Prominent features of the amino acid mutation landscape in cancer

Arginines of the CGN codon family are Achilles' heels of cancer genes

Recent studies have revealed that arginine is the most favorable target of amino acid alteration in most cancer types and it has been suggested that the high preference for arginine mutations reflects the critical roles of this amino acid in the function of proteins. High rates of mutations of arginine residues in cancer, however, might also be due to increased mutability of arginine codons of the CGN family as the CpG dinucleotides of these codons may be methylated. In the present work we have analyzed spectra of single base substitutions of cancer genes (oncogenes, tumor suppressor genes) and passenger genes in cancer tissues to assess the contributions of CpG hypermutability and selection to arginine mutations. Our studies have shown that arginines encoded by the CGN codon family display higher rates of mutation in both cancer genes and passenger genes than arginine codons AGA and AGG that are devoid of CpG dinucleotide, suggesting that the predominance of arginine mutations in cancer is primarily due to CpG hypermutability, rather than selection for arginine replacement. Nevertheless, our results also suggest that CGN codons for arginines may serve as Achilles' heels of cancer genes. CpG hypermutability of key arginines of proto-oncogenes, leading to high rates of recurrence of driver mutations, contributes significantly to carcinogenesis. Similarly, our results indicate that hypermutability of the CpG dinucleotide of CGA codons (converting them to TGA stop codons) contributes significantly to recurrent truncation and inactivation of tumor suppressor genes.

Evolution of pH-sensitive transcription termination during adaptation to repeated long-term starvation

Fluctuating environments that consist of regular cycles of co-occurring stress are a common challenge faced by cellular populations. For a population to thrive in constantly changing conditions, an ability to coordinate a rapid cellular response is essential. Here, we identify a mutation conferring an arginine-to-histidine (Arg to His) substitution in the transcription terminator Rho. The rho R109H mutation frequently arose in E. coli populations experimentally evolved under repeated long-term starvation conditions, during which feast and famine result in drastic environmental pH fluctuations. Metagenomic sequencing revealed that populations containing the rho mutation also possess putative loss-of-function mutations in ydcI, which encodes a recently characterized transcription factor associated with pH homeostasis. Genetic reconstructions of these mutations show that the rho allele confers a plastic alkaline-induced reduction of Rho function that, when found in tandem with a ΔydcI allele, leads to intracellular alkalinization and genetic assimilation of Rho mutant function. We further identify Arg to His substitutions at analogous sites in rho alleles from species originating from fluctuating alkaline environments. Our results suggest that Arg to His substitutions in global regulators of gene expression can serve to rapidly coordinate complex responses through pH sensing and shed light on how cellular populations across the tree of life use environmental cues to coordinate rapid responses to complex, fluctuating environments.

Computational approaches for identifying disease-causing mutations in proteins

Advancements in genome sequencing have expanded the scope of investigating mutations in proteins across different diseases. Amino acid mutations in a protein alter its structure, stability and function and some of them lead to diseases. Identification of disease-causing mutations is a challenging task and it will be helpful for designing therapeutic strategies. Hence, mutation data available in the literature have been curated and stored in several databases, which have been effectively utilized for developing computational methods to identify deleterious mutations (drivers), using sequence and structure-based properties of proteins. In this chapter, we describe the contents of specific databases that have information on disease-causing and neutral mutations followed by sequence and structure-based properties. Further, characteristic features of disease-causing mutations will be discussed along with computational methods for identifying cancer hotspot residues and disease-causing mutations in proteins.

