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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.

Colorectal cancer (CRC) is a highly heterogeneous disease, showing significant variability in clinical aggressiveness and treatment response, thus largely hesitating in metastatic spread, resistance to therapies and unfavorable prognosis. Despite the documented activity of targeted therapies, resistance to drugs develops in many patients, and evaluation of more successful combination is needed to further improve outcomes. NEDD8-activating enzyme inhibitor, Pevonedistat, was previously shown to be effective for poorly differentiated, clinically aggressive CRC, thus inducing in vivo tumor stabilization, with promising clinical application. We performed an unbiased “drop-out” loss-of-function synthetic lethal screening with a shRNA library covering genes, targets of FDA-approved drugs, combined with Pevonedistat in wild-type BRAF- or KRAS-mutated CRC cell lines. The screening identified hits involved in the EGFR signaling pathway, irrespective of the cell line mutational status, suggesting that a successful combination relays on inhibition of the pathway rather than of a specific gene. We further investigated the therapeutic relevance of the combinations in BRAF and WT CRC cells and found by in-vitro and in-vivo experiments that the combined treatment with Pevonedistat and EGFR pathway inhibitors leads to increased proliferative block and apoptosis, ultimately promoting tumor regression in vivo. We further explored EGFR pathway modulation underlying these effects in multiple CRC pre-clinical models, thus defining key mediators of the combined effect and unveiling possible therapeutic opportunities in specific CRC clinical settings. Citation Format: Federica Invrea, Simona Punzi, Consalvo Petti, Rosalba Minelli, Michael Peoples, Christopher Bristow, Alessia Corrado, Valentina Vurchio, Livio Trusolino, Caterina Marchio, Alberto Bardelli, Claudio Isella, Alessandro Carugo, Giulio Draetta, Enzo Medico. Synthetic lethality screenings highlight colorectal cancer vulnerability to concomitant blockade of the NEDD8 and EGFR pathways [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1397.

Simple Summary Identification of effective therapies for clinically aggressive, treatment-resistant colorectal cancer (CRC) remains an unmet clinical need. Targeted therapies against the epidermal growth factor receptor (EGFR) signaling axis lead to clinical benefits only in a small fraction of patients due to primary and acquired resistance. We previously showed that the NEDD8 pathway inhibitor pevonedistat induced tumor stabilization in preclinical models of aggressive CRC. Here, through synthetic lethality screenings, we found that pevonedistat could be successfully combined with EGFR pathway-targeted treatments in BRAF-mutant and RAS-RAF wild-type CRCs originally resistant to BRAF and EGFR blockade. We found that combined blockade of NEDD8 and EGFR pathways reverted compensatory feedback loops that reduced the efficacy of single treatments. Our results provide preclinical validation of a promising therapeutic strategy for clinically aggressive CRC resistant to EGFR and BRAF-targeted treatments. Abstract 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.

Blockade of epidermal growth factor receptor (EGFR) causes tumor regressions in selected patients with metastatic colorectal cancer (mCRC); however, residual disease reservoirs typically remain even after maximal response to therapy, leading to relapse. Using patient-derived xenografts, we observed that mCRC cells surviving EGFR inhibition exhibited gene expression patterns reminiscent of those displayed by a quiescent subpopulation of normal intestinal secretory precursors with Paneth-cell characteristics. These pseudodifferentiated remnants had reduced expression of EGFR-activating ligands, more pronounced activity of human epidermal growth factor 2 (HER2) and human epidermal growth factor receptor 3 (HER3), and persistent signaling along the phosphatidylinositol-3-kinase (PI3K) pathway compared with untreated tumors. Clinically, residual disease traits were detected in lingering tumors of responsive patients and in tumors of individuals who had experienced early recurrence. Mechanistically, residual tumor reprogramming was mediated by inactivation of Yes-associated protein (YAP) – a master regulator of post-injury intestinal epithelium recovery – following EGFR neutralization. In preclinical trials, Pan-HER antibodies minimized residual disease, blunted PI3K signaling, and induced long-term tumor control after treatment discontinuation. By showing that tolerance to EGFR inhibition is typified by the disengagement of an in-built lineage program that drives both regenerative signaling during intestinal repair and EGFR-dependent tumorigenesis, our results shed light onto CRC lineage plasticity as an adaptive escape mechanism from therapeutic insults and suggest opportunities to pre-emptively target residual disease.

Purpose: Defects in the homologous recombination (HR) repair pathway are of clinical interest due to sensitivity of HR-deficient cells to PARP inhibitors. We were interested in defining PARP vulnerability in patients with metastatic colorectal cancer (mCRC) carrying KRAS and BRAF mutations who display poor prognosis, have limited therapeutic options, and represent an unmet clinical need. Experimental Design: We tested colorectal cancer cell lines, patient-derived organoids (PDO), and patient-derived xenografts (PDX) enriched for KRAS and BRAF mutations for sensitivity to the PARP inhibitor olaparib, and the chemotherapeutic agents oxaliplatin and 5-fluorouracil (5-FU). Genomic profiles and DNA repair proficiency of colorectal cancer models were compared with pharmacologic response. Results: Thirteen of 99 (around 13%) colorectal cancer cell lines were highly sensitive to clinically active concentrations of olaparib and displayed functional deficiency in HR. Response to PARP blockade was positively correlated with sensitivity to oxaliplatin in colorectal cancer cell lines as well as patient-derived organoids. Treatment of PDXs with olaparib impaired tumor growth and maintenance therapy with PARP blockade after initial oxaliplatin response delayed disease progression in mice. Conclusions: These results indicate that a colorectal cancer subset characterized by poor prognosis and limited therapeutic options is vulnerable to PARP inhibition and suggest that PDO-based drug-screening assays can be used to identify patients with colorectal cancer likely to benefit from olaparib. As patients with mCRC almost invariably receive therapies based on oxaliplatin, “maintenance” treatment with PARP inhibitors warrants further clinical investigation.

Patient-derived xenografts (PDXs) are obtained by transplanting fragments of a patient's tumour into immunodeficient mice. Growth and propagation of PDXs allows correlating therapeutic response in vivo with extensive, multi-dimensional molecular annotation, leading to identification of predictive biomarkers. PDXs are increasingly recognised as clinically relevant models of cancer for several reasons, of which the main is the possibility of studying the behaviour of cancer cells in a natural microenvironment, where they interact with stromal components accrued from the mouse host. PDXs maintain close similarities with the tumour of origin, in terms of tissue architecture, molecular features and response to treatments. Indeed, preclinical trials in PDXs have been shown to match and also anticipate data obtained in patients. Exploration of more complex processes like metastatic evolution and antitumour immune responses is actively pursued with PDXs, as new generations of host models emerge on the horizon.

In recent years, cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) have substantially improved the clinical outcome of pseudomyxoma peritonei (PMP) originating from mucinous appendiceal cancer. However, current histopathological grading of appendiceal PMP frequently fails in predicting disease outcome. We recently observed that the integration of cancer cell transcriptional traits with those of cancer-associated fibroblasts (CAFs) improves prognostic prediction for tumors of the large intestine. We therefore generated global expression profiles on a consecutive series of 24 PMP patients treated with CRS plus HIPEC. Multiple lesions were profiled for nine patients. We then used expression data to stratify the samples by a previously published “high-risk appendiceal cancer” (HRAC) signature and by a CAF signature that we previously developed for colorectal cancer, or by a combination of both. The prognostic value of the HRAC signature was confirmed in our cohort and further improved by integration of the CAF signature. Classification of cases profiled for multiple lesions revealed the existence of outlier samples and highlighted the need of profiling multiple PMP lesions to select representative samples for optimal performances. The integrated predictor was subsequently validated in an independent PMP cohort. These results provide new insights into PMP biology, revealing a previously unrecognized prognostic role of the stromal component and supporting integration of standard pathological grade with the HRAC and CAF transcriptional signatures to better predict disease outcome.

