bims-pimaco 2021-01-10 papers

on PI3K and MAPK signalling in colorectal cancer

Issue of 2021–01–10
ten papers selected by
Lucas B. Zeiger, CRUK Scotland Institute, Beatson Institute for Cancer Research

The amino acid transporter SLC7A5 is required for efficient growth of KRAS-mutant colorectal cancer.
A RAC-GEF network critical for early intestinal tumourigenesis.
Implications of Peak Selection in the Interpretation of Unsupervised Mass Spectrometry Imaging Data Analyses.
The Evolutionary Landscape of Treatment for BRAFV600E Mutant Metastatic Colorectal Cancer.
Gβγ recruits and activates P-Rex1 via two independent binding interfaces.
Epibrassinolide activates AKT to trigger autophagy with polyamine metabolism in SW480 and DLD-1 colon cancer cell lines.
Prediction of KRAS, NRAS and BRAF status in colorectal cancer patients with liver metastasis using a deep artificial neural network based on radiomics and semantic features.
CT Texture Analysis: A Potential Biomarker for Evaluating KRAS Mutational Status in Colorectal Cancer.
Immune landscape and prognostic immune-related genes in KRAS-mutant colorectal cancer patients.
mTORC2 deploys the mRNA binding protein IGF2BP1 to regulate c-MYC expression and promote cell survival.

Nat Genet. 2021 Jan;53(1): 16-26

The amino acid transporter SLC7A5 is required for efficient growth of KRAS-mutant colorectal cancer.

CRUK Rosetta Grand Challenge Consortium

Oncogenic KRAS mutations and inactivation of the APC tumor suppressor co-occur in colorectal cancer (CRC). Despite efforts to target mutant KRAS directly, most therapeutic approaches focus on downstream pathways, albeit with limited efficacy. Moreover, mutant KRAS alters the basal metabolism of cancer cells, increasing glutamine utilization to support proliferation. We show that concomitant mutation of Apc and Kras in the mouse intestinal epithelium profoundly rewires metabolism, increasing glutamine consumption. Furthermore, SLC7A5, a glutamine antiporter, is critical for colorectal tumorigenesis in models of both early- and late-stage metastatic disease. Mechanistically, SLC7A5 maintains intracellular amino acid levels following KRAS activation through transcriptional and metabolic reprogramming. This supports the increased demand for bulk protein synthesis that underpins the enhanced proliferation of KRAS-mutant cells. Moreover, targeting protein synthesis, via inhibition of the mTORC1 regulator, together with Slc7a5 deletion abrogates the growth of established Kras-mutant tumors. Together, these data suggest SLC7A5 as an attractive target for therapy-resistant KRAS-mutant CRC.

DOI: https://doi.org/10.1038/s41588-020-00753-3
Nat Commun. 2021 01 04. 12(1): 56

A RAC-GEF network critical for early intestinal tumourigenesis.

K A Pickering, K Gilroy, J W Cassidy, S K Fey, A K Najumudeen, L B Zeiger, D F Vincent, D M Gay, J Johansson, R P Fordham, B Miller, W Clark, A Hedley, E B Unal, C Kiel, E McGhee, L M Machesky, C Nixon, A E Johnsson, M Bain, D Strathdee, S R van Hoof, J P Medema, K I Anderson, S M Brachmann, V M Stucke, A Malliri, M Drysdale, M Turner, L Serrano, K Myant, A D Campbell, O J Sansom.

RAC1 activity is critical for intestinal homeostasis, and is required for hyperproliferation driven by loss of the tumour suppressor gene Apc in the murine intestine. To avoid the impact of direct targeting upon homeostasis, we reasoned that indirect targeting of RAC1 via RAC-GEFs might be effective. Transcriptional profiling of Apc deficient intestinal tissue identified Vav3 and Tiam1 as key targets. Deletion of these indicated that while TIAM1 deficiency could suppress Apc-driven hyperproliferation, it had no impact upon tumourigenesis, while VAV3 deficiency had no effect. Intriguingly, deletion of either gene resulted in upregulation of Vav2, with subsequent targeting of all three (Vav2-/- Vav3-/- Tiam1-/-), profoundly suppressing hyperproliferation, tumourigenesis and RAC1 activity, without impacting normal homeostasis. Critically, the observed RAC-GEF dependency was negated by oncogenic KRAS mutation. Together, these data demonstrate that while targeting RAC-GEF molecules may have therapeutic impact at early stages, this benefit may be lost in late stage disease.