Exploring alternative approaches to precision medicine through genomics and artificial intelligence - a systematic review

The core idea behind precision medicine is to pinpoint the subpopulations that differ from one another in terms of disease risk, drug responsiveness, and treatment outcomes due to differences in biology and other traits. Biomarkers are found through genomic sequencing. Multi-dimensional clinical and biological data are created using these biomarkers. Better analytic methods are needed for these multidimensional data, which can be accomplished by using artificial intelligence (AI). An updated review of 80 latest original publications is presented on four main fronts-preventive medicine, medication development, treatment outcomes, and diagnostic medicine-All these studies effectively illustrated the significance of AI in precision medicine. Artificial intelligence (AI) has revolutionized precision medicine by swiftly analyzing vast amounts of data to provide tailored treatments and predictive diagnostics. Through machine learning algorithms and high-resolution imaging, AI assists in precise diagnoses and early disease detection. AI's ability to decode complex biological factors aids in identifying novel therapeutic targets, allowing personalized interventions and optimizing treatment outcomes. Furthermore, AI accelerates drug discovery by navigating chemical structures and predicting drug-target interactions, expediting the development of life-saving medications. With its unrivaled capacity to comprehend and interpret data, AI stands as an invaluable tool in the pursuit of enhanced patient care and improved health outcomes. It's evident that AI can open a new horizon for precision medicine by translating complex data into actionable information. To get better results in this regard and to fully exploit the great potential of AI, further research is required on this pressing subject.

Multi-omic stratification of the missense variant cysteinome

Cancer genomes are rife with genetic variants; one key outcome of this variation is gain-ofcysteine, which is the most frequently acquired amino acid due to missense variants in COSMIC. Acquired cysteines are both driver mutations and sites targeted by precision therapies. However, despite their ubiquity, nearly all acquired cysteines remain uncharacterized. Here, we pair cysteine chemoproteomics-a technique that enables proteome-wide pinpointing of functional, redox sensitive, and potentially druggable residues-with genomics to reveal the hidden landscape of cysteine acquisition. For both cancer and healthy genomes, we find that cysteine acquisition is a ubiquitous consequence of genetic variation that is further elevated in the context of decreased DNA repair. Our chemoproteogenomics platform integrates chemoproteomic, whole exome, and RNA-seq data, with a customized 2-stage false discovery rate (FDR) error controlled proteomic search, further enhanced with a user-friendly FragPipe interface. Integration of CADD predictions of deleteriousness revealed marked enrichment for likely damaging variants that result in acquisition of cysteine. By deploying chemoproteogenomics across eleven cell lines, we identify 116 gain-of-cysteines, of which 10 were liganded by electrophilic druglike molecules. Reference cysteines proximal to missense variants were also found to be pervasive, 791 in total, supporting heretofore untapped opportunities for proteoform-specific chemical probe development campaigns. As chemoproteogenomics is further distinguished by sample-matched combinatorial variant databases and compatible with redox proteomics and small molecule screening, we expect widespread utility in guiding proteoform-specific biology and therapeutic discovery.

Proteoglycans: a common portal for SARS-CoV-2 and extracellular vesicle uptake

As structural components of the glycocalyx, heparan sulfate proteoglycans (HSPGs) are involved in multiple pathophysiological processes at the apex of cell signaling cascades, and as endocytosis receptors for particle structures, such as lipoproteins, extracellular vesicles, and enveloped viruses, including SARS-CoV-2. Given their diversity and complex biogenesis regulation, HSPGs remain understudied. Here we compile some of the latest studies focusing on HSPGs as internalizing receptors of extracellular vesicles ("endogenous virus") and SARS-CoV-2 lipid-enclosed particles and highlight similarities in their biophysical and structural characteristics. Specifically, the similarities in their biogenesis, size, and lipid composition may explain a common dependence on HSPGs for efficient cell-surface attachment and uptake. We further discuss the relative complexity of extracellular vesicle composition and the viral mechanisms that evolve towards increased infectivity that complicate therapeutic strategies addressing blockade of their uptake.

