Most tumors exhibit increased glucose metabolism to lactate, however, the extent to which glucose-derived metabolic fluxes are used for alternative processes is poorly understood. Using a ...metabolomics approach with isotope labeling, we found that in some cancer cells a relatively large amount of glycolytic carbon is diverted into serine and glycine metabolism through phosphoglycerate dehydrogenase (PHGDH). An analysis of human cancers showed that PHGDH is recurrently amplified in a genomic region of focal copy number gain most commonly found in melanoma. Decreasing PHGDH expression impaired proliferation in amplified cell lines. Increased expression was also associated with breast cancer subtypes, and ectopic expression of PHGDH in mammary epithelial cells disrupted acinar morphogenesis and induced other phenotypic alterations that may predispose cells to transformation. Our findings show that the diversion of glycolytic flux into a specific alternate pathway can be selected during tumor development and may contribute to the pathogenesis of human cancer.
Fusions involving the oncogenic gene RET have been observed in thyroid and lung cancers. Here we report RET gene alterations, including amplification, missense mutations, known fusions, novel ...fusions, and rearrangements in breast cancer. Their frequency, oncogenic potential, and actionability in breast cancer are described. Two out of eight RET fusions (NCOA4-RET and a novel RASGEF1A-RET fusion) and RET amplification were functionally characterized and shown to activate RET kinase and drive signaling through MAPK and PI3K pathways. These fusions and RET amplification can induce transformation of non-tumorigenic cells, support xenograft tumor formation, and render sensitivity to RET inhibition. An index case of metastatic breast cancer progressing on HER2-targeted therapy was found to have the NCOA4-RET fusion. Subsequent treatment with the RET inhibitor cabozantinib led to a rapid clinical and radiographic response. RET alterations, identified by genomic profiling, are promising therapeutic targets and are present in a subset of breast cancers.
Several lines of evidence indicate that during transformation epithelial cancer cells can acquire mesenchymal features via a process called epithelial‐to‐mesenchymal transition (EMT). This process ...endows cancer cells with increased invasive and migratory capacity, enabling tumour dissemination and metastasis. EMT is associated with a complex metabolic reprogramming, orchestrated by EMT transcription factors, which support the energy requirements of increased motility and growth in harsh environmental conditions. The discovery that mutations in metabolic genes such as FH, SDH and IDH activate EMT provided further evidence that EMT and metabolism are intertwined. In this review, we discuss the role of EMT in cancer and the underpinning metabolic reprogramming. We also put forward the hypothesis that, by altering chromatin structure and function, metabolic pathways engaged by EMT are necessary for its full activation.
During transformation, epithelial cells undergo a complex phenotypic reprogramming called epithelial‐to‐mesenchymal transition (EMT), whereby they become more motile and invasive. During EMT, cancer cells also profoundly reprogramme their metabolism. In this review, we describe the molecular underpinnings of the metabolic rewiring during EMT and how, in turn, metabolic alterations can trigger EMT.
The YAP and TAZ paralogs are transcriptional co-activators recruited to target sites by TEAD proteins. Here, we show that YAP and TAZ are also recruited by JUNB (a member of the AP-1 family) and ...STAT3, key transcription factors that mediate an epigenetic switch linking inflammation to cellular transformation. YAP and TAZ directly interact with JUNB and STAT3 via a WW domain important for transformation, and they stimulate transcriptional activation by AP-1 proteins. JUNB, STAT3, and TEAD co-localize at virtually all YAP/TAZ target sites, yet many target sites only contain individual AP-1, TEAD, or STAT3 motifs. This observation and differences in relative crosslinking efficiencies of JUNB, TEAD, and STAT3 at YAP/TAZ target sites suggest that YAP/TAZ is recruited by different forms of an AP-1/STAT3/TEAD complex depending on the recruiting motif. The different classes of YAP/TAZ target sites are associated with largely non-overlapping genes with distinct functions. A small minority of target sites are YAP- or TAZ-specific, and they are associated with different sequence motifs and gene classes from shared YAP/TAZ target sites. Genes containing either the AP-1 or TEAD class of YAP/TAZ sites are associated with poor survival of breast cancer patients with the triple-negative form of the disease.
