficacy of a HER2 synNotch/CEA-CAR combinatorial immunotherapy against colorectal cancer with HER2 amplification.

HER2 amplification occurs in approximately 5% of colorectal cancer (CRC) cases and is associated only partially with clinical response to combined human epidermal growth factor receptor 2 (HER2)/epidermal growth factor receptor (EGFR)-targeted treatment. An alternative approach based on adoptive cell therapy using T cells engineered with anti-HER2 chimeric antigen receptor (CAR) proved to be toxic due to on-target/off-tumor activity. Here we describe a combinatorial strategy to safely target HER2 amplification and carcinoembryonic antigen (CEA) expression in CRC using a synNotch-CAR-based artificial regulatory network. The natural killer (NK) cell line NK-92 was engineered with an anti-HER2 synNotch receptor driving the expression of a CAR against CEA only when engaged. After being transduced and sorted for HER2-driven CAR expression, cells were cloned. The clone with optimal performances in terms of specificity and amplitude of CAR induction demonstrated significant activity in vitro and in vivo specifically against HER2-amplified (HER2amp)/CEA+ CRC models, with no effects on cells with physiological HER2 levels. The HER2-synNotch/CEA-CAR-NK system provides an innovative, scalable, and safe off-the-shelf cell therapy approach with potential against HER2amp CRC resistant or partially responsive to HER2/EGFR blockade.

The biomedicalization of pregnancy prevention, neoliberal feminism, and college women's experiences of the contraceptive paradox.

Research examining the "contraceptive paradox" has illuminated how contraception can be a source of empowerment for some and oppression for others. This study advances theorizing of the contraceptive paradox by illustrating how 45 young women experience contraception as both liberating and constraining due to a confluence of biomedicalization processes, gender inequality, and neoliberal feminism. Drawing on focus group data, we find that the biomedicalization of pregnancy prevention and neoliberal feminist discourse, in combination with experiences of social and economic privilege and gender inequality in fertility work, shape participants' interpretation of contraceptive technology as a key resource for individually liberating themselves from undesired pregnancy. At the same time, their experiences indicate prescription contraception plays an oppressive role in their lives. In addition to blaming themselves and their bodies for negative contraceptive side effects, participants take for granted that assuming sole responsibility for contraceptive use in their relationships with men is the price they must pay to feel free. The findings indicate that addressing a social problem using an individualized biomedical solution obscures the power that structural inequalities exert over pregnancy-capable people, including relatively privileged young women. As an expression of biopower, these dynamics prompted participants to emphasize distributive justice over social justice, foreclosing their engagement in collective action.

RAS/RAF Comutation and ERBB2 Copy Number Modulates HER2 Heterogeneity and Responsiveness to HER2-directed Therapy in Colorectal Cancer.

PURPOSE: ERBB2-amplified colorectal cancer is a distinct molecular subtype with expanding treatments. Implications of concurrent oncogenic RAS/RAF alterations are not known. EXPERIMENTAL DESIGN: Dana-Farber and Foundation Medicine Inc. Colorectal cancer cohorts with genomic profiling were used to identify ERBB2-amplified cases [Dana-Farber, n = 47/2,729 (1.7%); FMI, n = 1857/49,839 (3.7%)]. Outcomes of patients receiving HER2-directed therapies are reported (Dana-Farber, n = 9; Flatiron Health-Foundation Medicine clinicogenomic database, FH-FMI CGDB, n = 38). Multisite HER2 IHC and genomic profiling were performed to understand HER2 intratumoral and interlesional heterogeneity. The impact of concurrent RAS comutations on the effectiveness of HER2-directed therapies were studied in isogenic colorectal cancer cell lines and xenografts. RESULTS: ERBB2 amplifications are enriched in left-sided colorectal cancer. Twenty percent of ERBB2-amplified colorectal cancers have co-occurring oncogenic RAS/RAF alterations. While RAS/RAF WT colorectal cancers typically have clonal ERBB2 amplification, colorectal cancers with co-occurring RAS/RAF alterations have lower level ERRB2 amplification, higher intratumoral heterogeneity, and interlesional ERBB2 discordance. These distinct genomic patterns lead to differential responsiveness and patterns of resistance to HER2-directed therapy. ERBB2-amplified colorectal cancer with RAS/RAF alterations are resistant to trastuzumab-based combinations, such as trastuzumab/tucatinib, but retain sensitivity to trastuzumab deruxtecan in in vitro and murine models. Trastuzumab deruxtecan shows clinical efficacy in cases with high-level ERBB2-amplified RAS/RAF coaltered colorectal cancer. CONCLUSIONS: Co-occurring RAS/RAF alterations define a unique subtype of ERBB2-amplified colorectal cancer that has increased intratumoral heterogeneity, interlesional discordance, and resistance to trastuzumab-based combinations. Further examination of trastuzumab deruxtecan in this previously understudied cohort of ERBB2-amplified colorectal cancer is warranted.

