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.

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.

Tolerance to colibactin correlates with homologous recombination proficiency and resistance to irinotecan in colorectal cancer cells.

The bacterial genotoxin colibactin promotes colorectal cancer (CRC) tumorigenesis, but systematic assessment of its impact on DNA repair is lacking, and its effect on response to DNA-damaging chemotherapeutics is unknown. We find that CRC cell lines display differential response to colibactin on the basis of homologous recombination (HR) proficiency. Sensitivity to colibactin is induced by inhibition of ATM, which regulates DNA double-strand break repair, and blunted by HR reconstitution. Conversely, CRC cells chronically infected with colibactin develop a tolerant phenotype characterized by restored HR activity. Notably, sensitivity to colibactin correlates with response to irinotecan active metabolite SN38, in both cell lines and patient-derived organoids. Moreover, CRC cells that acquire colibactin tolerance develop cross-resistance to SN38, and a trend toward poorer response to irinotecan is observed in a retrospective cohort of CRCs harboring colibactin genomic island. Our results shed insight into colibactin activity and provide translational evidence on its chemoresistance-promoting role in CRC.

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.

Towards precision oncology with patient-derived xenografts.

Under the selective pressure of therapy, tumours dynamically evolve multiple adaptive mechanisms that make static interrogation of genomic alterations insufficient to guide treatment decisions. Clinical research does not enable the assessment of how various regulatory circuits in tumours are affected by therapeutic insults over time and space. Likewise, testing different precision oncology approaches informed by composite and ever-changing molecular information is hard to achieve in patients. Therefore, preclinical models that incorporate the biology and genetics of human cancers, facilitate analyses of complex variables and enable adequate population throughput are needed to pinpoint randomly distributed response predictors. Patient-derived xenograft (PDX) models are dynamic entities in which cancer evolution can be monitored through serial propagation in mice. PDX models can also recapitulate interpatient diversity, thus enabling the identification of response biomarkers and therapeutic targets for molecularly defined tumour subgroups. In this Review, we discuss examples from the past decade of the use of PDX models for precision oncology, from translational research to drug discovery. We elaborate on how and to what extent preclinical observations in PDX models have confirmed and/or anticipated findings in patients. Finally, we illustrate emerging methodological efforts that could broaden the application of PDX models by honing their predictive accuracy or improving their versatility.

Dynamic and adaptive cancer stem cell population admixture in colorectal neoplasia.

Intestinal homeostasis is underpinned by LGR5+ve crypt-base columnar stem cells (CBCs), but following injury, dedifferentiation results in the emergence of LGR5-ve regenerative stem cell populations (RSCs), characterized by fetal transcriptional profiles. Neoplasia hijacks regenerative signaling, so we assessed the distribution of CBCs and RSCs in mouse and human intestinal tumors. Using combined molecular-morphological analysis, we demonstrate variable expression of stem cell markers across a range of lesions. The degree of CBC-RSC admixture was associated with both epithelial mutation and microenvironmental signaling disruption and could be mapped across disease molecular subtypes. The CBC-RSC equilibrium was adaptive, with a dynamic response to acute selective pressure, and adaptability was associated with chemoresistance. We propose a fitness landscape model where individual tumors have equilibrated stem cell population distributions along a CBC-RSC phenotypic axis. Cellular plasticity is represented by position shift along this axis and is influenced by cell-intrinsic, extrinsic, and therapeutic selective pressures.

TRF2 cooperates with CTCF for controlling the oncomiR-193b-3p in colorectal cancer.

The Telomeric Repeat binding Factor 2 (TRF2), a key protein involved in telomere integrity, is over-expressed in several human cancers and promotes tumor formation and progression. Recently, TRF2 has been also found outside telomeres where it can affect gene expression. Here we provide evidence that TRF2 is able to modulate the expression of microRNAs (miRNAs), small non-coding RNAs altered in human tumors. Among the miRNAs regulated by TRF2, we focused on miR-193b-3p, an oncomiRNA that positively correlates with TRF2 expression in human colorectal cancer patients from The Cancer Genome Atlas dataset. At the mechanistic level, the control of miR-193b-3p expression requires the cooperative activity between TRF2 and the chromatin organization factor CTCF. We found that CTCF physically interacts with TRF2, thus driving the proper positioning of TRF2 on a binding site located upstream the miR-193b-3p host-gene. The binding of TRF2 on the identified region is necessary for promoting the expression of miR-193b3p which, in turn, inhibits the translation of the onco-suppressive methyltransferase SUV39H1 and promotes tumor cell proliferation. The translational relevance of the oncogenic properties of miR-193b-3p was confirmed in patients, in whom the association between TRF2 and miR-193b-3p has a prognostic value.

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.

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.

The gRASs Is Greener: Potential New Therapies in Lung Cancer with Acquired Resistance to KRASG12C Inhibitors.

Inhibitors of KRASG12C that bind the target in its inactive conformation and lock it in off-mode have shown early signs of clinical activity in patients with KRAS G12C-mutant lung cancer, but responses tend to be short-lived and invariably prelude the development of acquired resistance through largely unexplored mechanisms. A new study describes the emergence of RAS-MAPK heterogeneous subclonal alterations in a patient relapsed on a KRASG12C inactive-state inhibitor and identifies a novel KRASY96D-resistant variant that is druggable by a next-generation compound capable of associating with KRASG12C in its active configuration.See related article by Tanaka et al., p. 1913.