Angiogenesis requires the temporal coordination of the proliferation and the migration of endothelial cells. Here, we investigated the regulatory role of microRNAs (miRNAs) in harmonizing angiogenesis processes in a three-dimensional in vitro model. We described a microRNA network which contributes to the observed down- and upregulation of proliferative and migratory genes, respectively. Global analysis of miRNA–target gene interactions identified two sub-network modules, the first organized in upregulated miRNAs connected with downregulated target genes and the second with opposite features. miR-424–5p and miR-29a-3p were selected for the network validation. Gain- and loss-of-function approaches targeting these microRNAs impaired angiogenesis, suggesting that these modules are instrumental to the temporal coordination of endothelial migration and proliferation. Interestingly, miR-29a-3p and its targets belong to a selective biomarker that is able to identify colorectal cancer patients who are responding to anti-angiogenic treatments. Our results provide a view of higher-order interactions in angiogenesis that has potential to provide diagnostic and therapeutic insights.

Stratification of breast cancer (BC) into molecular subtypes by multigene expression assays is of demonstrated clinical utility. In principle, global RNA-sequencing (RNA-seq) should enable reconstructing existing transcriptional classifications of BC samples. Yet, it is not clear whether adaptation to RNA-seq of classifiers originally developed using PCR or microarrays, or reconstruction through machine learning (ML) is preferable. Hence, we focused on robustness and portability of PAM50, a nearest-centroid classifier developed on microarray data to identify five BC “intrinsic subtypes”. We found that standard PAM50 is profoundly affected by the composition of the sample cohort used for reference construction, and we propose a strategy, named AWCA, to mitigate this issue, improving classification robustness, with over 90% of concordance, and prognostic ability; we also show that AWCA-based PAM50 can even be applied as single-sample method. Furthermore, we explored five supervised learners to build robust, single-sample intrinsic subtype callers via RNA-seq. From our ML-based survey, regularized multiclass logistic regression (mLR) displayed the best performance, further increased by ad-hoc gene selection on the global transcriptome. On external test sets, mLR classifications reached 90% concordance with PAM50-based calls, without need of reference sample; mLR proven robustness and prognostic ability make it an equally valuable single-sample method to strengthen BC subtyping.

Patient-Derived Xenografts (PDXs), entailing implantation of cancer specimens in immunocompromised mice, are emerging as a valuable translational model that could help validate biologically relevant targets and assist the clinical development of novel therapeutic strategies for gastric cancer. More than 30% of PDXs generated from gastric carcinoma samples developed human B-cell lymphomas instead of gastric cancer. These lymphomas were monoclonal, Epstein Barr Virus (EBV) positive, originated tumorigenic cell cultures and displayed a mutational burden and an expression profile distinct from gastric adenocarcinomas. The ability of grafted samples to develop lymphomas did not correlate with patient outcome, nor with the histotype, the lymphocyte infiltration level, or the EBV status of the original gastric tumor, impeding from foreseeing lymphoma onset. Interestingly, lymphoma development was significantly more frequent when primary rather than metastatic samples were grafted. Notably, the development of such lympho-proliferative disease could be prevented by a short rituximab treatment upon mice implant, without negatively affecting gastric carcinoma engraftment. Due to the high frequency of human lymphoma onset, our data show that a careful histologic analysis is mandatory when generating gastric cancer PDXs. Such care would avoid misleading results that could occur if testing of putative gastric cancer therapies is performed in lymphoma PDXs. We propose rituximab treatment of mice to prevent lymphoma development in PDX models, averting the loss of human-derived samples.

Semaphorins are a family of molecular signals that guide cell migration and are implicated in the regulation of cancer cells. In particular, transmembrane semaphorins are postulated to act as both ligands ("forward" mode) and signaling receptors ("reverse" mode); however, reverse semaphorin signaling in cancer is relatively less understood. Here, we identified a previously unknown function of transmembrane semaphorin 4C (Sema4C), acting in reverse mode, to elicit nonconventional TGF-β/BMP receptor activation and selective SMAD1/5 phosphorylation. Sema4C coimmunoprecipitated with TGFBRII and BMPR1, supporting its role as modifier of this pathway. Sema4C reverse signaling led to the increased abundance of ID1/3 transcriptional factors and to extensive reprogramming of gene expression, which suppressed the typical features of the epithelial-mesenchymal transition in invasive carcinoma cells. This phenotype was nevertheless coupled with burgeoning metastatic behavior in vivo, consistent with evidence that Sema4C expression correlates with metastatic progression in human breast cancers. Thus, Sema4C reverse signaling promoted SMAD1/5- and ID1/3-dependent gene expression reprogramming and phenotypic plasticity in invasive cancer cells.

Purpose: Patient-derived xenograft (PDX) models accurately recapitulate the tumor of origin in terms of histopathology, genomic landscape, and therapeutic response, but some limitations due to costs associated with their maintenance and restricted amenability for large-scale screenings still exist. To overcome these issues, we established a platform of 2D cell lines (xeno-cell lines, XL), derived from PDXs of colorectal cancer with matched patient germline gDNA available. Experimental Design: Whole-exome and transcriptome sequencing analyses were performed. Biomarkers of response and resistance to anti-HER therapy were annotated. Dependency on the WRN helicase gene was assessed in MSS, MSI-H, and MSI-like XLs using a reverse genetics functional approach. Results: XLs recapitulated the entire spectrum of colorectal cancer transcriptional subtypes. Exome and RNA-seq analyses delineated several molecular biomarkers of response and resistance to EGFR and HER2 blockade. Genotype-driven responses observed in vitro in XLs were confirmed in vivo in the matched PDXs. MSI-H models were dependent upon WRN gene expression, while loss of WRN did not affect MSS XLs growth. Interestingly, one MSS XL with transcriptional MSI-like traits was sensitive to WRN depletion. Conclusions: The XL platform represents a preclinical tool for functional gene validation and proof-of-concept studies to identify novel druggable vulnerabilities in colorectal cancer.

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, which could impact the capacity of PDXs for faithful modeling of patient treatment response. Such results contrast with reports that have observed genomic fidelity of PDX models with respect to the originating patient tumors and from early to late passages by direct DNA measurements (DNA sequencing or SNP arrays). Here we resolve these contradicting observations by systematically evaluating CNA changes and the genes they affect during engraftment and passaging in a large, internationally collected set of PDX models, comparing both RNA and DNA-based approaches. The data collected, as part of the U.S. National Cancer Institute (NCI) PDXNet (PDX Development and Trial Centers Research Network) Consortium and EurOPDX consortium, comprises 1548 patient (PT) and PDX datasets (1451 unique samples) from 509 models derived from American, European and Asian cancer patients, spanning across 16 tumor types. By assessing copy number changes by pairwise (PT-PDX or PDX-PDX) correlation and residual analysis to control for systematic biases, our study demonstrates that prior reports of systematic copy number divergence between PTs and PDXs are incorrect, and confirms the high retention of copy number during PDX engraftment and passaging. Moreover, only a small proportion of models show large CNA discordance between the samples, suggesting that the variations observed in PDX are mainly due to rare clonal selection of individual tumors rather than murine pressures. This large scale data analysis also reveals several other findings that clarify the evolutionary process in PDXs. We do observe larger deviations between PT-PDX than in PDX-PDX comparisons, likely due to dilution of PT signal by human stromal cells. Interestingly, we found that a major contributor to the differences between PDX samples is lineage-specific drift associated with splitting of tumors into fragments during PDX propagation. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models, suggesting the lack of systematic copy number evolution driven by the PDX mouse host. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multi-region tumor samples or intra-patient samples. Thus concerns about the genetic stability of the PDX system are likely to be less important than the spatial heterogeneity of solid tumors themselves. This result is consistent with our results on lineage effects during passaging, which indicate that intratumoral spatial evolution is the major reason for genetic drift. Our in-depth tracking of CNAs throughout PDX engraftment and passaging confirms that tumors engrafted and passaged in PDX models maintain a high degree of molecular fidelity to the original patient tumors and their suitability for pre-clinical drug testing. This work also finely enumerates the copy number profiles in hundreds of publicly available models, which will enable researchers to assess the suitability of each for individualized treatment studies. Citation Format: Xing Yi Woo, Jessica Giordano, Anuj Srivastava, Zi-Ming Zhao, Michael W. Lloyd, Roebi de Bruijn, Yun-Suhk Suh, Jong-Il Kim, Han-Kwang Yang, Charles Lee, Dennis A. Dean, Brandi Davis-Dusenbery, Yvonne A. Evrard, James H. Doroshow, Alana L. Welm, Bryan Welm, Michael T. Lewis, Bingliang Fang, Jack A. Roth, Funda Meric-Bernstam, Meenhard Herlyn, Michael Davies, Li Ding, Shunqiang Li, Ramaswamy Govindan, Claudio Isella, Jeffrey A. Moscow, Livio Trusolino, Annette Byrne, Jos Jonkers, Carol J. Bult, Enzo Medico, Jeffrey H. Chuang, PDXNET consortium & EurOPDX consortium. Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1673.