DOI: https://doi.org/10.1038/s41467-020-20255-4
Anal Chem. 2021 Jan 04.

Implications of Peak Selection in the Interpretation of Unsupervised Mass Spectrometry Imaging Data Analyses.

Teresa Murta, Rory T Steven, Chelsea J Nikula, Spencer A Thomas, Lucas B Zeiger, Alex Dexter, Efstathios A Elia, Bin Yan, Andrew D Campbell, Richard J A Goodwin, Zoltan Takáts, Owen J Sansom, Josephine Bunch.

Mass spectrometry imaging can produce large amounts of complex spectral and spatial data. Such data sets are often analyzed with unsupervised machine learning approaches, which aim at reducing their complexity and facilitating their interpretation. However, choices made during data processing can impact the overall interpretation of these analyses. This work investigates the impact of the choices made at the peak selection step, which often occurs early in the data processing pipeline. The discussion is done in terms of visualization and interpretation of the results of two commonly used unsupervised approaches: t-distributed stochastic neighbor embedding and k-means clustering, which differ in nature and complexity. Criteria considered for peak selection include those based on hypotheses (exemplified herein in the analysis of metabolic alterations in genetically engineered mouse models of human colorectal cancer), particular molecular classes, and ion intensity. The results suggest that the choices made at the peak selection step have a significant impact in the visual interpretation of the results of either dimensionality reduction or clustering techniques and consequently in any downstream analysis that relies on these. Of particular significance, the results of this work show that while using the most abundant ions can result in interesting structure-related segmentation patterns that correlate well with histological features, using a smaller number of ions specifically selected based on prior knowledge about the biochemistry of the tissues under investigation can result in an easier-to-interpret, potentially more valuable, hypothesis-confirming result. Findings presented will help researchers understand and better utilize unsupervised machine learning approaches to mine high-dimensionality data.

DOI: https://doi.org/10.1021/acs.analchem.0c04179
Cancers (Basel). 2021 Jan 04. pii: E137. [Epub ahead of print]13(1):

The Evolutionary Landscape of Treatment for BRAFV600E Mutant Metastatic Colorectal Cancer.

Gianluca Mauri, Erica Bonazzina, Alessio Amatu, Federica Tosi, Katia Bencardino, Viviana Gori, Daniela Massihnia, Tiziana Cipani, Francesco Spina, Silvia Ghezzi, Salvatore Siena, Andrea Sartore-Bianchi.

  The BRAFV600E mutation is found in 8-10% of metastatic colorectal cancer (mCRC) patients and it is recognized as a poor prognostic factor with a median overall survival inferior to 20 months. At present, besides immune checkpoint inhibitors (CPIs) for those tumors with concomitant MSI-H status, recommended treatment options include cytotoxic chemotherapy + anti-VEGF in the first line setting, and a combination of EGFR and a BRAF inhibitor (cetuximab plus encorafenib) in second line. However, even with the latter targeted approach, acquired resistance limits the possibility of more than an incremental benefit and survival is still dismal. In this review, we discuss current treatment options for this subset of patients and perform a systematic review of ongoing clinical trials. Overall, we identified six emerging strategies: targeting MAPK pathway (monotherapy or combinations), targeting MAPK pathway combined with cytotoxic agents, intensive cytotoxic regimen combinations, targeted agents combined with CPIs, oxidative stress induction, and cytotoxic agents combined with antiangiogenic drugs and CPIs. In the future, the integration of new therapeutic strategies targeting key players in the BRAFV600E oncogenic pathways with current treatment approach based on cytotoxic chemotherapy and surgery is likely to redefine the treatment landscape of these CRC patients.

Keywords:  BRAF; FOLFOXIRI; colon cancer; immune checkpoint inhibitors; targeted agents

DOI:  https://doi.org/10.3390/cancers13010137
Biochem Biophys Res Commun. 2021 Jan 04. pii: S0006-291X(20)32276-2. [Epub ahead of print]539 20-27

Gβγ recruits and activates P-Rex1 via two independent binding interfaces.