Quantitative differentiation of benign and misfolded glaucoma-causing myocilin variants on the basis of protein thermal stability

Accurate predictions of the pathogenicity of mutations associated with genetic diseases are key to the success of precision medicine. Inherited missense mutations in the myocilin (MYOC) gene, within its olfactomedin (OLF) domain, constitute the strongest genetic link to primary open-angle glaucoma via a toxic gain of function, and thus MYOC is an attractive precision-medicine target. However, not all mutations in MYOC cause glaucoma, and common variants are expected to be neutral polymorphisms. The Genome Aggregation Database (gnomAD) lists ∼100 missense variants documented within OLF, all of which are relatively rare (allele frequency <0.001%) and nearly all are of unknown pathogenicity. To distinguish disease-causing OLF variants from benign OLF variants, we first characterized the most prevalent population-based variants using a suite of cellular and biophysical assays, and identified two variants with features of aggregation-prone familial disease variants. Next, we considered all available biochemical and clinical data to demonstrate that pathogenic and benign variants can be differentiated statistically based on a single metric: the thermal stability of OLF. Our results motivate genotyping MYOC in patients for clinical monitoring of this widespread, painless and irreversible ocular disease.

Mediating and maintaining methylation while minimizing mutation: Recent advances on mammalian DNA methyltransferases

Mammalian genomes are methylated on carbon-5 of many cytosines, mostly in CpG dinucleotides. Methylation patterns are maintained during mitosis via DNMT1, and regulatory factors involved in processes that include histone modifications. Methylation in a sequence longer than CpG can influence the binding of sequence-specific transcription factors, thus affecting gene expression. 5-Methylcytosine deamination results in C-to-T transition. While some mutations are beneficial, most are not; so boosting C-to-T transitions can be dangerous. Given the role of DNMT3A in establishing de novo DNA methylation during development, it is this CpG methylation and deamination that provide the major mutagenic impetus in the DNMT3A gene itself, including the R882H dominant-negative substitution associated with two diseases: germline mutations in DNMT3A overgrowth syndrome, and somatic mutations in clonal hematopoiesis that can initiate acute myeloid leukemia. We discuss recent developments in therapeutics targeting DNMT1, the role of noncatalytic isoform DNMT3B3 in regulating de novo methylation by DNMT3A, and structural characterization of DNMT3A in various configurations.

Differential ETS1 binding to T:G mismatches within a CpG dinucleotide contributes to C-to-T somatic mutation rate of the IDH2 hotspot at codon Arg140

Cytosine to thymine (C>T) somatic mutation is highly enriched in certain types of cancer, and most commonly occurs via deamination of a 5-methylcytosine (5mC) to thymine, in the context of a CpG dinucleotide. In theory, deamination should occur at equal rates to both 5mC nucleotides on opposite strands. In most cases, the resulting T:G or G:T mismatch can be repaired by thymine DNA glycosylase activities. However, while some hotspot-associated CpG mutations have approximately equal numbers of mutations that resulted either from C>T or G>A in a CpG dinucleotide, many showed strand bias, being skewed toward C>T of the first base pair or G>A of the second base pair. Using the IDH2 Arg140 codon as a case study, we show that the two possible T:G mismatches at the codon-specific CpG site have differing effects on transcription factor ETS1 binding affinity, differentially affecting access of a repair enzyme (MBD4) to the deamination-caused T:G mismatch. Our study thus provides a plausible mechanism for exclusion of repair enzymes by the differential binding of transcription factors affecting the rate at which the antecedent opposite-strand mutations occur.

Double PIK3CA Alterations and Parallel Evolution in Colorectal Cancers

OBJECTIVES

To demonstrate clinicopathologic features and evaluate the clonality of double PIK3CA alterations in colorectal cancers (CRCs).

METHODS

Clonality was examined in 13 CRCs with double PIK3CA alterations (1.7% of CRCs or 9.6% of PIK3CA-mutated CRCs). Multiregional analyses were performed to confirm subclonal PIK3CA alterations.

RESULTS

PIK3CA alterations were detected within exon 9 (51%), exon 20 (23%), exon 1 (15%), and exon 7 (6.0%). CRCs with exon 7 alterations showed a significantly higher incidence of double PIK3CA alterations. Most double PIK3CA alterations consisted of a hotpsot alteration and an uncommon alteration; they were often clonal and present within a single tumor population. Multiregional analyses of CRCs with predicted subclonal double-alterations revealed multiclonal CRCs with divergent PIK3CA variant status originating from a common APC- and KRAS-mutated founder lineage of adenoma.