Patient-Derived Xenografts (PDXs) are preclinical models largely used to study tumor biology and drug response. Recent literature highlighted the possibility that growth of human tumors in a mouse microenvironment imposes a selection driving mouse-specific genetic evolution of PDXs, which may compromise their reliability as human cancer models. Conversely, independent studies observed a conservation of the genomic landscape during PDX engraftment and passaging. We noticed that PDX genetic evolution was particularly evident in studies based on copy number aberration (CNA) inferred from gene expression data, while it was negligible when DNA-based CNA profiles were employed. Therefore, in a joint international effort of the EurOPDX and PDXNet consortia, we assembled a dataset of 37 hepatocellular and 54 gastric carcinoma tumor or PDX samples with matched RNA-based and DNA-based CNA profiles. We found that DNA-based CNA profiles invariably yield higher concordance between patient's tumor and derived PDXs than those inferred from RNA. RNA-based profiles displayed poor concordance with matched DNA-based profiles, and much lower resolution, so that they missed many focal copy number events detected by DNA-based methods. These results revealed that CNA measurements cannot be accurately estimated by expression data and that a systematic reassessment of CNA dynamics in PDXs based on DNA data is required. To this aim, we generated CNA profiles by low-pass whole genome sequencing (WGS) of 87 colorectal and 43 breast cancer triplets, each composed of matched patient's tumor (PT) and PDX at early (PDX-early) and later (PDX-late) passage. In this way, for each tumor type, we generated three perfectly matched PT, PDX-early and PDX-late cohorts and performed CNA recurrence analysis by GISTIC in each cohort. The hypothesis was that if the mouse host induces a selective pressure capable of shaping the CNA landscape during PDX engraftment and propagation, GISTIC analysis would highlight systematic and progressive changes, from the PT to the PDX-early cohort, and then to the PDX-late cohort. Notably instead, the CNA profiles of the PT and PDX-early/late cohorts were virtually indistinguishable, with no progressive accumulation or loss of CNA during PDX passage and only minor changes not functionally related or associated to cancer-driver or actionable genes. These results were not consequence of insufficient capture of the CNA repertoire, since the GISTIC profiles recapitulated those generated by TCGA for colorectal and breast cancer. In summary, our analyses highlighted that while RNA-based CNA inferences have inadequate resolution and accuracy to study genomic evolution in PDXs, DNA-based CNA profiles confirm retention of CNAs in PTs and PDXs, excluding a systematic mouse driven selection via copy number changes. Ultimately, these results support the robustness of PDXs as preclinical models for predicting drug response. Citation Format: Jessica Giordano, Xing Yi Woo, Anuj Srivastava, Zi-Ming Zhao, Michael W. Lloyd, Roebi de Bruijn, Yun-Suhk Suh, Francesco Galimi, Andrea Bertotti, Adam Lafferty, Alice C. O'Farrell, Elodie Modave, Diether Lambrechts, Petra ter Brugge, Violeta Serra, Elisabetta Marangoni, Rania El Botty, Jong-Il Kim, Han-Kwang Yang, Charles Lee, Dennis A. Dean, Brandi Davis-Dusenbery, Yvonne A. Evrard, James H. Doroshow, Alana L. Welm, Bryan E. Welm, Michael T. Lewis, Bingliang Fang, Jack Roth, Funda Meric-Bernstam, Meenhard Herlyn, Michael Davies, Li Ding, Shunqiang Li, Ramaswamy Govindan, Jeffrey A. Moscow, Carol J. Bult, Claudio Isella, Livio Trusolino, Annette T. Byrne, Jos Jonkers, Jeffrey H. Chuang, Enzo Medico, EurOPDX consortium & PDXNET consortium. Absence of mouse-specific tumor evolution in patient-derived cancer xenografts [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1118.

Colorectal cancer (CRC) develops and progresses through an accumulation of genetic and epigenetic alterations in multiple molecular pathways. Currently, targeted therapies combined with standard chemotherapy are the first-line therapy for metastatic CRC; nevertheless, the effectiveness of these drugs is limited by primary and acquired resistance. Since pathways are highly interconnected, the development of rational combinations of targeted therapies can be exploited to circumvent resistance mechanisms. As a possible alternative pathway for CRC treatment, an attractive option is the blockade of the NEDD8-ubiquitin like protein conjugation pathway. We previously found that the NEDD8-inhibitor pevonedistat has significant in vitro and in vivo activity on a subset of CRCs. However, the in vivo response is limited to tumor stabilization rather than regression, highlighting the need for therapeutic combinations. When the optimal drug combination cannot be readily predicted, functional genetic screens represent a powerful tool for unbiased exploration. We therefore carried out a synthetic lethality screening with an shRNA library covering 200 genes associated with FDA-approved drugs. The screening was aimed at identifying shRNAs that would be depleted only in the presence of pevonedistat: such constructs were expected to target genes that could harbor synergistic effects with NEDD8 inhibition. After shRNA library transduction, CRC cell lines were grown in the absence or presence of low-dose pevonedistat; Next Generation Sequencing and bioinformatics analysis allowed comparing the transduced library repertoire with or without pevonedistat, and identifying candidate synthetic lethal genes. The screening results revealed a strong, pevonedistat-dependent depletion of constructs targeting different tyrosine kinases (i.e. EGFR, BRAF, FYN and FLT4) in specific CRC cell lines (CAR1, WIDR, LIM2099 and DIFI, respectively). Firstly, we focused on the remarkable drop-out of EGFR-targeting shRNAs in CAR1 cells, which represent a subgroup of aggressive tumors refractory to cetuximab treatment, despite the lack of currently known markers of resistance. We discovered an independent and additive effect of anti-EGFR drugs (cetuximab and lapatinib) combined with pevonedistat, which was then validated in vitro on further cell lines (HCA7 and HROC69) and in vivo on HCA7-transplanted mice. Furthermore, we considered the depletion of constructs targeting BRAF, a member of EGFR pathway, observed in WIDR BRAF-mutant cells: we found an additive effect of BRAF inhibitor vemurafenib and pevonedistat in reducing in vitro cell growth. Altogether our results suggest that the concomitant pharmacological inhibition of NEDD8 and EGFR-pathway could be a novel effective approach to treat clinically aggressive CRCs, worthy of further characterization. Citation Format: Federica Invrea, Alessandro Carugo, Consalvo Petti, Cristopher Bristow, Michael Peoples, Carlotta Cancelliere, Alessia Corrado, Alberto Bardelli, Claudio Isella, Giulio F. Draetta, Enzo Medico. The NEDD8 and EGFR pathways are independent therapeutic targets in colorectal cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1935.

Receptor tyrosine kinases (RTKs) inhibitors&rsquo, activity in advanced osteosarcoma is significant but short-lived. To prevent or at least delay drug resistance, we explored a vertical inhibition by combining drugs acting at different levels of the RTK pathways (pazopanib + trametinib). We studied pazopanib + trametinib antitumor activity both in vitro and in vivo (MNNG-HOS and KHOS xenografts in NOD/SCID mice) investigating the molecular mechanisms and potential escapes. The involvement of MAPK-PI3K pathways was validated by Nanostring technology, western blot and by silencing/overexpression experiments. Pazopanib targets were expressed on seven osteosarcoma cell lines and their pathways were activated. Pazopanib + trametinib exhibited synergistic antitumor activity by inducing apoptosis and inhibiting ERK1/2 and Akt. In vivo antitumor activity was shown in osteosarcoma-bearing mice. The drug combination significantly down-modulated RTK Ephrin Type-A Receptor 2 (EphA2) and Interleukin-7 Receptor (IL-7R), whereas induced mitogen-activated protein-kinase kinase (MAPKK) MEK6. EphA2 silencing significantly reduced osteosarcoma cell proliferation and migration, while impeding MEK6 up-regulation in the treated cells significantly increased the antitumor effect of the studied drugs. Moreover, the up-regulation of MEK6 reduced combination activity. Pazopanib + trametinib demonstrated synergistic antitumor effects in osteosarcoma models through ERK and Akt inhibition and EphA2 and IL-7R down-modulation. MEK6 up-regulation might evoke escaping mechanism.