Pathway level subtyping identifies a slow-cycling biological phenotype associated with poor clinical outcomes in colorectal cancer.

Molecular stratification using gene-level transcriptional data has identified subtypes with distinctive genotypic and phenotypic traits, as exemplified by the consensus molecular subtypes (CMS) in colorectal cancer (CRC). Here, rather than gene-level data, we make use of gene ontology and biological activation state information for initial molecular class discovery. In doing so, we defined three pathway-derived subtypes (PDS) in CRC: PDS1 tumors, which are canonical/LGR5+ stem-rich, highly proliferative and display good prognosis; PDS2 tumors, which are regenerative/ANXA1+ stem-rich, with elevated stromal and immune tumor microenvironmental lineages; and PDS3 tumors, which represent a previously overlooked slow-cycling subset of tumors within CMS2 with reduced stem populations and increased differentiated lineages, particularly enterocytes and enteroendocrine cells, yet display the worst prognosis in locally advanced disease. These PDS3 phenotypic traits are evident across numerous bulk and single-cell datasets, and demark a series of subtle biological states that are currently under-represented in pre-clinical models and are not identified using existing subtyping classifiers.

Phosphoproteomics of patient-derived xenografts identifies targets and markers associated with sensitivity and resistance to EGFR blockade in colorectal cancer.

Epidermal growth factor receptor (EGFR) is a well-exploited therapeutic target in metastatic colorectal cancer (mCRC). Unfortunately, not all patients benefit from current EGFR inhibitors. Mass spectrometry-based proteomics and phosphoproteomics were performed on 30 genomically and pharmacologically characterized mCRC patient-derived xenografts (PDXs) to investigate the molecular basis of response to EGFR blockade and identify alternative drug targets to overcome resistance. Both the tyrosine and global phosphoproteome as well as the proteome harbored distinctive response signatures. We found that increased pathway activity related to mitogen-activated protein kinase (MAPK) inhibition and abundant tyrosine phosphorylation of cell junction proteins, such as CXADR and CLDN1/3, in sensitive tumors, whereas epithelial-mesenchymal transition and increased MAPK and AKT signaling were more prevalent in resistant tumors. Furthermore, the ranking of kinase activities in single samples confirmed the driver activity of ERBB2, EGFR, and MET in cetuximab-resistant tumors. This analysis also revealed high kinase activity of several members of the Src and ephrin kinase family in 2 CRC PDX models with genomically unexplained resistance. Inhibition of these hyperactive kinases, alone or in combination with cetuximab, resulted in growth inhibition of ex vivo PDX-derived organoids and in vivo PDXs. Together, these findings highlight the potential value of phosphoproteomics to improve our understanding of anti-EGFR treatment and response prediction in mCRC and bring to the forefront alternative drug targets in cetuximab-resistant tumors.

