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Mix & Match: Phenotypic coexistence as a key facilitator of solid tumour invasion

Invasion of healthy tissue is a defining feature of malignant tumours. Traditionally, invasion is thought to be driven by cells that have acquired all the necessary traits to overcome the range of biological and physical defences employed by the body. However, in light of the ever-increasing evidence for geno- and phenotypic intra-tumour heterogeneity an alternative hypothesis presents itself: Could invasion be driven by a collection of cells with distinct traits that together facilitate the invasion process? In this paper, we use a mathematical model to assess the feasibility of this hypothesis in the context of acid-mediated invasion. We assume tumour expansion is obstructed by stroma which inhibits growth, and extra-cellular matrix (ECM) which blocks cancer cell movement. Further, we assume that there are two types of cancer cells: i) a glycolytic phenotype which produces acid that kills stromal cells, and ii) a matrix-degrading phenotype that locally remodels the ECM. We extend the Gatenby-Gawlinski reaction-diffusion model to derive a system of five coupled reaction-diffusion equations to describe the resulting invasion process. We characterise the spatially homogeneous steady states and carry out a simulation study in one spatial dimension to determine how the tumour develops as we vary the strength of competition between the two phenotypes. We find that overall tumour growth is most extensive when both cell types can stably coexist, since this allows the cells to locally mix and benefit most from the combination of traits. In contrast, when inter-species competition exceeds intra-species competition the populations spatially separate and invasion arrests either: i) rapidly (matrix-degraders dominate), or ii) slowly (acid-producers dominate). Overall, our work demonstrates that the spatial and ecological relationship between a heterogeneous population of tumour cells is a key factor in determining their ability to cooperate. Specifically, we predict that tumours in which different phenotypes coexist stably are more invasive than tumours in which phenotypes are spatially separated.

cancer biology↗

Aberrant claudin-6-adhesion signal promotes endometrial cancer progression via estrogen receptor α

Cell adhesion proteins not only maintain tissue integrity but also possess signaling abilities to organize diverse cellular events in physiological and pathological processes; however, the underlying mechanism remains obscure. Among cell adhesion molecules, the claudin (CLDN) family often possesses aberrant expression in various cancers, but the biological relevance and molecular basis have not yet been established. Here, we show that high CLDN6 expression promotes endometrial cancer progression and represents the poor prognostic marker. The second extracellular domain and Y196/200 of CLDN6 were required to recruit and activate Src-family kinases (SFKs) and to stimulate malignant phenotypes. Importantly, we demonstrate that the CLDN6/SFK/PI3K-dependent AKT and SGK (serum- and glucocorticoid-regulated kinase) signalings target Ser518 in the human estrogen receptor and ligand-independently activate target genes in endometrial cancer cells, resulting in cancer development. The identification of this machinery highlights regulation of the transcription factors by cell adhesion to advance tumor progression.

cancer biology↗

A genome-wide screen in mice to identify cell-extrinsic regulators of pulmonary metastatic colonisation

Metastatic colonisation, whereby a disseminated tumour cell is able to survive and proliferate at a secondary site, involves both tumour cell-intrinsic and -extrinsic factors. To identify tumour cell-extrinsic (microenvironmental) factors that regulate the ability of metastatic tumour cells to effectively colonise a tissue, we performed a genome-wide screen utilising the experimental metastasis assay on mutant mice. Mutant and wildtype (control) mice were tail vein-dosed with murine metastatic melanoma B16-F10 cells and 10 days later the number of pulmonary metastatic colonies were counted. Of the 1,300 genes/genetic locations (1,344 alleles) assessed in the screen 34 genes were determined to significantly regulate pulmonary metastatic colonisation (15 increased and 19 decreased; P<0.005 and genotype effect <-60 or >+60). Whilst several of these genes have known roles in immune system regulation (Bach2, Cyba, Cybb, Cybc1, Id2, Igh-6, Irf1, Irf7, Ncf1, Ncf2, Ncf4 and Pik3cg) most are involved in a disparate range of biological processes, ranging from ubiquitination (Herc1) to diphthamide synthesis (Dph6) to Rho GTPase-activation (Arhgap30 and Fgd4), with no previous reports of a role in the regulation of metastasis. Thus, we have identified numerous novel regulators of pulmonary metastatic colonisation, which may represent potential therapeutic targets.