CONCLUSIONS

The findings supported multiclonal CRCs resulting from parallel evolution during the progression from adenoma to adenocarcinoma within the mitogen-activated protein kinase pathway, as previously demonstrated, or the mammalian target of rapamycin pathway. Further studies are warranted to elucidate clinical significance and potential targeted therapy for CRC patients with double PIK3CA alterations and impacts on clinical decision-making in patients with multiclonal CRCs harboring divergent PIK3CA mutational status.

Arginine Depletion in Human Cancers

Arginine is encoded by six different codons. Base pair changes in any of these codons can have a broad spectrum of effects including substitutions to twelve different amino acids, eighteen synonymous changes, and two stop codons. Four amino acids (histidine, cysteine, glutamine, and tryptophan) account for over 75% of amino acid substitutions of arginine. This suggests that a mutational bias, or "purifying selection", mechanism is at work. This bias appears to be driven by C > T and G > A transitions in four of the six arginine codons, a signature that is universal and independent of cancer tissue of origin or histology. Here, we provide a review of the available literature and reanalyze publicly available data from the Catalogue of Somatic Mutations in Cancer (COSMIC). Our analysis identifies several genes with an arginine substitution bias. These include known factors such as IDH1, as well as previously unreported genes, including four cancer driver genes (FGFR3, PPP6C, MAX, GNAQ). We propose that base pair substitution bias and amino acid physiology both play a role in purifying selection. This model may explain the documented arginine substitution bias in cancers.

The structure-based cancer-related single amino acid variation prediction

Single amino acid variation (SAV) is an amino acid substitution of the protein sequence that can potentially influence the entire protein structure or function, as well as its binding affinity. Protein destabilization is related to diseases, including several cancers, although using traditional experiments to clarify the relationship between SAVs and cancer uses much time and resources. Some SAV prediction methods use computational approaches, with most predicting SAV-induced changes in protein stability. In this investigation, all SAV characteristics generated from protein sequences, structures and the microenvironment were converted into feature vectors and fed into an integrated predicting system using a support vector machine and genetic algorithm. Critical features were used to estimate the relationship between their properties and cancers caused by SAVs. We describe how we developed a prediction system based on protein sequences and structure that is capable of distinguishing if the SAV is related to cancer or not. The five-fold cross-validation performance of our system is 89.73% for the accuracy, 0.74 for the Matthews correlation coefficient, and 0.81 for the F1 score. We have built an online prediction server, CanSavPre ( http://bioinfo.cmu.edu.tw/CanSavPre/ ), which is expected to become a useful, practical tool for cancer research and precision medicine.

Significant non-existence of sequences in genomes and proteomes

Minimal absent words (MAWs) are minimal-length oligomers absent from a genome or proteome. Although some artificially synthesized MAWs have deleterious effects, there is still a lack of a strategy for the classification of non-occurring sequences as potentially malicious or benign. In this work, by using Markovian models with multiple-testing correction, we reveal significant absent oligomers, which are statistically expected to exist. This suggests that their absence is due to negative selection. We survey genomes and proteomes covering the diversity of life and find thousands of significant absent sequences. Common significant MAWs are often mono- or dinucleotide tracts, or palindromic. Significant viral MAWs are often restriction sites and may indicate unknown restriction motifs. Surprisingly, significant mammal genome MAWs are often present, but rare, in other mammals, suggesting that they are suppressed but not completely forbidden. Significant human MAWs are frequently present in prokaryotes, suggesting immune function, but rarely present in human viruses, indicating viral mimicry of the host. More than one-fourth of human proteins are one substitution away from containing a significant MAW, with the majority of replacements being predicted harmful. We provide a web-based, interactive database of significant MAWs across genomes and proteomes.