Multi-label transcriptional classification of colorectal cancer reflects tumor cell population heterogeneity.

BACKGROUND: Transcriptional classification has been used to stratify colorectal cancer (CRC) into molecular subtypes with distinct biological and clinical features. However, it is not clear whether such subtypes represent discrete, mutually exclusive entities or molecular/phenotypic states with potential overlap. Therefore, we focused on the CRC Intrinsic Subtype (CRIS) classifier and evaluated whether assigning multiple CRIS subtypes to the same sample provides additional clinically and biologically relevant information. METHODS: A multi-label version of the CRIS classifier (multiCRIS) was applied to newly generated RNA-seq profiles from 606 CRC patient-derived xenografts (PDXs), together with human CRC bulk and single-cell RNA-seq datasets. Biological and clinical associations of single- and multi-label CRIS were compared. Finally, a machine learning-based multi-label CRIS predictor (ML2CRIS) was developed for single-sample classification. RESULTS: Surprisingly, about half of the CRC cases could be significantly assigned to more than one CRIS subtype. Single-cell RNA-seq analysis revealed that multiple CRIS membership can be a consequence of the concomitant presence of cells of different CRIS class or, less frequently, of cells with hybrid phenotype. Multi-label assignments were found to improve prediction of CRC prognosis and response to treatment. Finally, the ML2CRIS classifier was validated for retaining the same biological and clinical associations also in the context of single-sample classification. CONCLUSIONS: These results show that CRIS subtypes retain their biological and clinical features even when concomitantly assigned to the same CRC sample. This approach could be potentially extended to other cancer types and classification systems.

EGAsubmitter: A software to automate submission of nucleic acid sequencing data to the European Genome-phenome Archive.

Making raw data available to the research community is one of the pillars of Findability, Accessibility, Interoperability, and Reuse (FAIR) research. However, the submission of raw data to public databases still involves many manually operated procedures that are intrinsically time-consuming and error-prone, which raises potential reliability issues for both the data themselves and the ensuing metadata. For example, submitting sequencing data to the European Genome-phenome Archive (EGA) is estimated to take 1 month overall, and mainly relies on a web interface for metadata management that requires manual completion of forms and the upload of several comma separated values (CSV) files, which are not structured from a formal point of view. To tackle these limitations, here we present EGAsubmitter, a Snakemake-based pipeline that guides the user across all the submission steps, ranging from files encryption and upload, to metadata submission. EGASubmitter is expected to streamline the automated submission of sequencing data to EGA, minimizing user errors and ensuring higher end product fidelity.

CONNECTOR, fitting and clustering of longitudinal data to reveal a new risk stratification system.

MOTIVATION: The transition from evaluating a single time point to examining the entire dynamic evolution of a system is possible only in the presence of the proper framework. The strong variability of dynamic evolution makes the definition of an explanatory procedure for data fitting and clustering challenging. RESULTS: We developed CONNECTOR, a data-driven framework able to analyze and inspect longitudinal data in a straightforward and revealing way. When used to analyze tumor growth kinetics over time in 1599 patient-derived xenograft growth curves from ovarian and colorectal cancers, CONNECTOR allowed the aggregation of time-series data through an unsupervised approach in informative clusters. We give a new perspective of mechanism interpretation, specifically, we define novel model aggregations and we identify unanticipated molecular associations with response to clinically approved therapies. AVAILABILITY AND IMPLEMENTATION: CONNECTOR is freely available under GNU GPL license at https://qbioturin.github.io/connector and https://doi.org/10.17504/protocols.io.8epv56e74g1b/v1.

MicroRNA 483-3p overexpression unleashes invasive growth of metastatic colorectal cancer via NDRG1 downregulation and ensuing activation of the ERBB3/AKT axis.