Quantitative traits analyzed in Genome‐Wide Association Studies (GWAS) are often nonnormally distributed. For such traits, association tests based on standard linear regression are subject to reduced ...power and inflated type I error in finite samples. Applying the rank‐based inverse normal transformation (INT) to nonnormally distributed traits has become common practice in GWAS. However, the different variations on INT‐based association testing have not been formally defined, and guidance is lacking on when to use which approach. In this paper, we formally define and systematically compare the direct (D‐INT) and indirect (I‐INT) INT‐based association tests. We discuss their assumptions, underlying generative models, and connections. We demonstrate that the relative powers of D‐INT and I‐INT depend on the underlying data generating process. Since neither approach is uniformly most powerful, we combine them into an adaptive omnibus test (O‐INT). O‐INT is robust to model misspecification, protects the type I error, and is well powered against a wide range of nonnormally distributed traits. Extensive simulations were conducted to examine the finite sample operating characteristics of these tests. Our results demonstrate that, for nonnormally distributed traits, INT‐based tests outperform the standard untransformed association test, both in terms of power and type I error rate control. We apply the proposed methods to GWAS of spirometry traits in the UK Biobank. O‐INT has been implemented in the R package RNOmni, which is available on CRAN.
Computational materials design has made significant progress lately. However, one underexploited opportunity lies in the combination of physically based modelling and machine learning (ML). In the ...present work we exploit this combination for modelling of strain-induced martensitic phase transformation (SIMT) in austenitic steels. A fully predictive model for SIMT, responsible for the TRIP effect in many steels, is devised. An experimental dataset correlating SIMT with composition, temperature and strain is collected from the open literature firstly. Secondly, the Olson-Cohen model is applied to make physically based predictions on temperature and strain dependence of SIMT in order to expand the database to the final size of 16,500 entries relating the features and the target. Thirdly, ensemble ML methods are applied to model the data and the final model is validated on a holdout dataset, including also dual-phase alloys. The final model provides accurate predictions of SIMT in a temperature range from −196 to 100 °C and from 0 to 1 in strain. The model can readily be extended to consider further factors such as strain rate and stress state. Moreover, it can be used together with thermodynamic and kinetic calculations, or thermomechanical simulations, for the design of steels and components, respectively.
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•An integrated machine learning and physical modelling to predict strain-induced martensite in austenitic steels.•A fully predictive model of SIM features, responsible for the TRIP effect in many steels, is devised.•The model provides accurate predictions in comprehensive temperature and strain range in austenitic and dual phase steels.•The model can readily be extended to consider further factors such as strain rate and stress state.
Species evolve by mutations and epigenetic changes acting on individuals in a population; tumors evolve by similar mechanisms at a cellular level in a tissue. This article reviews growing evidence ...about tumor dormancy and suggests that (i) cellular malignancy is a natural byproduct of evolutionary mechanisms, such as gene mutations and epigenetic modifications, which is manifested in the form of tumor dormancy in healthy individuals as well as in cancer survivors; (ii) cancer metastasis could be an early dissemination event that could occur during malignant dormancy even before primary cancer is clinically detectable; and (iii) chronic inflammation is a key factor in awakening dormant malignant cells at the primary site, leading to primary cancer development, and at distant sites, leading to advanced stage diseases. On the basis of this evidence, it is reasonable to propose that we are all cancer survivors rather than cancer-free individuals because of harboring dormant malignant cells in our organs. A better understanding of local and metastatic tumor dormancy could lead to novel cancer therapeutics for the prevention of cancer.
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This research investigates how entrepreneurs of small and medium enterprises (SMEs) with inadequate capabilities and limited resources drove digital transformation in their companies, a phenomenon ...that remains under‐researched in the extant literature. We conduct qualitative research on digital transformation to cross‐border e‐commerce undergone by 7 SMEs on the Alibaba digital platform. We inductively derive a process model that aims to describe and explain how SME entrepreneurs, with support from the digital platform service provider, drive digital transformation through managerial cognition renewal, managerial social capital development, business team building, and organizational capability building. This model expands our understanding of both digital entrepreneurship and digital transformation. It also presents new insights into how digital platform service providers can help SMEs transform and compete.