Cancer and pH Dynamics: Transcriptional Regulation, Proteostasis, and the Need for New Molecular Tools

An emerging hallmark of cancer cells is dysregulated pH dynamics. Recent work has suggested that dysregulated intracellular pH (pHi) dynamics enable diverse cancer cellular behaviors at the population level, including cell proliferation, cell migration and metastasis, evasion of apoptosis, and metabolic adaptation. However, the molecular mechanisms driving pH-dependent cancer-associated cell behaviors are largely unknown. In this review article, we explore recent literature suggesting pHi dynamics may play a causative role in regulating or reinforcing tumorigenic transcriptional and proteostatic changes at the molecular level, and discuss outcomes on tumorigenesis and tumor heterogeneity. Most of the data we discuss are population-level analyses; lack of single-cell data is driven by a lack of tools to experimentally change pHi with spatiotemporal control. Data is also sparse on how pHi dynamics play out in complex in vivo microenvironments. To address this need, at the end of this review, we cover recent advances for live-cell pHi measurement at single-cell resolution. We also discuss the essential role for tool development in revealing mechanisms by which pHi dynamics drive tumor initiation, progression, and metastasis.

Litmus-Body: A Molecularly Targeted Sensor for Cell-Surface pH Measurements

Precise pH measurements in the immediate environment of receptors is essential for elucidating the mechanisms through which local pH changes associated with diseased phenotypes manifest into aberrant receptor function. However, current pH sensors lack the ability to localize and target specific receptor molecules required to make these measurements. Herein we present the Litmus-body, our recombinant protein-based pH sensor, which through fusion to an anti-IgG nanobody is capable of piggybacking on IgG antibodies for molecular targeting to specific proteins on the cell surface. By normalizing a pH-dependent green fluorescent protein to a long Stokes shift red fluorophore or fluorescent protein, we readily report pH independent of sensor concentration using a single 488 nm excitation. Our Litmus-body showed excellent responsiveness in solution, with a greater than 50-fold change across the regime of physiological pH. The sensor was further validated for use on live cells and shown to be specific to the protein of interest. In complex with our Litmus-body, cetuximab therapeutic antibody retained its functionality in binding and inhibiting ligand interaction of its target epidermal growth factor receptor (EGFR), triggering receptor-mediated endocytosis that allowed tracking of local pH from the cell surface through the endocytic pathway.

Sensitivity of Alphaviruses to G3BP Deletion Correlates with Efficiency of Replicase Polyprotein Processing

We present a comprehensive overview of the dependency of several Old World alphaviruses for the host protein G3BP. Based on their replication ability in G3BP-deleted cells, Old World alphaviruses can be categorized into two groups, being either resistant or sensitive to G3BP deletion. We observed that all sensitive viruses have an Arg residue at the P4 position of the cleavage site between the nonstructural protein P1 (nsP1) and nsP2 regions of the replicase precursor polyprotein (1/2 site), while a different residue is found at this site in viruses resistant to G3BP deletion. Swapping this residue between resistant and sensitive viruses also switches the G3BP deletion sensitivity. In the absence of G3BP, chikungunya virus (CHIKV) replication is at the limit of detection. The P4 Arg-to-His substitution partially rescues this defect. The P4 residue of the 1/2 site is known to play a regulatory role during processing at this site, and we found that if processing is blocked, the influence of the P4 residue on the sensitivity to G3BP deletion is abolished. Immunofluorescence experiments with CHIKV replicase with manipulated processing indicate that the synthesis of double-stranded RNA is defective in the absence of G3BP and suggest a role of G3BP during negative-strand RNA synthesis. This study provides a functional link between the host protein G3BP and the P4 residue of the 1/2 site for viral RNA replication of Old World alphaviruses. While this suggests a link between G3BP proteins and viral replicase polyprotein processing, we propose that G3BP proteins do not have a regulatory role during polyprotein processing.IMPORTANCE Old World alphaviruses comprise several medically relevant viruses, including chikungunya virus and Ross River virus. Recurrent outbreaks and the lack of antivirals and vaccines demand ongoing research to fight the emergence of these infectious diseases. In this context, a thorough investigation of virus-host interactions is critical. Here, we highlight the importance of the host protein G3BP for several Old World alphaviruses. Our data strongly suggest that G3BP plays a crucial role for the activity of the viral replicase and, thus, the amplification of the viral RNA genome. To our knowledge, the present work is the first to provide a functional link between the regulation of viral polyprotein processing and RNA replication and a host factor for alphaviruses. Moreover, the results of this study raise several questions about the fundamental regulatory mechanisms that dictate the activity of the viral replicase, thereby paving the way for future studies.