In colorectal cancer, the mechanisms underlying tumor aggressiveness require further elucidation. Taking advantage of a large panel of human metastatic colorectal cancer xenografts and matched stem-like cell cultures (m-colospheres), here we show that the overexpression of microRNA 483-3p (miRNA-483-3p; also known as MIR-483-3p), encoded by a frequently amplified gene locus, confers an aggressive phenotype. In m-colospheres, endogenous or ectopic miRNA-483-3p overexpression increased proliferative response, invasiveness, stem cell frequency, and resistance to differentiation. Transcriptomic analyses and functional validation found that miRNA-483-3p directly targets NDRG1, known as a metastasis suppressor involved in EGFR family downregulation. Mechanistically, miRNA-483-3p overexpression induced the signaling pathway triggered by ERBB3, including AKT and GSK3ß, and led to the activation of transcription factors regulating epithelial-mesenchymal transition (EMT). Consistently, treatment with selective anti-ERBB3 antibodies counteracted the invasive growth of miRNA-483-3p-overexpressing m-colospheres. In human colorectal tumors, miRNA-483-3p expression inversely correlated with NDRG1 and directly correlated with EMT transcription factor expression and poor prognosis. These results unveil a previously unrecognized link between miRNA-483-3p, NDRG1, and ERBB3-AKT signaling that can directly support colorectal cancer invasion and is amenable to therapeutic targeting.

Colorectal cancer patient-derived organoids and cell lines harboring ATRX and/or DAXX mutations lack Alternative Lengthening of Telomeres (ALT).

Telomere maintenance is necessary to maintain cancer cell unlimited viability. However, the mechanisms maintaining telomere length in colorectal cancer (CRC) have not been extensively investigated. Telomere maintenance mechanisms (TMM) include the re-expression of telomerase or alternative lengthening of telomeres (ALT). ALT is genetically associated with somatic alterations in alpha-thalassemia/mental retardation X-linked (ATRX) and death domain-associated protein (DAXX) genes. Cells displaying ALT present distinctive features including C-circles made of telomeric DNA, long and heterogenous telomeric tracts, and telomeric DNA co-localized with promyelocytic leukemia (PML) bodies forming so-called ALT-associated PML bodies (APBs). Here, we identified mutations in ATRX and/or DAXX genes in an extensive collection of CRC samples including 119 patient-derived organoids (PDOs) and 232 established CRC cell lines. C-circles measured in CRC PDOs and cell lines showed low levels overall. We also observed that CRC PDOs and cell lines did not display a significant accumulation of APBs or long telomeres with no appreciable differences between wild-type and mutated ATRX/DAXX samples. Overall, our extensive analyses indicate that CRC is not prone to engage ALT, even when carrying genetic lesions in ATRX and/or DAXX, and support the notion that ATRX/DAXX genomic footprints are not reliable predictors of ALT.

Synthetic Lethal Interaction with BCL-XL Blockade Deepens Response to Cetuximab in Patient-Derived Models of Metastatic Colorectal Cancer.

PURPOSE: Approximately 20% of patients with RAS wild-type metastatic colorectal cancer (mCRC) experience objective responses to the anti-EGFR antibody cetuximab, but disease eradication is seldom achieved. The extent of tumor shrinkage correlates with long-term outcome. We aimed to find rational combinations that potentiate cetuximab efficacy by disrupting adaptive dependencies on antiapoptotic molecules (BCL2, BCL-XL, MCL1). EXPERIMENTAL DESIGN: Experiments were conducted in patient-derived xenografts (PDX) and organoids (PDXO). Apoptotic priming was analyzed by BH3 profiling. Proapoptotic and antiapoptotic protein complexes were evaluated by co-immunoprecipitation and electroluminescence sandwich assays. The effect of combination therapies was assessed by caspase activation in PDXOs and by monitoring PDX growth. RESULTS: A population trial in 314 PDX cohorts, established from as many patients, identified 46 models (14.6%) with appreciable (>50% tumor shrinkage) but incomplete response to cetuximab. From these models, 14 PDXOs were derived. Cetuximab primed cells for apoptosis, but only concomitant blockade of BCL-XL precipitated cell death. Mechanistically, exposure to cetuximab induced upregulation of the proapoptotic protein BIM and its sequestration by BCL-XL. Inhibition of BCL-XL resulted in displacement of BIM, which was not buffered by MCL1 and thereby became competent to induce apoptosis. In five PDX models, combination of cetuximab and a selective BCL-XL inhibitor triggered apoptosis and led to more pronounced tumor regressions and longer time to relapse after treatment discontinuation than cetuximab alone. CONCLUSIONS: In mCRC tumors that respond to cetuximab, antibody treatment confers a synthetic-lethal dependency on BCL-XL. Targeting this dependency unleashes apoptosis and increases the depth of response to cetuximab.