Rodolfo Daniel Cervantes-Villagrana, Yarely Mabell Beltrán-Navarro, Irving García-Jiménez, Sendi Rafael Adame-García, Adán Olguín-Olguín, Guadalupe Reyes-Cruz, José Vázquez-Prado.

  Gβγ marks the inner side of the plasma membrane where chemotactic GPCRs activate Rac to lead the assembly of actin filaments that push the cell to move forward. Upon dissociation from heterotrimeric Gi, Gβγ recruits and activates P-Rex1, a Rac guanine nucleotide exchange factor (RacGEF). This cytosolic chemotactic effector is kept inactive by intramolecular interactions. The mechanism by which Gβγ stimulates P-Rex1 has been debated. We hypothesized that Gβγ activates P-Rex1 by a two-step mechanism based on independent interaction interfaces to recruit and unroll this RacGEF. Using pulldown assays, we found that Gβγ binds P-Rex1-DH/PH as well as PDZ-PDZ domains. These domains and the DEP-DEP tandem interact among them and dissociate upon binding with Gβγ, arguing for a stimulatory allosteric effect. In addition, P-Rex1 catalytic activity is inhibited by its C-terminal domain. To discern P-Rex1 recruitment from activation, we studied Q-Rhox, a synthetic RhoGEF having the PDZ-RhoGEF catalytic DH/PH module, insensitive to Gβγ, swapped into P-Rex1. Gβγ recruited Q-Rhox to the plasma membrane, indicating that Gβγ/PDZ-PDZ interaction interface plays a role on P-Rex1 recruitment. In conclusion, we reconcile previous findings and propose a mechanistic model of P-Rex1 activation; accordingly, Gβγ recruits P-Rex1 via the Gβγ/PDZ-PDZ interface followed by a second contact involving the Gβγ/DH/PH interface to unleash P-Rex1 RacGEF activity at the plasma membrane.

Keywords:  Chemotaxis; DEP domain; GPCR signaling; Gβγ; P-Rex1; PDZ domain; Rac

DOI:  https://doi.org/10.1016/j.bbrc.2020.12.089
Turk J Biol. 2020 ;44(6): 417-426

Epibrassinolide activates AKT to trigger autophagy with polyamine metabolism in SW480 and DLD-1 colon cancer cell lines.

Kaan Adacan, Pınar Obakan Yerlİkaya.

  Epibrassinolide (EBR), a plant-derived polyhydroxylated derivative of 5α-cholestane, structurally shows similarities to animal steroid hormones. According to the present study, EBR treatment triggered a significant stress response via activating ER stress, autophagy, and apoptosis in cancer cells. EBR could also increase Akt phosphorylation in vitro. While the activation of Akt resulted in cellular metabolic activation in normal cells to proceed with cell survival, a rapid stress response was induced in cancer cells to reduce survival. Therefore, Akt as a mediator of cellular survival and death decision pathways is a crucial target in cancer cells. In this study, we determined that EBR induces stress responses through activating Akt, which reduced the mTOR complex I (mTORC1) activation in SW480 and DLD-1 colon cancer cells. As a consequence, EBR triggered macroautophagy and led to lipidation of LC3 most efficiently in SW480 cells. The cotreatment of spermidine (Spd) with EBR increased lipidation of LC3 synergistically in both cell lines. We also found that EBR promoted polyamine catabolism in SW480 cells. The retention of polyamine biosynthesis was remarkable following EBR treatment. We suggested that EBR-mediated Akt activation might determine the downstream cellular stress responses to induce autophagy related to polyamines.

Keywords:  Autophagy; LC3; epibrassinolide; polyamines; spermidine

DOI:  https://doi.org/10.3906/biy-2005-37
Am J Cancer Res. 2020 ;10(12): 4513-4526

Prediction of KRAS, NRAS and BRAF status in colorectal cancer patients with liver metastasis using a deep artificial neural network based on radiomics and semantic features.

Ruichuan Shi, Weixing Chen, Bowen Yang, Jinglei Qu, Yu Cheng, Zhitu Zhu, Yu Gao, Qian Wang, Yunpeng Liu, Zhi Li, Xiujuan Qu.