cancer biology↗

Defining the cell surface proteomic landscape of multiple myeloma reveals immunotherapeutic strategies and biomarkers of drug resistance

The myeloma cell surface proteome ("surfaceome") not only determines tumor interaction with the microenvironment but serves as an emerging arena for therapeutic development. Here, we use glycoprotein capture proteomics to first define surface markers most-enriched on myeloma when compared to B-cell malignancy models, revealing unexpected biological signatures unique to malignant plasma cells. We next integrate our proteomic dataset with existing transcriptome databases, nominating CCR10 and TXNDC11 as possible monotherapeutic targets and CD48 as a promising co-target for increasing avidity of BCMA-directed cellular therapies. We further identify potential biomarkers of resistance to both proteasome inhibitors and lenalidomide including changes in CD53, EVI2B, CD10, and CD33. Comparison of short-term treatment with chronic resistance delineates large differences in surface proteome profile under each type of drug exposure. Finally, we develop a miniaturized version of the surface proteomics protocol and present the first surface proteomic profile of a primary myeloma patient plasma cell sample. Our dataset provides a unique resource to advance the biological, therapeutic, and diagnostic understanding of myeloma.

cancer biology↗

A multi-step immune-competent genetic mouse model reveals phenotypic plasticity in uveal melanoma

Uveal melanoma (UM) is a highly aggressive intraocular malignancy with limited therapeutic options for metastatic disease. Existing transgenic UM mouse models inadequately recapitulate human disease progression, while transplant models lack immune competence for studying the tumor immune microenvironment and therapeutic interventions. To address these limitations, we developed a genetically engineered mouse model incorporating stepwise genetic alterations implicated in human UM progression. Spatiotemporally controlled expression of mutant GNAQQ209L from the endogenous locus induced choroidal nevi with limited penetrance. Concomitant BAP1 deletion enhanced nevus formation, while further MYC activation led to fully penetrant intraocular tumors with metastatic potential. Single-cell RNA sequencing revealed malignant cells segregated into Melanocytic and Neural Crest-like subpopulations characterized by distinct transcriptional and biosynthetic programs. Trajectory analyses inferred dedifferentiation from the Melanocytic toward the Neural Crest-like state during tumor progression. Comparison to human UM revealed commonalities with highly aggressive Class 2 UM, including gene expression signatures and copy number gains affecting genes that map to human chromosome 8q beyond the activated MYC allele, suggesting cooperative effects of multiple drivers in this chromosomal region. The tumor microenvironment featured immunosuppressive macrophage populations and exhausted T cells, closely resembling human UM. This physiologically relevant, immune-competent model provides a platform for investigating UM biology, functionally characterizing candidate driver genes, and developing immune-based therapeutic strategies. SIGNIFICANCE STATEMENTWe developed a mouse model that resembles the genetic progression and phenotypic plasticity of human UM. This spatially controlled model confirms the critical role of driver mutations in GNAQ and BAP1, proposes MYC as a promoter of malignant transformation in coordination with other chromosome 8q genes, and reveals UM progression through distinct cellular states. This model offers an urgently needed preclinical platform for understanding the immunogenomics of UM and for testing immune and targeted treatments for this lethal cancer.

cancer biology↗

IMiDs induce FAM83F degradation via an interaction with CK1α to attenuate Wnt signalling