A modified fluctuation-test framework characterizes the population dynamics and mutation rate of colorectal cancer persister cells.

Compelling evidence shows that cancer persister cells represent a major limit to the long-term efficacy of targeted therapies. However, the phenotype and population dynamics of cancer persister cells remain unclear. We developed a quantitative framework to study persisters by combining experimental characterization and mathematical modeling. We found that, in colorectal cancer, a fraction of persisters slowly replicates. Clinically approved targeted therapies induce a switch to drug-tolerant persisters and a temporary 7- to 50-fold increase of their mutation rate, thus increasing the number of persister-derived resistant cells. These findings reveal that treatment may influence persistence and mutability in cancer cells and pinpoint inhibition of error-prone DNA polymerases as a strategy to restrict tumor recurrence.

Effective drug combinations in breast, colon and pancreatic cancer cells.

Combinations of anti-cancer drugs can overcome resistance and provide new treatments1,2. The number of possible drug combinations vastly exceeds what could be tested clinically. Efforts to systematically identify active combinations and the tissues and molecular contexts in which they are most effective could accelerate the development of combination treatments. Here we evaluate the potency and efficacy of 2,025 clinically relevant two-drug combinations, generating a dataset encompassing 125 molecularly characterized breast, colorectal and pancreatic cancer cell lines. We show that synergy between drugs is rare and highly context-dependent, and that combinations of targeted agents are most likely to be synergistic. We incorporate multi-omic molecular features to identify combination biomarkers and specify synergistic drug combinations and their active contexts, including in basal-like breast cancer, and microsatellite-stable or KRAS-mutant colon cancer. Our results show that irinotecan and CHEK1 inhibition have synergistic effects in microsatellite-stable or KRAS-TP53 double-mutant colon cancer cells, leading to apoptosis and suppression of tumour xenograft growth. This study identifies clinically relevant effective drug combinations in distinct molecular subpopulations and is a resource to guide rational efforts to develop combinatorial drug treatments.

The EurOPDX Data Portal: an open platform for patient-derived cancer xenograft data sharing and visualization.

BACKGROUND: Patient-derived xenografts (PDX) mice models play an important role in preclinical trials and personalized medicine. Sharing data on the models is highly valuable for numerous reasons - ethical, economical, research cross validation etc. The EurOPDX Consortium was established 8 years ago to share such information and avoid duplicating efforts in developing new PDX mice models and unify approaches to support preclinical research. EurOPDX Data Portal is the unified data sharing platform adopted by the Consortium. MAIN BODY: In this paper we describe the main features of the EurOPDX Data Portal ( https://dataportal.europdx.eu/ ), its architecture and possible utilization by researchers who look for PDX mice models for their research. The Portal offers a catalogue of European models accessible on a cooperative basis. The models are searchable by metadata, and a detailed view provides molecular profiles (gene expression, mutation, copy number alteration) and treatment studies. The Portal displays the data in multiple tools (PDX Finder, cBioPortal, and GenomeCruzer in future), which are populated from a common database displaying strictly mutually consistent views. (SHORT) CONCLUSION: EurOPDX Data Portal is an entry point to the EurOPDX Research Infrastructure offering PDX mice models for collaborative research, (meta)data describing their features and deep molecular data analysis according to users' interests.