Cancer cell dependence on activated oncogenes is therapeutically targeted, but acquired resistance is virtually unavoidable. Here we show that the treatment of addicted melanoma cells with BRAF inhibitors, and of breast cancer cells with HER2-targeted drugs, led to an adaptive rise in neuropilin-1 (NRP1) expression, which is crucial for the onset of acquired resistance to therapy. Moreover, NRP1 levels dictated the efficacy of MET oncogene inhibitors in addicted stomach and lung carcinoma cells. Mechanistically, NRP1 induced a JNK-dependent signaling cascade leading to the upregulation of alternative effector kinases EGFR or IGF1R, which in turn sustained cancer cell growth and mediated acquired resistance to BRAF, HER2, or MET inhibitors. Notably, the combination with NRP1-interfering molecules improved the efficacy of oncogene-targeted drugs and prevented or even reversed the onset of resistance in cancer cells and tumor models. Our study provides the rationale for targeting the NRP1-dependent upregulation of tyrosine kinases, which are responsible for loss of responsiveness to oncogene-targeted therapies.

Background The role of forkhead-box A1 (FOXA1) and Androgen receptor (AR) in breast cancer (BC) has been extensively studied. However, the prognostic role of their co-expression in Estrogen receptor positive (ER+) BC has not been investigated so far. The aim of the present study was thus to assess the co-expression (protein and mRNA) of FOXA1 and AR in BC patients, in order to evaluate their prognostic impact according to ER status. Methods Immunohistochemical expression of AR and FOXA1 was evaluated on 479 consecutive BC, with complete clinical-pathological and follow up data. Fresh-frozen tissues from 65 cases were available. The expression of AR and FOXA1 with ER was validated using mRNA analyses. Survival and Cox proportional hazard analyses were used to evaluate the relationship between FOXA1, AR and prognosis. Results Expression of ER, AR and FOXA1 was observed in 78, 60 and 85% of cases respectively. Most AR+ cases (97%) were also FOXA1+. The level of FOXA1 mRNA positively correlated with level of both AR mRNA (r = 0.8975; P

BRAF V600E mutations occur in ∼10% of colorectal cancer cases, are associated with poor survival, and have limited responses to BRAF/MEK inhibition with or without EGFR inhibition. There is an unmet need to understand the biology of poor prognostic BRAFMT colorectal cancer. We have used differential gene expression and pathway analyses of untreated stage II and stage III BRAFMT (discovery set: n = 31; validation set: n = 26) colorectal cancer, and an siRNA screen to characterize the biology underpinning the BRAFMT subgroup with poorest outcome. These analyses identified the unfolded protein response (UPR) as a novel and druggable pathway associated with the BRAFMT colorectal cancer subgroup with poorest outcome. We also found that oncogenic BRAF drives endoplasmic reticulum (ER) stress and UPR pathway activation through MEK/ERK. Furthermore, inhibition of GRP78, the master regulator of the UPR, using siRNA or small molecule inhibition, resulted in acute ER stress and apoptosis, in particular in BRAFMT colorectal cancer cells. In addition, dual targeting of protein degradation using combined Carfilzomib (proteasome inhibitor) and ACY-1215 (HDAC6-selective inhibitor) treatment resulted in marked accumulation of protein aggregates, acute ER stress, apoptosis, and therapeutic efficacy in BRAFMT in vitro and xenograft models. Mechanistically, we found that the apoptosis following combined Carfilzomib/ACY-1215 treatment is mediated through increased CHOP expression. Taken together, our findings indicate that oncogenic BRAF induces chronic ER stress and that inducers of acute ER stress could be a novel treatment strategy for poor prognostic BRAFMT colorectal cancer. Mol Cancer Ther; 17(6); 1280–90. ©2018 AACR.

Summary The microenvironment influences cancer drug response and sustains resistance to therapies targeting receptor-tyrosine kinases. However, if and how the tumor microenvironment can be altered during treatment, contributing to resistance onset, is not known. We show that, under prolonged treatment with tyrosine kinase inhibitors (TKIs), EGFR- or MET-addicted cancer cells displayed a metabolic shift toward increased glycolysis and lactate production. We identified secreted lactate as the key molecule instructing cancer-associated fibroblasts to produce hepatocyte growth factor (HGF) in a nuclear factor κB-dependent manner. Increased HGF, activating MET-dependent signaling in cancer cells, sustained resistance to TKIs. Functional or pharmacological targeting of molecules involved in the lactate axis abrogated in vivo resistance, demonstrating the crucial role of this metabolite in the adaptive process. This adaptive resistance mechanism was observed in lung cancer patients progressed on EGFR TKIs, demonstrating the clinical relevance of our findings and opening novel scenarios in the challenge to drug resistance.

Effective stratification of cancer patients on the basis of their molecular make-up is a key open challenge. Given the altered and heterogenous nature of cancer metabolism, we here propose to use the overall expression of central carbon metabolism as biomarker to characterize groups of patients with important characteristics, such as response to ad-hoc therapeutic strategies and survival expectancy. To this end, we here introduce the data integration framework named Metabolic Reaction Enrichment Analysis ( MaREA ), which strives to characterize the metabolic deregulations that distinguish cancer phenotypes, by projecting RNA-seq data onto metabolic networks, without requiring metabolic measurements. MaREA computes a score for each network reaction, based on the expression of the set of genes encoding for the associated enzyme(s). The scores are first used as features for cluster analysis and then to rank and visualize in an organized fashion the metabolic deregulations that distinguish cancer sub-types. We applied our method to recent lung and breast cancer RNA-seq datasets from The Cancer Genome Atlas and we were able to identify subgroups of patients with significant differences in survival expectancy. We show how the prognostic power of MaREA improves when an extracted and further curated core model focusing on central carbon metabolism is used rather than the genome-wide reference network. The visualization of the metabolic differences between the groups with best and worst prognosis allowed to identify and analyze key metabolic properties related to cancer aggressiveness. Some of these properties are shared across different cancer (sub) types, e.g., the up-regulation of nucleic acid and amino acid synthesis, whereas some other appear to be tumor-specific, such as the up- or down-regulation of the phosphoenolpyruvate carboxykinase reaction, which display different patterns in distinct tumor (sub)types. These results might be soon employed to deliver highly automated diagnostic and prognostic strategies for cancer patients.

USP6NL, also named RN-tre, is a GTPase-activating protein involved in control of endocytosis and signal transduction. Here we report that USP6NL is overexpressed in breast cancer, mainly of the basal-like/integrative cluster 10 subtype. Increased USP6NL levels were accompanied by gene amplification and were associated with worse prognosis in the METABRIC dataset, retaining prognostic value in multivariable analysis. High levels of USP6NL in breast cancer cells delayed endocytosis and degradation of the EGFR, causing chronic AKT (protein kinase B) activation. In turn, AKT stabilized the glucose transporter GLUT1 at the plasma membrane, increasing aerobic glycolysis. In agreement, elevated USP6NL sensitized breast cancer cells to glucose deprivation, indicating that their glycolytic capacity relies on this protein. Depletion of USP6NL accelerated EGFR/AKT downregulation and GLUT1 degradation, impairing cell proliferation exclusively in breast cancer cells that harbored increased levels of USP6NL. Overall, these findings argue that USP6NL overexpression generates a metabolic rewiring that is essential to foster the glycolytic demand of breast cancer cells and promote their proliferation. Significance: USP6NL overexpression leads to glycolysis addiction of breast cancer cells and presents a point of metabolic vulnerability for therapeutic targeting in a subset of aggressive basal-like breast tumors. Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/13/3432/F1.large.jpg. Cancer Res; 78(13); 3432–44. ©2018 AACR.