Immunomodulatory imide drugs (IMiDs) bind CRBN, a substrate receptor of the Cul4A E3 ligase complex, enabling neo-substrate recruitment and degradation via the ubiquitin-proteasome system. Here, we report FAM83F as such a neo-substrate. We recently showed that the eight FAM83 proteins (A-H) interact with members of the serine/threonine protein kinase CK1 family, to regulate their subcellular distribution and distinct biological roles. CK1 is a well-established IMiD neo-substrate and we demonstrate here that IMiD-induced FAM83F degradation requires its association with CK1. Despite all FAM83 proteins interacting with CK1, no other FAM83 protein is degraded by IMiDs. FAM83F is localised to the plasma membrane, and consistent with this, IMiD treatment results in depletion of both FAM83F and CK1 levels from the plasma membrane. We have recently identified FAM83F as a mediator of the canonical Wnt signalling pathway. The IMiD-induced degradation of FAM83F attenuated Wnt signalling in colorectal cancer cells and removed CK1 from the plasma membrane, mirroring the phenotypes observed with genetic ablation of FAM83F. Intriguingly, in many cancer cell lines, IMiD-induced degradation of CK1 is only modest and incomplete. In line with this observation, the expression of FAM83G, which also binds to CK1, appears to attenuate the IMiD-induced degradation of CK1, suggesting a protective role for FAM83G on CK1. Our findings reveal that the efficiency of target protein degradation by IMiDs, and perhaps other degraders such as PROTACs, relies on the nature of the inherent multiprotein complex in which the target protein exists. Our findings unearth opportunities for developing degraders to target specific protein complexes.

cancer biology↗

Method to identify physical, chemical and biological factors that trigger Bcl-xL-mediated apoptosis

The evidence that pan-Bcl-2 or Bcl-xL-specific inhibitors prematurely kill virus-infected or RNA/DNA-transfected cells provides rationale for investigating these apoptotic inducers further. Here, we show that Bcl-xL-specific agent A-1155463 prematurely kills cells of different origins and the small roundworms (C. elegans), when combined with DNA-damaging agent 4-nitroquinoline-1-oxide (4NQO). The synergistic effect of 4NQO-A-1155463 combination was p53-dependent, was associated with the release of Bad and Bax from Bcl-xL, which triggered mitochondrial outer membrane permeabilization (MOMP). Combinations of Bcl-xL-specific inhibitors with certain anticancer compounds or physical insults also killed cells. Collectively, our results suggest that biological, chemical and physical factors trigger evolutionary conserved Bcl-xL-mediated apoptotic pathway.

cancer biology↗

Telomerase reverse transcriptase induces targetable alterations in glutathione and nucleotide biosynthesis in glioblastomas

Telomerase reverse transcriptase (TERT) is essential for glioblastoma (GBM) proliferation. Delineating metabolic vulnerabilities induced by TERT can lead to novel GBM therapies. We previously showed that TERT upregulates glutathione (GSH) pool size in GBMs. Here, we show that TERT acts via the FOXO1 transcription factor to upregulate expression of the catalytic subunit of glutamate-cysteine ligase (GCLC), the rate-limiting enzyme of de novo GSH synthesis. Inhibiting GCLC using siRNA or buthionine sulfoximine (BSO) reduces synthesis of 13C-GSH from [U-13C]-glutamine and inhibits clonogenicity. However, GCLC inhibition does not induce cell death, an effect that is associated with elevated [U-13C]-glutamine metabolism to glutamate and pyrimidine nucleotide biosynthesis. Mechanistically, GCLC inhibition activates MYC and leads to compensatory upregulation of two key glutamine-utilizing enzymes i.e., glutaminase (GLS), which generates glutamate from glutamine, and CAD (carbamoyl-phosphate synthetase 2, aspartate transcarbamoylase, dihydroorotatase), the enzyme that converts glutamine to the pyrimidine nucleotide precursor dihydroorotate. We then examined the therapeutic potential of inhibiting GLS and CAD in combination with GCLC. 6-diazo-5-oxy-L-norleucin (DON) is a potent inhibitor of glutamine-utilizing enzymes including GLS and CAD. The combination of BSO and DON suppresses GSH and pyrimidine nucleotide biosynthesis and is synergistically lethal in GBM cells. Importantly, in vivo stable isotope tracing indicates that combined treatment with JHU-083 (a brain-penetrant prodrug of DON) and BSO abrogates synthesis of GSH and pyrimidine nucleotides from [U-13C]-glutamine and induces tumor shrinkage in mice bearing intracranial GBM xenografts. Collectively, our studies exploit a mechanistic understanding of TERT biology to identify synthetically lethal metabolic vulnerabilities in GBMs. SIGNIFICANCEUsing in vivo stable isotope tracing, metabolomics, and loss-of-function studies, we demonstrate that TERT expression is associated with metabolic alterations that can be synergistically targeted for therapy in glioblastomas.