Hepatocellular carcinoma (HCC) formation is a multi‐step pathological process that involves evolution of a heterogeneous immunosuppressive tumor microenvironment. However, the specific cell ...populations involved and their origins and contribution to HCC development remain largely unknown. Here, comprehensive single‐cell transcriptome sequencing was applied to profile rat models of toxin‐induced liver tumorigenesis and HCC patients. Specifically, we identified three populations of hepatic parenchymal cells emerging during HCC progression, termed metabolic hepatocytes (HCMeta), Epcam+ population with differentiation potential (EP+Diff) and immunosuppressive malignant transformation subset (MTImmu). These distinct subpopulations form an oncogenic trajectory depicting a dynamic landscape of hepatocarcinogenesis, with signature genes reflecting the transition from EP+Diff to MTImmu. Importantly, GPNMB+Gal‐3+ MTImmu cells exhibit both malignant and immunosuppressive properties. Moreover, SOX18 is required for the generation and malignant transformation of GPNMB+Gal‐3+ MTImmu cells. Enrichment of the GPNMB+Gal‐3+ MTImmu subset was found to be associated with poor prognosis and a higher rate of recurrence in patients. Collectively, we unraveled the single‐cell HCC progression atlas and uncovered GPNMB+Gal‐3+ parenchymal cells as a major subset contributing to the immunosuppressive microenvironment thus malignance in HCC.
Synopsis
Malignant transformation is the major driver of liver cancer, but the molecular and cellular bases for its induction remain poorly understood. Here, in‐depth profiling of hepatocellular carcinoma (HCC) initiation and progression defines new molecular markers involved and emerging malignant cell populations counteracting immune surveillance.
Longitudinal single‐cell RNA‐sequencing of toxin‐induced liver tumorigenesis in rats reveals a dynamic composition and transformation of hepatic parenchymal cells.
Complementary analyses of four HCC patients show conservation of HCC cell dynamics.
GPNMB+Gal‐3+ parenchymal cells arise from EPCAM+ cells during HCC progression and exhibit immunosuppressive and malignant properties in vivo.
The transcription factor SOX18 is required for the GPNMB+Gal‐3+ cell stemness and immunosuppressive capacity.
Enrichment of GPNMB+Gal‐3+ cells is associated with poor prognosis in HCC patients.
Longitudinal single‐cell profiling of liver cancer in rats and patients unveils an emerging aggressive parenchymal cell population counteracting immune surveillance.
Cellular senescence is a process that results in irreversible cell-cycle arrest, and is thought to be an autonomous tumor-suppressor mechanism. During senescence, cells develop distinctive metabolic ...and signaling features, together referred to as the senescence-associated secretory phenotype (SASP). The SASP is implicated in several aging-related pathologies, including various malignancies. Accumulating evidence argues that cellular senescence acts as a double-edged sword in human cancer, and new agents and innovative strategies to tackle senescent cells are in development pipelines to counter the adverse effects of cellular senescence in the clinic. We focus on recent discoveries in senescence research and SASP biology, and highlight the potential of SASP suppression and senescent cell clearance in advancing precision medicine.
Cellular senescence is a highly conserved stress response that restrains the proliferation of cells at risk of oncogenic transformation.
Senescent cells spatially occupy tissue environmental niches and elaborate numerous extracellular factors encoded by the SASP, contributing to aging-related disorders, notably cancer.
In the tumor microenvironment, senescent cells can drive events that support malignant progression, including but not limited to therapeutic resistance, disease relapse, and distant metastasis.
In cancer clinics, the abundance of senescent cells can serve as a ‘molecular’ marker that predicts adverse outcomes, while senescent cell clearance significantly mitigates pathological exacerbation.
A new class of agents, termed senolytics, has been shown to be effective in extending healthspan, reducing frailty and improving stem cell function in animal models of aging.
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