What is pH regulation, and why do cancer cells need it?

Metabolism is a continuous source of acids. To keep up with a desired metabolic rate, tumors must establish an adequate means of clearing their acidic end-products. This homeostatic priority is achieved by various buffers, enzymes, and transporters connected through the common denominator of H⁺ ions. Whilst this complexity is proportionate to the importance of adequate pH control, it is problematic for developing an intuition for tracking the route taken by acids, assessing the relative importance of various acid-handling proteins, and predicting the outcomes of pharmacological inhibition or genetic alteration. Here, with the help of a simplified mathematical framework, the genesis of cancer pH regulation is explained in terms of the obstacles to efficient acid venting and how these are overcome by specific molecules, often associated with cancer. Ultimately, the pH regulatory apparatus in tumors must (i) provide adequate lactic acid permeability through membranes, (ii) facilitate CO₂/HCO₃⁻/H⁺ diffusivity across the interstitium, (iii) invest in a form of active transport that strikes a favorable balance between intracellular pH and intracellular lactate retention under the energetic constraints of a cell, and (iv) enable the necessary feedback to complete the homeostatic loop. A more informed and quantitative approach to understanding acid-handling in cancer is mandatory for identifying vulnerabilities, which could be exploited as therapeutic targets.

Intracellular pH dynamics and charge-changing somatic mutations in cancer

An unresolved question critical for understanding cancer is how recurring somatic mutations are retained and how selective pressures drive retention. Increased intracellular pH (pHi) is common to most cancers and is an early event in cancer development. Recent work shows that recurrent somatic mutations can confer an adaptive gain in pH sensing to mutant proteins, enhancing tumorigenic phenotypes specifically at the increased pHi of cancer. Newly identified amino acid mutation signatures in cancer suggest charge-changing mutations define and shape the mutational landscape of cancer. Taken together, these results support a new perspective on the functional significance of somatic mutations in cancer. In this review, we explore existing data and new directions for better understanding how changes in dynamic pH sensing by somatic mutation might be conferring a fitness advantage to the high pH of cancer.

Physicochemical Foundations of Life that Direct Evolution: Chance and Natural Selection are not Evolutionary Driving Forces

The current framework of evolutionary theory postulates that evolution relies on random mutations generating a diversity of phenotypes on which natural selection acts. This framework was established using a top-down approach as it originated from Darwinism, which is based on observations made of complex multicellular organisms and, then, modified to fit a DNA-centric view. In this article, it is argued that based on a bottom-up approach starting from the physicochemical properties of nucleic and amino acid polymers, we should reject the facts that (i) natural selection plays a dominant role in evolution and (ii) the probability of mutations is independent of the generated phenotype. It is shown that the adaptation of a phenotype to an environment does not correspond to organism fitness, but rather corresponds to maintaining the genome stability and integrity. In a stable environment, the phenotype maintains the stability of its originating genome and both (genome and phenotype) are reproduced identically. In an unstable environment (i.e., corresponding to variations in physicochemical parameters above a physiological range), the phenotype no longer maintains the stability of its originating genome, but instead influences its variations. Indeed, environment- and cellular-dependent physicochemical parameters define the probability of mutations in terms of frequency, nature, and location in a genome. Evolution is non-deterministic because it relies on probabilistic physicochemical rules, and evolution is driven by a bidirectional interplay between genome and phenotype in which the phenotype ensures the stability of its originating genome in a cellular and environmental physicochemical parameter-depending manner.