cancer biology↗

Differential Proteomic Analysis of AML Patients at Low and Intermediate Altitudes after Chemotherapy

Chemotherapy is the primary treatment for patients with acute myeloid leukemia (AML). In addition to factors such as patient age, physical condition, and choice of medication, we have noticed that environmental factors such as altitude may also have a significant impact on post-chemotherapy bone marrow suppression in AML patients in clinical practice. The results indicate that there are differences in the proteomics of the two groups of patients during the bone marrow suppression period after chemotherapy. Differentially expressed proteins are primarily located in the cytoplasm, extracellular space, and nucleus, followed by mitochondria and membranes. These differentially expressed proteins mainly participate in biological processes such as cell and metabolism. For differential protein KEGG pathway enrichment analysis, it was found that metabolic pathways were mainly enriched in the metabolic category, while the PI3K-Akt signaling pathway, HIF-1 signaling pathway, NF-{kappa}B signaling pathway, and calcium signaling pathway were enriched in the signaling pathways.

cancer biology↗

Defining the RNA Modification Landscape of Multiple Myeloma Reveals METTL3-Dependent m6A Regulation of NEAT1

RNA modifications play critical roles in gene regulation. N6-methyladenosine (m6A) is the most abundant modification on mRNA and long noncoding RNA (lncRNA) and regulates RNA processing, stability, and translation. RNA modifications are not well characterized in multiple myeloma (MM), a plasma cell malignancy characterized by relapse and disease progression, and the contribution of m6A-modified lncRNAs to the disease remains unclear. Here, we define the RNA modification landscape of MM by combining mass spectrometry, Nanopore Direct RNA sequencing, and methylated RNA immunoprecipitation sequencing. We identify 20 RNA modification types and > 15,000 m6A sites, including sites on 2,398 lncRNAs. Among these, we validate m6A sites on the paraspeckle-associated lncRNA NEAT1. Functional studies reveal that NEAT1 expression is regulated by the methyltransferase METTL3 and site-specific demethylation of a NEAT1 m6A site reduces MM cell viability. Single-cell RNA sequencing shows consistent NEAT1 enrichment in malignant plasma cells but minimal expression in healthy cells. These findings identify m6A-modified lncRNAs as key regulators of MM biology and establish NEAT1 as an epitranscriptomically controlled driver of MM cell survival.

cancer biology↗

Comprehensive Multi-Omic Analysis Reveals Distinct Molecular Features in Early and Advanced Stages of Hepatocellular Carcinoma

Hepatocellular Carcinoma (HCC) is a serious primary solid tumor that is prevalent worldwide. Due to its high mortality rate, it is crucial to explore both early diagnosis and advanced treatment for HCC. In recent years, multi-omic approaches have emerged as promising tools to identify biomarkers and investigate molecular mechanisms of biological processes and diseases. In this study, we performed proteomics, phosphoproteomics, metabolomics, and lipidomics to reveal the molecular features of early- and advanced-stage HCC. The data obtained from these omics were analyzed separately and then integrated to provide a comprehensive understanding of the disease. The multi-omic results unveiled intricate biological pathways and interaction networks underlying the initiation and progression of HCC. Moreover, we proposed specific potential biomarker panels for both early- and advanced-stage HCC by overlapping our data with CPTAC database, and deduced novel insights and mechanisms related to HCC origination and development.

cancer biology↗

Comprehensive single cell transcriptomics analysis of murine osteosarcoma uncovers Skp2 function in metastasis, genomic instability and immune activation and reveals additional target pathways