There is a critical need for development of improved methods capable of accurately predicting the RAS (KRAS and NRAS) and BRAF gene mutation status in patients with advanced colorectal cancer (CRC). The purpose of this study was to investigate whether radiomics and/or semantic features could improve the detection accuracy of RAS/BRAF gene mutation status in patients with colorectal liver metastasis (CRLM). In this retrospective study, 159 patients who had been diagnosed with CRLM in two hospitals were enrolled. All patients received lung and abdominal contrast-enhanced CT (CECT) scans prior to radiation therapy and chemotherapy. Semantic features were independently assessed by two radiologists. Radiomics features were extracted from the portal venous phase (PVP) of the CT scan for each patient. Seven machine learning algorithms were used to establish three scores based on the semantic, radiomics and the combination of both features. Two semantic and 851 radiomics features were used to predict the mutation status of RAS and BRAF using an artificial neural network method (ANN). This approach performed best out of the seven tested algorithms. We constructed three scores which were based on radiomics, semantic features and the combined scores. The combined score could distinguish between wild-type and mutant patients with an AUC of 0.95 in the primary cohort and 0.79 in the validation cohort. This study proved that the application of radiomics together with semantic features can improve non-invasive assessment of the gene mutation status of RAS (KRAS and NRAS) and BRAF in CRLM.

Keywords: BRAF; RAS; artificial neural network; colorectal cancer; radiomics
Chin Med Sci J. 2020 Dec 31. 35(4): 306-314

CT Texture Analysis: A Potential Biomarker for Evaluating KRAS Mutational Status in Colorectal Cancer.

Jian Cao, Guo Rong Wang, Zhi Wei Wang, Zheng Yu Jin.

Objective Texture analysis is deemed to reflect intratumor heterogeneity invisible to the naked eyes. The aim of this study was to evaluate the feasibility of assessing the KRAS mutational status in colorectal cancer (CRC) patients using CT texture analysis. Methods This retrospective study included 92 patients who had histopathologically confirmed CRC and underwent preoperative contrast-enhanced CT examinations. The patients were assigned into a training cohort (n=51) and a validation cohort (n=41). We placed the region of interest in the tumour regions on the selected axial images using software of TexRad to extract a series of quantitative parameters based on the spatial scaling factors (SSFs), including mean, standard deviation (SD), entropy, mean of positive pixels (MPP), skewness, and kurtosis. The texture parameters and clinical characteristics (age, gender, tumour location, histopathology, tumour size, T, N, M stages) were compared between the mutated and wild-type KRAS patient groups in training cohort and validation cohort. Before building the multiple feature classifier, we calculated the correlations of the features using Pearson's correlation coefficient, and if any two features were significantly correlated, the one with lower AUC was removed. Ultimately, only the most discriminative isolated features were combined to train a supporting vector machine (SVM) classifier. The receiver operating characteristic (ROC) curve was processed for evaluating the diagnostic efficiency of texture parameters in differentiating CRC patients with mutated KRAS from those with wild-type KRAS. Results None of the clinical characteristics were significant different between CRC patients with wild-type KRAS and mutated KRAS in both cohorts. For predicting the expression of mutated KRAS in CRC patients, the perfect model which combined skewness on SSF 5 by unenhanced CT, entropy on SSF 2, skewness and kurtosis on SSF 0, and kurtosis and mean on SSF 3 by enhanced CT, showed a desirable AUC of 0.951 (95% CI: 0.895-1, P<0.001), with a sensitivity of 88.9% and a specificity of 91.7%, when the cut-off value was 0.46 in the training cohort; while in the validation cohort, the AUC value was 0.995 (95% CI: 0.982-1, P<0.001), the sensitivity was 100%, and the specificity was 93.7% when the cut-off value was 0.28. Conclusion It is feasible to evaluate the KRAS mutational status in CRC using CT texture analysis.

DOI: https://doi.org/10.24920/003770
J Transl Med. 2021 Jan 07. 19(1): 27

Immune landscape and prognostic immune-related genes in KRAS-mutant colorectal cancer patients.

Jungang Liu, Xiaoliang Huang, Haizhou Liu, Chunyin Wei, Haiming Ru, Haiquan Qin, Hao Lai, Yongsheng Meng, Guo Wu, Weishun Xie, Xianwei Mo, Caroline H Johnson, Yawei Zhang, Weizhong Tang.