Protocol versus practice: Deviations from guidelines in low-risk twin deliveries in the United States.

BACKGROUND: Medical guidelines recommend vaginal delivery for low-risk twin pregnancies because cesareans increase the probability of maternal morbidity and mortality. Yet, vaginal delivery rates for twins are considerably lower than for comparable singletons. One explanation for this disparity argues that greater risk associated with twins warrants increased surgical intervention. An alternative explanation is that twin deliveries are more likely to deviate from protocols that advise vaginal birth. METHODS: Using the 2017 Natality Detail File (N = 3,197,401), we measured alignment of vaginal birth and trial of labor (TOL) with the American College of Obstetricians and Gynecologists' guidelines for twin and singleton no-indicated-risk births. We calculated predicted probabilities for the population and by maternal race/ethnicity to assess whether low rates of vaginal births among twins are explained by associated risk factors, or by deviations from recommended delivery methods. RESULTS: Overall, 31.2% of twins were born vaginally compared with 79.4% of singletons. Controlling for indicated risks, the predicted probability of vaginal birth for twins was 0.49 and 0.85 for singletons. The predicted probability of TOL for twins was 0.18 and 0.47 for singletons. Maternal race/ethnicity was only weakly associated with mode of delivery. These findings indicate that no-indicated-risk twin pregnancies, across maternal racial/ethnic categories, have lower probabilities of vaginal birth and TOL than would be expected with widespread adherence to current guidelines. CONCLUSIONS: Given the life-threatening consequences that may result from unnecessary surgical procedures, our findings highlight the need for further research to illuminate medical and nonmedical mechanisms driving nonadherence to clinical guidelines for twin births.

Chromatin Velocity reveals epigenetic dynamics by single-cell profiling of heterochromatin and euchromatin.

Recent efforts have succeeded in surveying open chromatin at the single-cell level, but high-throughput, single-cell assessment of heterochromatin and its underlying genomic determinants remains challenging. We engineered a hybrid transposase including the chromodomain (CD) of the heterochromatin protein-1α (HP-1α), which is involved in heterochromatin assembly and maintenance through its binding to trimethylation of the lysine 9 on histone 3 (H3K9me3), and developed a single-cell method, single-cell genome and epigenome by transposases sequencing (scGET-seq), that, unlike single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq), comprehensively probes both open and closed chromatin and concomitantly records the underlying genomic sequences. We tested scGET-seq in cancer-derived organoids and human-derived xenograft (PDX) models and identified genetic events and plasticity-driven mechanisms contributing to cancer drug resistance. Next, building upon the differential enrichment of closed and open chromatin, we devised a method, Chromatin Velocity, that identifies the trajectories of epigenetic modifications at the single-cell level. Chromatin Velocity uncovered paths of epigenetic reorganization during stem cell reprogramming and identified key transcription factors driving these developmental processes. scGET-seq reveals the dynamics of genomic and epigenetic landscapes underlying any cellular processes.

Synthetic Lethality Screening Highlights Colorectal Cancer Vulnerability to Concomitant Blockade of NEDD8 and EGFR Pathways.