Osteosarcoma (OS) is the most common primary pediatric bone malignancy. One promising new therapeutic target is SKP2, encoding a substrate recognition factor of the SCF E3 ubiquitin ligase responsible for ubiquitination and proteasome degradation of substrate p27, thus driving cellular proliferation. We have shown previously that knockout of Skp2 in an immunocompetent transgenic mouse model of OS improved survival, drove apoptosis, and induced tumor inflammation. Here, we applied single-cell RNA-sequencing (scRNA-seq) to study primary OS tumors derived from Osx-Cre driven conditional knockout of Rb1 and Trp53. We showed that murine OS models recapitulate the tumor heterogeneity and microenvironment complexity observed in patient tumors. We further compared this model with OS models with functional disruption of Skp2: one with Skp2 knockout and the other with the Skp2-p27 interaction disrupted (resulting in p27 overexpression). We found reduction of T cell exhaustion and upregulation of interferon activation, along with evidence of replicative and endoplasmic reticulum-related stress in the Skp2 disruption models, and showed that interferon induction was correlated with improved survival in OS patients. Additionally, our scRNA-seq analysis uncovered decreased activities of metastasis-related gene signatures in the Skp2-disrupted OS, which we validated by observation of a strong reduction in lung metastasis in the Skp2 knockout mice. Finally, we report several potential mechanisms of escape from targeting Skp2 in OS, including upregulation of Myc targets, DNA copy number amplification and overexpression of alternative E3 ligase genes, and potential alternative lineage activation. These mechanistic insights into OS tumor biology and Skp2 function suggest novel targets for new, synergistic therapies, while the data and our comprehensive analysis may serve as a public resource for further big data-driven OS research.

cancer biology↗

A new genetic method to predict the prognostic outcome of melanoma

Cutaneous melanoma is quite often encountered in dermato-oncology. This paper describes a new genetic method to predict the prognostic outcome of melanoma. Data were collected from the TCGA databases. According to tumor progression status, the data were divided into two groups to evaluate the significant biological processes and key genes influencing the outcome of melanoma using a bioinformatics method. By adopting a statistical regression analysis method, a novel score based on the contributing genes was developed. Cox regression analysis was used to validate the effectiveness of the genetic risk score in predicting the outcome. Seven biological processes associated with melanocytes were identified. A protein-protein interactions network showed that 27 functional genes were associated with the outcome of melanoma. Among these, three genes (COL17A1, ITGA6, and SPRR2F) were used to calculate the genetic risk score, which was regarded as an independent and effective risk factor for disease progression or overall survival in melanoma.

cancer biology↗

Proton FLASH preserves neurocognition across delivery techniques: implications for clinical translation in pediatric brain tumors