Purpose: Patient-derived xenografts (“xenopatients”) of colorectal cancer metastases have been essential to identify genetic determinants of resistance to the anti-EGFR antibody cetuximab and to explore new therapeutic strategies. From xenopatients, a genetically annotated collection of stem-like cultures (“xenospheres”) was generated and characterized for response to targeted therapies. Experimental Design: Xenospheres underwent exome-sequencing analysis, gene expression profile, and in vitro targeted treatments to assess genetic, biological, and pharmacologic correspondence with xenopatients, and to investigate nongenetic biomarkers of therapeutic resistance. The outcome of EGFR family inhibition was tested in an NRG1-expressing in vivo model. Results: Xenospheres faithfully retained the genetic make-up of their matched xenopatients over in vitro and in vivo passages. Frequent and rare genetic lesions triggering primary resistance to cetuximab through constitutive activation of the RAS signaling pathway were conserved, as well as the vulnerability to their respective targeted treatments. Xenospheres lacking such alterations (RASwt) were highly sensitive to cetuximab, but were protected by ligands activating the EGFR family, mostly NRG1. Upon reconstitution of NRG1 expression, xenospheres displayed increased tumorigenic potential in vivo and generated tumors completely resistant to cetuximab, and sensitive only to comprehensive EGFR family inhibition. Conclusions: Xenospheres are a reliable model to identify both genetic and nongenetic mechanisms of response and resistance to targeted therapies in colorectal cancer. In the absence of RAS pathway mutations, NRG1 and other EGFR ligands can play a major role in conferring primary cetuximab resistance, indicating that comprehensive inhibition of the EGFR family is required to achieve a significant therapeutic response. Clin Cancer Res; 24(4); 807–20. ©2017 AACR. See related commentary by Napolitano and Ciardiello, p. 727

Stromal content heavily impacts the transcriptional classification of colorectal cancer (CRC), with clinical and biological implications. Lineage-dependent stromal transcriptional components could therefore dominate over more subtle expression traits inherent to cancer cells. Since in patient-derived xenografts (PDXs) stromal cells of the human tumour are substituted by murine counterparts, here we deploy human-specific expression profiling of CRC PDXs to assess cancer-cell intrinsic transcriptional features. Through this approach, we identify five CRC intrinsic subtypes (CRIS) endowed with distinctive molecular, functional and phenotypic peculiarities: (i) CRIS-A: mucinous, glycolytic, enriched for microsatellite instability or KRAS mutations; (ii) CRIS-B: TGF-β pathway activity, epithelial–mesenchymal transition, poor prognosis; (iii) CRIS-C: elevated EGFR signalling, sensitivity to EGFR inhibitors; (iv) CRIS-D: WNT activation, IGF2 gene overexpression and amplification; and (v) CRIS-E: Paneth cell-like phenotype, TP53 mutations. CRIS subtypes successfully categorize independent sets of primary and metastatic CRCs, with limited overlap on existing transcriptional classes and unprecedented predictive and prognostic performances., Stromal cells contribute to the gene expression profiles based on which colorectal cancer (CRC) molecular subtypes are classified. Here, patient-derived xenografts enable the authors to obtain cancer cell-specific transcriptomes by excluding transcripts from murine stromal cells, based on which they define CRC intrinsic subtypes (CRIS) and evaluate their prognostic and predictive potential.

The inflammatory cytokine Tumor Necrosis Factor Alpha (TNF-α) is known to trigger invasive growth, a physiological property for tissue healing, turning into a hallmark of progression in cancer. However, the invasive response to TNF-α relies on poorly understood molecular mechanisms. We thus investigated whether it involves the MET oncogene, which regulates the invasive growth program by encoding the tyrosine kinase receptor for Hepatocyte Growth Factor (HGF). Here we show that the TNF-α pro-invasive activity requires MET function, as it is fully inhibited by MET-specific inhibitors (small-molecules, antibodies, and siRNAs). Mechanistically, we show that TNF-α induces MET transcription via NF-κB, and exploits MET to sustain MEK/ERK activation and Snail accumulation, leading to E-cadherin downregulation. We then show that TNF-α not only induces MET expression in cancer cells, but also HGF secretion by fibroblasts. Consistently, we found that, in human colorectal cancer tissues, high levels of TNF-α correlates with increased expression of both MET and HGF. These findings suggest that TNF-α fosters a HGF/MET pro-invasive paracrine loop in tumors. Targeting this ligand/receptor pair would contribute to prevent cancer progression associated with inflammation.

Background The diagnosis of colorectal cancer (CRC) is routinely accomplished through histopathologic examination. Prognostic information and treatment decisions are mainly determined by TNM classification, first defined in 1968. In the last decade, patient-specific CRC genomic landscapes were shown to provide important prognostic and predictive information. Therefore, there is a need for developing next generation sequencing (NGS) and bioinformatic workflows that can be routinely used for the assessment of prognostic and predictive biomarkers. Materials and Methods To foster the application of genomics in the clinical management of CRCs, the IDEA workflow has been built to easily adapt to the availability of patient specimens and the clinical question that is being asked. Initially, IDEA deploys ad-hoc NGS assays to interrogate predefined genomic target sequences (from 600 kb to 30 Mb) with optimal detection sensitivity. Next, sequencing data are processed through an integrated bioinformatic pipeline to assess single nucleotide variants, insertions and deletions, gene copy-number alterations, and chromosomal rearrangements. The overall results are gathered into a user-friendly report. Results We provide evidence that IDEA is capable of identifying clinically relevant molecular alterations. When optimized to analyze circulating tumor DNA, IDEA can be used to monitor response and relapse in the blood of patients with metastatic CRC receiving targeted agents. IDEA detected primary and secondary resistance mechanisms to ERBB2 blockade including sub-clonal RAS and BRAF mutations. Conclusions The IDEA workflow provides a flexible platform to integrate NGS and bioinformatic tools for refined diagnosis and management of patients with advanced CRC.

Background The NEDD8 conjugation pathway modulates the ubiquitination and activity of a wide range of intracellular proteins, and its blockade by pevonedistat is emerging as a promising therapeutic approach in various cancer settings. However, systematic characterization of pevonedistat efficacy in specific tumor types and definition of response predictors are still missing. Methods We investigated in vitro sensitivity to pevonedistat in 122 colorectal cancer (CRC) cell lines by an ATP-based proliferation assay and evaluated apoptosis and DNA content by flow cytometry. Associations between pevonedistat sensitivity and CRC molecular features were assessed by Student's t test. A 184-gene transcriptional predictor was generated in cell lines and applied to 87 metastatic CRC samples for which patient-derived xenografts (PDXs) were available. In vivo reponse to pevonedistat was assessed in PDX models (≥5 mice per group). All statistical tests were two-sided. Results Sixteen (13.1%) cell lines displayed a marked response to pevonedistat, featuring DNA re-replication, proliferative block, and increased apoptosis. Pevonedistat sensitivity did not statistically significantly correlate with microsatellite instability or mutations in KRAS or BRAF and was functionally associated with low EGFR pathway activity. While ineffective on predicted resistant PDXs, in vivo administration of pevonedistat statistically significantly impaired growth of five out of six predicted sensitive models (P < .01). In samples from CRC patients, transcriptional prediction of pevonedistat sensitivity was associated with poor prognosis after surgery (hazard ratio [HR] = 2.49, 95% confidence interval [CI] = 1.34 to 4.62, P = .003) and early progression under cetuximab treatment (HR = 3.59, 95% CI = 1.60 to 8.04, P < .001). Histological and immunohistochemical analyses revealed that the pevonedistat sensitivity signature captures transcriptional traits of poor differentiation and high-grade mucinous adenocarcinoma. Conclusions These results highlight NEDD8-pathway inhibition by pevonedistat as a potentially effective treatment for poorly differentiated, clinically aggressive CRC.

MicroRNA (miRNA) expression profile can be used as prognostic marker for human cancers. We aim to explore the significance of miRNAs in colorectal cancer (CRC) metastasis.We performed miRNA microarrays using primary CRC tissues from patients with and without metastasis, and validated selected candidates in 85 CRC samples by quantitative real-time PCR (qRT-PCR). We tested metastatic activity of selected miRNAs and identified miRNA targets by prediction algorithms, qRT-PCR, western blot and luciferase assays. Clinical outcomes were analysed in six sets of CRC cases (n=449), including The Cancer Genome Atlas (TCGA) consortium and correlated with miR-224 status. We used the Kaplan-Meier method and log-rank test to assess the difference in survival between patients with low or high levels of miR-224 expression.MiR-224 expression increases consistently with tumour burden and microsatellite stable status, and miR-224 enhances CRC metastasis in vitro and in vivo. We identified SMAD4 as a miR-224 target and observed negative correlation (Spearman Rs=-0.44, p0.0001) between SMAD4 and miR-224 expression in clinical samples. Patients with high miR-224 levels display shorter overall survival in multiple CRC cohorts (p=0.0259, 0.0137, 0.0207, 0.0181, 0.0331 and 0.0037, respectively), and shorter metastasis-free survival (HR 6.51, 95% CI 1.97 to 21.51, p=0.0008). In the TCGA set, combined analysis of miR-224 with SMAD4 expression enhanced correlation with survival (HR 4.12, 95% CI 1.1 to 15.41, p=0.0175).MiR-224 promotes CRC metastasis, at least in part, through the regulation of SMAD4. MiR-224 expression in primary CRC, alone or combined with its targets, may have prognostic value for survival of patients with CRC.