   BACKGROUND: KRAS gene is the most common type of mutation reported in colorectal cancer (CRC). KRAS mutation-mediated regulation of immunophenotype and immune pathways in CRC remains to be elucidated.
METHODS: 535 CRC patients were used to compare the expression of immune-related genes (IRGs) and the abundance of tumor-infiltrating immune cells (TIICs) in the tumor microenvironment between KRAS-mutant and KRAS wild-type CRC patients. An independent dataset included 566 cases of CRC and an in-house RNA sequencing dataset were served as validation sets. An in-house dataset consisting of 335 CRC patients were used to analyze systemic immune and inflammatory state in the presence of KRAS mutation. An immue risk (Imm-R) model consist of IRG and TIICs for prognostic prediction in KRAS-mutant CRC patients was established and validated.
RESULTS: NF-κB and T-cell receptor signaling pathways were significantly inhibited in KRAS-mutant CRC patients. Regulatory T cells (Tregs) was increased while macrophage M1 and activated CD4 memory T cell was decreased in KRAS-mutant CRC. Prognosis correlated with enhanced Tregs, macrophage M1 and activated CD4 memory T cell and was validated. Serum levels of hypersensitive C-reactive protein (hs-CRP), CRP, and IgM were significantly decreased in KRAS-mutant compared to KRAS wild-type CRC patients. An immune risk model composed of VGF, RLN3, CT45A1 and TIICs signature classified CRC patients with distinct clinical outcomes.
CONCLUSIONS: KRAS mutation in CRC was associated with suppressed immune pathways and immune infiltration. The aberrant immune pathways and immune cells help to understand the tumor immune microenvironments in KRAS-mutant CRC patients.

Keywords:  Colorectal cancer; Immunosuppression; KRAS mutation; Tumor-infiltrating immune cells

DOI:  https://doi.org/10.1186/s12967-020-02638-9
Cell Signal. 2021 Jan 01. pii: S0898-6568(20)30390-9. [Epub ahead of print]80 109912

mTORC2 deploys the mRNA binding protein IGF2BP1 to regulate c-MYC expression and promote cell survival.

Andromachi Lambrianidou, Evangelia Sereti, Katerina Soupsana, Chrysoula Komini, Konstantinos Dimas, Theoni Trangas.

  mTORC2 promotes cell survival by phosphorylating AKT and enhancing its activity. Inactivation of mTORC2 reduces viability through down-regulation of E2F1 caused by up-regulation of c-MYC. An additional target of mTORC2 is IGF2BP1, an oncofetal RNA binding protein expressed de novo in a wide array of malignancies. IGF2BP1 enhances c-MYC expression by protecting the coding region instability sequence (CRD) of its mRNA from endonucleolytic cleavage. Here we show that repression of mTORC2 signalling and prevention of Ser181 phosphorylation of IGF2BP1 enhanced translation and destabilization of the endogenous c-myc mRNA as well as the mRNA of reporter transcripts carrying the CRD sequence in frame. The consequent increase in c-MYC protein was accompanied by the emergence of an apoptotic c-MYC overexpressing population. On the other hand, preventing phosphorylation of IGF2BP1 on Tyr396 by Src kinase caused the accumulation of translationally silent transcripts through sequestration by IGF2BP1 into cytoplasmic granules. The apoptotic effect of mTORC2 signalling deprivation was augmented when preceded by inhibition of IGF2BP1 phosphorylation by the Src kinase in concert with further increase of c-MYC levels because of enhanced translation of the previously stored mRNA only in the presence of IGF2BP1. Furthermore, the combined administration of mTORC2 and Src inhibitors exhibited synergism in delaying xenograft growth in female NOD.CB17-Prkdcscid/J mice. The above in vitro and in vivo findings may be applied for the induction of targeted apoptosis of cells expressing de novo the oncofetal protein IGF2BP1, a feature of aggressive malignancies resulting in a more focused anticancer therapeutic approach.

Keywords:  Apoptosis; C-MYC; IGF2BP1; Src kinase; mTORC2 kinase

DOI:  https://doi.org/10.1016/j.cellsig.2020.109912