BackgroundRadiation therapy is integral to the curative treatment of childhood brain tumors but contributes to late neurocognitive impairment in survivors. FLASH (ultra-high dose rate, >40Gy/s) reduces normal-tissue toxicity in preclinical models, and proton-FLASH is currently the only modality capable of delivering ultra-high dose rates to the deep targets, such as pediatric brain tumors. However, two questions remain unresolved before clinical translation: (1) whether the FLASH effect can be achieved on synchrotron-based proton systems, which deliver protons in discrete spills that may be insufficient to cover a clinical target within a single delivery, and (2) which dose-rate metric, among the multiple definitions currently used in the field, best predicts the biological FLASH effect. MethodsC57BL/6 mice (7-8 weeks) received 10 Gy whole-brain RT via a clinical Hitachi ProBEAT synchrotron with CBCT-guided delivery, using three transmission-beam techniques: single-spill pencil beam scanning (SS PBS), multi-spill PBS with [~]2-second inter-spot delay (MS PBS), and passive scatter (PS), compared to conventional (CONV) delivery and unirradiated controls (n=24-28/group, equal sex distribution). Dose rate was quantified using three frameworks: field dose rate (FDR), PBS dose rate (PBSDR), and dose-averaged dose rate (DADR). Recognition memory was assessed by novel object recognition (NOR) at 6 weeks post-RT, and cognitive flexibility was assessed via touchscreen visual discrimination and reversal learning at 14 weeks. Hippocampal neuroinflammation was evaluated by immunofluorescence and immunohistochemistry for Iba1, NeuN, and GFAP. ResultsFLASH conditions were met by SS PBS and PS under all three dose-rate definitions, but MS PBS qualified as FLASH only by DADR. Despite this, neuroprotection was preserved across all three FLASH techniques: discrimination index was significantly higher for SS PBS (P=0.021), MS PBS (P=0.008), and PS (P<0.001) versus CONV, with no significant difference between FLASH techniques. On touchscreen testing, FLASH-treated females demonstrated preserved cognitive flexibility (P=0.047 vs. CONV on reversal learning correct trials). Iba1+ microglia were reduced in FLASH compared to CONV mice, with morphology suggestive of preserved homeostatic state. ConclusionsSynchrotron-based proton FLASH preserves neurocognitive function across all delivery techniques, including under multi-spill delivery essential for treating clinical-scale pediatric brain tumors. Critically, this neuroprotection was observed even for deliveries that qualified as FLASH only by DADR, identifying DADR as the dose-rate metric most relevant to the biological FLASH effect with direct implications for clinical trial design and dose-rate reporting standards.

cancer biology↗

Integrative multi-omics analysis reveals molecular subtypes and tumor evolution of synovial sarcoma

Synovial sarcomas (SS) are malignant mesenchymal tumors characterized by the SS18-SSX fusion gene, which drives tumorigenesis by altering the composition of the BAF complex. Secondary genomic alterations that determine variations in tumor phenotype or clinical presentation are largely unknown. Herein, we present transcriptome, targeted DNA-sequencing, and proteomics analysis of 91 synovial sarcomas from 55 patients. We identified three SS clusters (SSCs) characterized by distinct histology, tumor microenvironments, genomic complexities, therapeutic effects, and clinical outcomes. Eight BAF complex components are differentially expressed among SSCs, and their role in mesenchymal-epithelial-transition is supported by single cell sequencing. The epithelial cells of biphasic tumors are more susceptible to developing copy number alterations, including amplification of PDCD1 and TMPRSS2. Our findings explain broad concepts in SS biology and imply that the BAF composition at the start of the tumorigenesis (i.e. the cellular linage) may determine the SS subtype, providing a rationale for individualized treatment strategies.

cancer biology↗

Essential gene networks in acute myeloid leukemia identified using a microRNA-knockout CRISPR library screen

MicroRNAs (miRNA) are small RNAs that function as key modulators of gene expression. Due to their promiscuity of binding, a single miRNA may regulate several genes and hence, multiple pathways simultaneously. In addition, the 3-UTR of mRNA can be recognized by several miRNA for suppression or degradation. We built a microRNA-only Knock-out (miRKo) CRISPR/Cas-9 library to identify essential miRNA in Acute Myeloid Leukemia (AML) using OCI-AML2, OCI-AML3 and U937 cell lines as in vitro models. 10 miRNA were identified to be essential in our screen among all three cell lines: miR-19b-1, -19b-2, 29b-2, -302a, -3678, -3713, -3910-1, -4447, -4718 and -6795. By using weighted degrees of association, we identified pathway hubs that uniquely affect all 3 cell lines by integrating miRNA:mRNA networks using mirDIP and pathway analysis using pathDIP. Through the miRKo screen, network membership analyses and biological anticorrelation scoring through patient data analysis, we identified RRP2CA, RPS6KB-1, CREB1, RPM1A, MAPK10, MAP3K2, ITCH, FBX-W7, NR3C1 and XIAP as likely targets of the essential miRNA in AML; and signal transduction, apoptosis, TGF-beta signalling and MAPK signalling as candidate essential pathways in AML.

cancer biology↗

A Measurable Systemic Immune Phenotype Links Circulating Myeloid Dysfunction to Tumour Spatial Organization in Gastroesophageal Adenocarcinoma