Purpose: MET, the tyrosine kinase receptor for hepatocyte growth factor, is frequently overexpressed in colon cancers with high metastatic tendency. We aimed to evaluate the role of its negative regulators, miR-1 and miR-199a*, and its transcriptional activator, the metastasis-associated in colon cancer 1 (MACC1), in controlling MET expression in human colon cancer samples. Experimental Design: The expression of MET, miR-1, miR-199a*, and MACC1 was evaluated by real-time PCR in 52 matched pairs of colorectal cancers and nontumoral surrounding tissues. The biological role of miR-1 in controlling MET expression and biological activity was assessed in colon cancer cells either by its forced expression or by AntagomiR-mediated inhibition. Results: MiR-1 was downregulated in 84.6% of the tumors and its decrease significantly correlated with MET overexpression, particularly in metastatic tumors. We found that concurrent MACC1 upregulation and miR-1 downregulation are required to elicit the highest increase of MET expression. Consistent with a suppressive role of miR-1, its forced in vitro expression in colon cancer cells reduced MET levels and impaired MET-induced invasive growth. Finally, we identified a feedback loop between miR-1 and MET, resulting in their mutual regulation. Conclusions: This study identifies an oncosuppressive role of miR-1 in colorectal cancer in which it acts by controlling MET expression through a feedback loop. Concomitant downregulation of miR-1 and increase of MACC1 can thus contribute to MET overexpression and to the metastatic behavior of colon cancer cells. Clin Cancer Res; 18(3); 737–47. ©2011 AACR.

Only a fraction of patients with metastatic colorectal cancer receive clinical benefit from therapy with anti-epidermal growth factor receptor (EGFR) antibodies, which calls for the identification of novel biomarkers for better personalized medicine. We produced large xenograft cohorts from 85 patient-derived, genetically characterized metastatic colorectal cancer samples (“xenopatients”) to discover novel determinants of therapeutic response and new oncoprotein targets. Serially passaged tumors retained the morphologic and genomic features of their original counterparts. A validation trial confirmed the robustness of this approach: xenopatients responded to the anti-EGFR antibody cetuximab with rates and extents analogous to those observed in the clinic and could be prospectively stratified as responders or nonresponders on the basis of several predictive biomarkers. Genotype–response correlations indicated HER2 amplification specifically in a subset of cetuximab-resistant, KRAS/NRAS/BRAF/PIK3CA wild-type cases. Importantly, HER2 amplification was also enriched in clinically nonresponsive KRAS wild-type patients. A proof-of-concept, multiarm study in HER2-amplified xenopatients revealed that the combined inhibition of HER2 and EGFR induced overt, long-lasting tumor regression. Our results suggest promising therapeutic opportunities in cetuximab-resistant patients with metastatic colorectal cancer, whose medical treatment in the chemorefractory setting remains an unmet clinical need. Significance: Direct transfer xenografts of tumor surgical specimens conserve the interindividual diversity and the genetic heterogeneity typical of the tumors of origin, combining the flexibility of preclinical analysis with the informative value of population-based studies. Our suite of patient-derived xenografts from metastatic colorectal carcinomas reliably mimicked disease response in humans, prospectively recapitulated biomarker-based case stratification, and identified HER2 as a predictor of resistance to anti-epidermal growth factor receptor antibodies and of response to combination therapies against HER2 and epidermal growth factor receptor in this tumor setting. Cancer Discovery; 1(6); 508–23. ©2011 AACR. Read the Commentary on this article by Ciardiello and Normanno, p. 472 This article is highlighted in the In This Issue feature, p. 457

Purpose: We determined the gene copy numbers for MET, for its transcriptional activator MACC1 and for its ligand hepatocyte growth factor (HGF) in liver metastases from colorectal carcinoma (mCRC). We correlated copy numbers with mRNA levels and explored whether gain and/or overexpression of MET and MACC1 predict response to anti-Met therapies. Finally, we assessed whether their genomic or transcriptional deregulation correlates with pathologic and molecular parameters of aggressive disease. Experimental Design: One hundred three mCRCs were analyzed. Copy numbers and mRNA were determined by quantitative PCR (qPCR). Thirty nine samples were implanted and expanded in NOD (nonobese diabetic)/SCID (severe combined immunodeficient) mice to generate cohorts that were treated with the Met inhibitor JNJ-38877605. In silico analysis of MACC1 targets relied on genome-wide mapping of promoter regions and on expression data from two CRC datasets. Results: No focal, high-grade amplifications of MET, MACC1, or HGF were detected. Chromosome 7 polysomy and gain of the p-arm were observed in 21% and 8% of cases, respectively, and significantly correlated with higher expression of both Met and MACC1. Met inhibition in patient-derived xenografts did not modify tumor growth. Copy number gain and overexpression of MACC1 correlated with unfavorable pathologic features better than overexpression of Met. Bioinformatic analysis of putative MACC1 targets identified elements besides Met, whose overexpression cosegregated with aggressive forms of colorectal cancer. Conclusions: Experiments in patient-derived xenografts suggest that mCRCs do not rely on Met genomic gain and/or overexpression for growth. On the basis of pathologic correlations and bioinformatic analysis, MACC1 could contribute to CRC progression through mechanisms other than or additional to Met transcriptional upregulation. Clin Cancer Res; 17(10); 3146–56. ©2011 AACR.

Colorectal cancer (CRC) biopsies underpin accurate diagnosis, but are also relevant for patient stratification in molecularly-guided clinical trials. The consensus molecular subtypes (CMS) and colorectal cancer intrinsic subtypes (CRIS) transcriptional signatures have potential clinical utility for improving prognostic/predictive patient assignment. However, their ability to provide robust classification, in pre-treatment biopsies from multiple regions or at different time points remains untested. In this study, we undertook a comprehensive assessment of the robustness of CRC transcriptional signatures, including CRIS and CMS, using a range of tumour sampling methodologies currently employed in clinical and translational research. These include analyses using (i) laser-capture microdissected CRC tissue, (ii) eight publically available rectal cancer biopsy data sets (n=543), (iii) serial biopsies (from AXEBeam trial, NCT00828672; n=10), (iv) multi-regional biopsies from colon tumours (n=29 biopsies, n=7 tumours) and (v) pre-treatment biopsies from the phase II rectal cancer trial COPERNCIUS (NCT01263171; n=44). Compared to previous results obtained using CRC resection material, we now demonstrate that CMS classification in biopsy tissue is significantly less capable of reliably classifying patient subtype (43% unknown in biopsy versus 13% unknown in resections, p=0.0001). In contrast, there was no significant difference in classification rate between biopsies and resections when using the CRIS classifier. Additionally, we demonstrated that CRIS provides significantly better spatially- and temporally- robust classification of molecular subtypes in CRC primary tumour tissue compared to CMS (p= 0.003 and p=0.02, respectively). These findings may have potential to inform ongoing biopsy-based patient stratification in CRC, enabling robust and stable assignment of patients into clinically-informative arms of prospective multi-arm, multi-stage clinical trials. Citation Format: Matthew Alderdice, Susan D. Richman, Simon Gollins, Peter Stewart, Chris Hurt, Richard Adams, Amy M. McCorry, Aideen Roddy, Dale Vimalachandran, Claudio Isella, Enzo Medico, Tim Maughan, Darrgh G. McArt, Mark Lawler, Philip D. Dunne. Prospective patient stratification into robust cancer-cell intrinsic subtypes from colorectal cancer biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5365.