Colorectal cancer (CRC) is a heterogeneous disease showing significant variability in clinical aggressiveness. Primary and acquired resistance limits the efficacy of available treatments, and identification of effective drug combinations is needed to further improve patients' outcomes. We previously found that the NEDD8-activating enzyme inhibitor pevonedistat induced tumor stabilization in preclinical models of poorly differentiated, clinically aggressive CRC resistant to available therapies. To identify drugs that can be effectively combined with pevonedistat, we performed a "drop-out" loss-of-function synthetic lethality screening with an shRNA library covering 200 drug-target genes in four different CRC cell lines. Multiple screening hits were found to be involved in the EGFR signaling pathway, suggesting that, rather than inhibition of a specific gene, interference with the EGFR pathway at any level could be effectively leveraged for combination therapies based on pevonedistat. Exploiting both BRAF-mutant and RAS/RAF wild-type CRC models, we validated the therapeutic relevance of our findings by showing that combined blockade of NEDD8 and EGFR pathways led to increased growth arrest and apoptosis both in vitro and in vivo. Pathway modulation analysis showed that compensatory feedback loops induced by single treatments were blunted by the combinations. These results unveil possible therapeutic opportunities in specific CRC clinical settings.

Molecular Subtyping Combined with Biological Pathway Analyses to Study Regorafenib Response in Clinically Relevant Mouse Models of Colorectal Cancer.

PURPOSE: Regorafenib (REG) is approved for the treatment of metastatic colorectal cancer, but has modest survival benefit and associated toxicities. Robust predictive/early response biomarkers to aid patient stratification are outstanding. We have exploited biological pathway analyses in a patient-derived xenograft (PDX) trial to study REG response mechanisms and elucidate putative biomarkers. EXPERIMENTAL DESIGN: Molecularly subtyped PDXs were annotated for REG response. Subtyping was based on gene expression (CMS, consensus molecular subtype) and copy-number alteration (CNA). Baseline tumor vascularization, apoptosis, and proliferation signatures were studied to identify predictive biomarkers within subtypes. Phospho-proteomic analysis was used to identify novel classifiers. Supervised RNA sequencing analysis was performed on PDXs that progressed, or did not progress, following REG treatment. RESULTS: Improved REG response was observed in CMS4, although intra-subtype response was variable. Tumor vascularity did not correlate with outcome. In CMS4 tumors, reduced proliferation and higher sensitivity to apoptosis at baseline correlated with response. Reverse phase protein array (RPPA) analysis revealed 4 phospho-proteomic clusters, one of which was enriched with non-progressor models. A classification decision tree trained on RPPA- and CMS-based assignments discriminated non-progressors from progressors with 92% overall accuracy (97% sensitivity, 67% specificity). Supervised RNA sequencing revealed that higher basal EPHA2 expression is associated with REG resistance. CONCLUSIONS: Subtype classification systems represent canonical "termini a quo" (starting points) to support REG biomarker identification, and provide a platform to identify resistance mechanisms and novel contexts of vulnerability. Incorporating functional characterization of biological systems may optimize the biomarker identification process for multitargeted kinase inhibitors.

PhyliCS: a Python library to explore scCNA data and quantify spatial tumor heterogeneity.

BACKGROUND: Tumors are composed by a number of cancer cell subpopulations (subclones), characterized by a distinguishable set of mutations. This phenomenon, known as intra-tumor heterogeneity (ITH), may be studied using Copy Number Aberrations (CNAs). Nowadays ITH can be assessed at the highest possible resolution using single-cell DNA (scDNA) sequencing technology. Additionally, single-cell CNA (scCNA) profiles from multiple samples of the same tumor can in principle be exploited to study the spatial distribution of subclones within a tumor mass. However, since the technology required to generate large scDNA sequencing datasets is relatively recent, dedicated analytical approaches are still lacking. RESULTS: We present PhyliCS, the first tool which exploits scCNA data from multiple samples from the same tumor to estimate whether the different clones of a tumor are well mixed or spatially separated. Starting from the CNA data produced with third party instruments, it computes a score, the Spatial Heterogeneity score, aimed at distinguishing spatially intermixed cell populations from spatially segregated ones. Additionally, it provides functionalities to facilitate scDNA analysis, such as feature selection and dimensionality reduction methods, visualization tools and a flexible clustering module. CONCLUSIONS: PhyliCS represents a valuable instrument to explore the extent of spatial heterogeneity in multi-regional tumour sampling, exploiting the potential of scCNA data.