Background: Both static and longitudinal measures of circulating neutrophil-to-lymphocyte ratio (cNLR) are prognostic markers across solid malignancies, including gastroesophageal adenocarcinoma (GEA). Despite this consistency, cNLR remains poorly integrated into clinical decision-making and is generally regarded as a nonspecific inflammatory or disease-burden signal rather than a defined biological state. Analysis of a large, prospectively assembled GEA cohort showed that cNLR was only weakly associated with tumour burden or pathological response, yet both baseline and postoperative cNLR independently predicted outcome. Methods: These observations prompted a retrospective biological investigation of what host biology cNLR captures. Using available clinically linked biospecimens, we performed multiscale analyses across complementary patient subsets encompassing peripheral-blood immune function and soluble signalling, tumour single-cell transcriptional programmes, and spatial myeloid organization within tissue. Results: High baseline cNLR was associated with reduced circulating cytotoxic and immune-trafficking mediators, elevated angiogenesis-associated factors, neutrophil-mediated suppression of lymphocyte proliferation, impaired tumour-cell killing, and enhanced spontaneous neutrophil extracellular trap formation. Single-cell profiling identified coordinated transcriptional differences across tumour compartments, including innate, cytokine and myeloid programmes. Spatial profiling showed that myeloid abundance and organization varied across anatomical compartments; greater tumour-periphery PDL1 positive myeloid clustering was associated with inferior recurrence-free survival. Baseline cNLR showed little relationship with static myeloid abundance, whereas pretreatment cNLR dynamics were associated with altered cross-compartment spatial relationships between CD8 positive cells and myeloid cells. Notably, higher early postoperative cNLR was associated with greater PDL1 positive myeloid clustering at the tumour periphery, linking the spatial architecture of the resected tumour with a systemic myeloid phenotype persisting after surgery. Conclusions: The data identify a prognostic, multilevel myeloid-associated host phenotype in GEA that is incompletely explained by tumour burden. Integrating systemic immune function, tumour single cell transcriptomics and spatial myeloid organization demonstrates that these biological domains provide distinct, yet convergent views of the host immune phenotype captured by cNLR. These findings establish a biological framework for the clinical utility of cNLR and highlight myeloid-associated immune processes as promising targets for therapeutic intervention.

cancer biology↗

Pathway-guided deep neural network toward interpretable and predictive modeling of drug sensitivity

MotivationTo efficiently save cost and reduce risk in drug research and development, there is a pressing demand to develop in-silico methods to predict drug sensitivity to cancer cells. With the exponentially increasing number of multi-omics data derived from high-throughput techniques, machine learning-based methods have been applied to the prediction of drug sensitivities. However, these methods have drawbacks either in the interpretability of mechanism of drug action or limited performance in modeling drug sensitivity. ResultsIn this paper, we presented a pathway-guided deep neural network model, referred to as pathDNN, to predict the drug sensitivity to cancer cells. Biological pathways describe a group of molecules in a cell that collaborates to control various biological functions like cell proliferation and death, thereby abnormal function of pathways can result in disease. To make advantage of both the excellent predictive ability of deep neural network and the biological knowledge of pathways, we reshape the canonical DNN structure by incorporating a layer of pathway nodes and their connections to input gene nodes, which makes the DNN model more interpretable and predictive compared to canonical DNN. We have conducted extensive performance evaluations on multiple independent drug sensitivity data sets, and demonstrate that pathDNN significantly outperformed canonical DNN model and seven other classical regression models. Most importantly, we observed remarkable activity decreases of disease-related pathway nodes during forward propagation upon inputs of drug targets, which implicitly corresponds to the inhibition effect of disease-related pathways induced by drug treatment on cancer cells. Our empirical experiments show that pathDNN achieves pharmacological interpretability and predictive ability in modeling drug sensitivity to cancer cells. AvailabilityThe web server, as well as the processed data sets and source codes for reproducing our work, is available at http://pathdnn.denglab.org

bioinformatics↗