Currently, the first line therapy for metastatic colorectal cancer (CRC) is the FOLFOX regimen, which includes Oxaliplatin in combination with Fluorouracil and Leucovorin. Responses to FOLFOX range from overt regressions (35%) to full resistance (25%), and eventually all patients become resistant. Indeed, the molecular mechanisms of Oxaliplatin resistance remain mostly to be understood. To identify genes involved in sensitivity/resistance to Oxaliplatin, we designed an integrated approach including forward genetic screens and computational analyses. The pipeline includes: (i) stable transduction of CRC cells with pooled shRNA libraries; (ii) Oxaliplatin treatment for six weeks to select a drug-resistant subpopulation; (iii) identification of shRNA constructs enriched in the Oxaliplatin-resistant subpopulation by next-generation sequencing analysis. We focused the shRNA libraries targeting phosphatases and ubiquitin conjugation pathway genes. The first are involved in several biological processes, reversing the biochemical activity of kinases and typically acting as feedback loop regulators. The second direct proteins to degradation by the proteasome regulating homeostasis, cell cycle, and DNA repair pathways. HCT116 CRC cells, markedly sensitive to Oxaliplatin, were transduced in duplicate with both shRNA libraries. After Oxaliplatin treatment for six weeks, resistant populations emerged from the library-transduced cells, but not from control-transduced cells. To reveal shRNA constructs responsible of such phenotype, we extracted genomic DNA from transduced cells and, upon amplification of shRNA constructs by targeted PCR and next-generation sequencing, we compared the repertoire of shRNA sequences in HCT116 cells selected with Oxaliplatin with that of cells grown in standard medium. Screening hits were then prioritized for functional characterization, resulting in a phosphatase (CDC25C) and an ubiquitin ligase candidate (DCAF17). In conclusion, we successfully setup a functional genomic screening for acquired resistance to Oxaliplatin in CRC. Specific shRNA constructs from both the phosphatase and ubiquitin ligase libraries were enriched after Oxaliplatin treatment, highlighting candidate genes whose loss of function could potentially drive resistances to Oxaliplatin. Citation Format: Federica Invrea, Francesca Cavicchioli, Consalvo Petti, Rosalia Russo, Claudio Isella, Enzo Medico. A functional genomics approach to the identification of genes involved in resistance to Oxaliplatin in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4038.

The best clinical and molecular criteria currently adopted in the diagnosis of colorectal cancer (CRC) often fail to predict the natural history of the disease, or to provide information regarding the molecular mechanisms inducing cancer onset and progression. To address these issues, molecular taxonomies based on transcriptional CRC subtypes have been developed; however, since the CRC transcriptome is heavily affected by mRNAs of stromal origin, these transcriptional traits are not specifically associated with cancer cell-intrisic features. To overcome this limitation, we recently employed gene expression profiles of CRC tissues specifically deprived of stromal transcripts to define “colorectal cancer cell-intrisinc subtypes” (CRIS). CRIS classification is not only bestowed with high prognositc and predictive value: it also conveys biological and molecular information on the subtypes, that may be tailored for specific therapies. To assess reliability of CRIS subtyping in preclinical CRC models, we designed a “XenoLine” platform, composed of 60 CRC cell lines representative of each CRIS class, grown in vitro and implanted in NOD-SCID mice to obtain xenograft tissues. After subcutaneous injection of 5 milion cells, xenografts were allowed to grow until they reached 2500 mm3 and were explanted. Engraftments were performed in duplicate and had a success rate around 85%. Further engraftments are ongoing. RNA-seq analysis was employed to compare in vivo- and in vitro-grown cells, and evaluate the stability of CRIS subtypes. The XenoLine RNA-seq profiles were in-silico microdissected, discriminating transcripts of epithelial cancer cell origin (human reads) from transcripts of stromal origin (mouse reads). Comparing paired in vitro / in vivo gene expression profiles, we observed that: 1) matched model pair correlation was systematically higher that random pair correlations; 2) for most genes, variation of expression across cells was consistent between in vitro and in vivo profiles; 3) CRIS classification was substantially maintained upon xenograft propagation. In conclusion, the molecular features distinguishing CRIS subtypes are resilient to major changes in cell growth conditions, such as changes in the microenvironment and acquisition of supporting stroma. The XenoLine platform was successfully established and will be further extended to better ascertain differences between in vitro- and in vivo- grown CRC cells of variable molecular makeup. Citation Format: Claudio Isella, Consalvo Petti, Carlotta Cancelliere, Daniela Cantarella, Roberta Porporato, Livio Trusolino, Andrea Bertotti, Alberto Bardelli, Enzo Medico. Conservation of colorectal cancer cell-intrisinc transcriptional traits in paired in vitro / in vivo cellular models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3403.

Introduction Progress in the development of effective cancer treatments is limited by the availability of tumour models that accurately reflect patient tumour with regards to histopathology, genomic landscape, and therapeutic response. To accomplish these needs, patient-derived tumour xenografts (PDX) were developed in recent years. Although they closely mirror structural and molecular features of the tumour of origin, PDXs still retain important restrictions related to maintenance costs and large-scale screening. To overcome this issue, we have established a novel platform of 2D cell lines (xeno-cell lines, XL) derived from PDXs of colorectal cancer (CRC) from which patient’s germline gDNA was available. We have characterised XL-cells at multiple levels to assess their suitability as patient avatars to interrogate functional networks in colorectal cancer. Material and methods Exome and expression analysis were performed on the entire xeno-cell line collection. Biomarkers of response and resistance to anti-HER therapy have been annotated in cell lines and pharmacological analysis to validate drug targets has been accordingly completed. Results and discussions All XL-cells showed an epithelial-like morphology and phenotype, as also confirmed by EMT biomarker analysis. Genetic features (mutation and copy number profiles) were consistently preserved between PDXs and matched cell models, and expression analysis revealed XL-line collection as a significant representative of all CRC subtypes (CMS and CRIS subgroups). Whole exome and RNA-seq analyses allowed the identification of molecular biomarkers of response and resistance to targeted therapies, including EGFR and HER2 blockade. Genotype-driven responses observed in vitro in XL-cells were confirmed in vivo in the corresponding PDX. Conclusion The XL-cell line platform represents a valuable preclinical tool for functional gene validation and proof of concept studies of novel therapeutics in colorectal cancer.

Recent studies identified a poor-prognosis stem/serrated/mesenchymal (SSM) transcriptional subtype of colorectal cancer (CRC). We noted that genes upregulated in this subtype are also prominently expressed by stromal cells, suggesting that SSM transcripts could derive from stromal rather than epithelial cancer cells. To test this hypothesis, we analyzed CRC expression data from patient-derived xenografts, where mouse stroma supports human cancer cells. Species-specific expression analysis showed that the mRNA levels of SSM genes were mostly due to stromal expression. Transcriptional signatures built to specifically report the abundance of cancer-associated fibroblasts (CAFs), leukocytes or endothelial cells all had significantly higher expression in human CRC samples of the SSM subtype. High expression of the CAF signature was associated with poor prognosis in untreated CRC, and joint high expression of the stromal signatures predicted resistance to radiotherapy in rectal cancer. These data show that the distinctive transcriptional and clinical features of the SSM subtype can be ascribed to its particularly abundant stromal component.

Among patients with colorectal cancer who benefit from therapy targeted to the epidermal growth factor receptor (EGFR), stable disease (SD) occurs more frequently than massive regressions. Exploring the mechanisms of this incomplete sensitivity to devise more efficacious treatments will likely improve patients' outcomes. We tested therapies tailored around hypothesis-generating molecular features in patient-derived xenografts ("xenopatients"), which originated from 125 independent samples that did not harbor established resistance-conferring mutations. Samples from xenopatients that responded to cetuximab, an anti-EGFR agent, with disease stabilization displayed high levels of EGFR family ligands and receptors, indicating high EGFR pathway activity. Five of 21 SD models (23.8%) characterized by particularly high expression of EGFR and EGFR family members regressed after intensified EGFR blockade by cetuximab and a small-molecule inhibitor. In addition, a subset of cases in which enhanced EGFR inhibition was unproductive (6 of 16, 37.5%) exhibited marked overexpression of insulin-like growth factor 2 (IGF2). Enrichment of IGF2 overexpressors among cases with SD was demonstrated in the entire xenopatient collection and was confirmed in patients by mining clinical gene expression data sets. In functional studies, IGF2 overproduction attenuated the efficacy of cetuximab. Conversely, interception of IGF2-dependent signaling in IGF2-overexpressing xenopatients potentiated the effects of cetuximab. The clinical implementation of IGF inhibitors awaits reliable predictors of response, but the results of this study suggest rational combination therapies for colorectal cancer and provide evidence for IGF2 as a biomarker of reduced tumor sensitivity to anti-EGFR therapy and a determinant of response to combined IGF2/EGFR targeting.

The development of molecularly targeted anticancer agents relies on large panels of tumour-specific preclinical models closely recapitulating the molecular heterogeneity observed in patients. Here we describe the mutational and gene expression analyses of 151 colorectal cancer (CRC) cell lines. We find that the whole spectrum of CRC molecular and transcriptional subtypes, previously defined in patients, is represented in this cell line compendium. Transcriptional outlier analysis identifies RAS/BRAF wild-type cells, resistant to EGFR blockade, functionally and pharmacologically addicted to kinase genes including ALK, FGFR2, NTRK1/2 and RET. The same genes are present as expression outliers in CRC patient samples. Genomic rearrangements (translocations) involving the ALK and NTRK1 genes are associated with the overexpression of the corresponding proteins in CRC specimens. The approach described here can be used to pinpoint CRCs with exquisite dependencies to individual kinases for which clinically approved drugs are already available.

Molecular classification of colorectal cancer (CRC) based on gene expression profiling of tumor samples is known to be heavily affected by transcripts of stromal origin. As a consequence, current CRC transcriptional subtypes reflect an admixture of cancer cell-intrinsic traits and tumor microenvironment features. Whether selective analysis of the cancer cell transcriptome could improve CRC subtyping, remains an open issue. In patient-derived xenografts (PDXs), human transcripts only originate from cancer cells, because stromal transcripts are of mouse origin. We therefore assessed cancer-cell intrinsic transcriptional features of CRC by generating human-specific expression profiles of 515 PDXs from 244 CRC patients, and performing unsupervised class discovery. We identified five “CRC intrinsic subtypes” (CRIS A-E) only partially overlapping with the current ones, and robustly enriched for distinct molecular, functional and phenotypic traits: (i) CRIS-A: mucinous, glycolytic, CIMP, and enriched for microsatellite instability or mutations in KRAS; (ii) CRIS-B: marked TGF-β pathway activity, epithelial-mesenchymal transition and poor prognosis; (iii) CRIS-C: MSS, elevated EGFR signaling and sensitivity to EGFR-targeted treatments; (iv) CRIS-D: MSS, WNT activation, and IGF2 overexpression and amplification; (v) CRIS-E: MSS, Paneth cell-like phenotype and higher frequency of TP53 mutation. CRIS subtypes successfully categorized independent sets of primary and metastatic CRCs and cell lines, for a total of over 3000 samples profiled by microarrays and RNAseq. The new subtypes displayed unprecedented predictive and prognostic performances, indipendent from known markers including stromal signatures, whose integration with CRIS further enhanced prognostic significance. Citation Format: Claudio Isella, Sara E. Bellomo, Francesco Brundu, Francesco Galimi, Elisa Ficarra, Luigi Marchionni, Livio Trusolino, Andrea Bertotti, Enzo Medico. Cancer cell-selective transcriptome analysis reveals new colorectal cancer molecular subtypes with improved biological resolution and superior predictive and prognostic performance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1742. doi:10.1158/1538-7445.AM2017-1742

Metastatic spread to the liver is a frequent complication of colorectal cancer (CRC), occurring in almost half of the cases, for which personalized treatment strategies are highly desirable. To this aim, it has been proven that patient-derived mouse xenografts (PDX) of liver-metastatic CRC can be used to discover new therapeutic targets and determinants of drug resistance. To identify gene fusions in RNA-Seq data obtained from such PDX samples, we propose a novel pipeline that tackles the following issues: (i) discriminating human from murine RNA, to filter out transcripts contributed by the mouse stroma that supports the PDX; (ii) increasing sensitivity in case of suboptimal RNA-Seq coverage; (iii) prioritizing the detected chimeric transcripts by molecular features of the fusion and by functional relevance of the involved genes; (iv) providing appropriate sequence information for subsequent validation of the identified fusions. The pipeline, built on top of Chimerascan(R.Iyer, 2011) and deFuse(McPherson, 2011) aligner tools, was successfully applied to RNASeq data from 11 PDX samples. Among the 299 fusion genes identified by the aforementioned softwares, five were selected since passed all the filtering stages implemented into the proposed pipeline resulting as biologically relevant fusions. Three of them were experimentally confirmed.

Objective: Upon colon cancer metastasis resection in liver, disease outcome is heterogeneous, ranging from indolent to very aggressive, with early recurrence. The aim of this study is to investigate the capability of metastasis associated in colon cancer 1 (MACC1) levels measured in liver metastasis specimens to predict further recurrence of the disease. Methods: Gene expression and gene dosage of MACC1, hepatocyte growth factor (HGF), and hepatocyte growth factor receptor (MET) were assessed using quantitative realtime polymerase chain reaction on a cohort of 64 liver metastasis samples from patients with complete follow-up of 36 months and detailed clinical annotation. The most relevant mutations associated to prognosis in colorectal cancer, KRAS, and PIK3CA were assessed on the same specimens with Sanger sequencing. Results: Receiver operating characteristic (ROC) analysis revealed that MACC1 mRNA abundance is a good indicator of metastatic recurrence (AUC = 0.65, P < 0.05), whereas no such results were obtained with MET and HGF, nor with gene dosage. Generation of MACC1-based risk classes was capable of successfully separating patients into poor and good prognosis subgroups [hazard ratio (HR) = 5.236, 95% confidence interval (CI) = 1.2068–22.715, P < 0.05]. Also KRAS mutation was significantly associated with higher risk of recurrence (HR = 2.07, 95% CI = 1.048–4.09, P < 0.05). Cox regression multivariate analysis supported the independence of MACC1, but not KRAS, from known prognostic clinical information (Node Size HR = 3.155, 95% CI = 1.4418–6.905, P < 0.001, Preoperative carcinoembryonic antigen HR = 2.359, 95% CI = 1.0203–5.452, P < 0.05, MACC1 HR = 7.2739, 95% CI = 1.6584–31.905, P < 0.01). Conclusions: MACC1, a new easily detectable biomarker in cancer, is an independent prognostic factor of recurrence after liver resection of colorectal cancer metastasis.

Background: Bone metastases represent a common and severe complication in breast cancer, and the involvement of cancer stem cells (CSCs) in the promotion of bone metastasis is currently under discussion. Here, we used a human-in-mice model to study bone metastasis formation due to primary breast CSCs-like colonisation. Methods: Primary CD44+CD24− breast CSCs-like were transduced by a luciferase-lentiviral vector and injected through subcutaneous and intracardiac (IC) routes in non-obese/severe-combined immunodeficient (NOD/SCID) mice carrying subcutaneous human bone implants. The CSCs-like localisation was monitored by in vivo luciferase imaging. Bone metastatic CSCs-like were analysed through immunohistochemistry and flow cytometry, and gene expression analyses were performed by microarray techniques. Results: Breast CSCs-like colonised the human-implanted bone, resulting in bone remodelling. Bone metastatic lesions were histologically apparent by tumour cell expression of epithelial markers and vimentin. The bone-isolated CSCs-like were CD44−CD24+ and showed tumorigenic abilities after injection in secondary mice. CD44−CD24+ CSCs-like displayed a distinct bone tropism signature that was enriched in genes that discriminate bone metastases of breast cancer from metastases at other organs. Conclusion: Breast CSCs-like promote bone metastasis and display a CSCs-like bone tropism signature. This signature has clinical prognostic relevance, because it efficiently discriminates osteotropic breast cancers from tumour metastases at other sites.

Nat. Genet. 47, 312–319 (2015); published online 23 February 2015; corrected after print 29 August 2016 In the version of this article initially published, an affiliation for author Zsolt Fekete was incorrectly omitted. The missing affiliation was to the Department of Oncology, University of Medicine and Pharmacy Iuliu Hatieganu, Cluj-Napoca, Romania.