Spatiotemporal pH Heterogeneity as a Promoter of Cancer Progression and Therapeutic Resistance

Dysregulation of pH in solid tumors is a hallmark of cancer. In recent years, the role of altered pH heterogeneity in space, between benign and aggressive tissues, between individual cancer cells, and between subcellular compartments, has been steadily elucidated. Changes in temporal pH-related processes on both fast and slow time scales, including altered kinetics of bicarbonate-CO₂ exchange and its effects on pH buffering and gradual, progressive changes driven by changes in metabolism, are further implicated in phenotypic changes observed in cancers. These discoveries have been driven by advances in imaging technologies. This review provides an overview of intra- and extracellular pH alterations in time and space reflected in cancer cells, as well as the available technology to study pH spatiotemporal heterogeneity.

Building a Hybrid Physical-Statistical Classifier for Predicting the Effect of Variants Related to Protein-Drug Interactions

A key issue in drug design is how population variation affects drug efficacy by altering binding affinity (BA) in different individuals, an essential consideration for government regulators. Ideally, we would like to evaluate the BA perturbations of millions of single-nucleotide variants (SNVs). However, only hundreds of protein-drug complexes with SNVs have experimentally characterized BAs, constituting too small a gold standard for straightforward statistical model training. Thus, we take a hybrid approach: using physically based calculations to bootstrap the parameterization of a full model. In particular, we do 3D structure-based docking on ∼10,000 SNVs modifying known protein-drug complexes to construct a pseudo gold standard. Then we use this augmented set of BAs to train a statistical model combining structure, ligand and sequence features and illustrate how it can be applied to millions of SNVs. Finally, we show that our model has good cross-validated performance (97% AUROC) and can also be validated by orthogonal ligand-binding data.

Integrative analysis of exogenous, endogenous, tumour and immune factors for precision medicine

Immunotherapy strategies targeting immune checkpoints such as the CTLA4 and CD274 (programmed cell death 1 ligand 1, PD-L1)/PDCD1 (programmed cell death 1, PD-1) T-cell coreceptor pathways are revolutionising oncology. The approval of pembrolizumab use for solid tumours with high-level microsatellite instability or mismatch repair deficiency by the US Food and Drug Administration highlights promise of precision immuno-oncology. However, despite evidence indicating influences of exogenous and endogenous factors such as diet, nutrients, alcohol, smoking, obesity, lifestyle, environmental exposures and microbiome on tumour-immune interactions, integrative analyses of those factors and immunity lag behind. Immune cell analyses in the tumour microenvironment have not adequately been integrated into large-scale studies. Addressing this gap, the transdisciplinary field of molecular pathological epidemiology (MPE) offers research frameworks to integrate tumour immunology into population health sciences, and link the exposures and germline genetics (eg, HLA genotypes) to tumour and immune characteristics. Multilevel research using bioinformatics, in vivo pathology and omics (genomics, epigenomics, transcriptomics, proteomics and metabolomics) technologies is possible with use of tissue, peripheral blood circulating cells, cell-free plasma, stool, sputum, urine and other body fluids. This immunology-MPE model can synergise with experimental immunology, microbiology and systems biology. GI neoplasms represent exemplary diseases for the immunology-MPE model, given rich microbiota and immune tissues of intestines, and the well-established carcinogenic role of intestinal inflammation. Proof-of-principle studies on colorectal cancer provided insights into immunomodulating effects of aspirin, vitamin D, inflammatory diets and omega-3 polyunsaturated fatty acids. The integrated immunology-MPE model can contribute to better understanding of environment-tumour-immune interactions, and effective immunoprevention and immunotherapy strategies for precision medicine.

Physical biology of the cancer cell glycocalyx

The glycocalyx coating the outside of most cells is a polymer meshwork comprising proteins and complex sugar chains called glycans. From a physical perspective, the glycocalyx has long been considered a simple 'slime' that protects cells from mechanical disruption or against pathogen interactions, but the great complexity of the structure argues for the evolution of more advanced functionality: the glycocalyx serves as the complex physical environment within which cell-surface receptors reside and operate. Recent studies have demonstrated that the glycocalyx can exert thermodynamic and kinetic control over cell signalling by serving as the local medium within which receptors diffuse, assemble and function. The composition and structure of the glycocalyx change markedly with changes in cell state, including transformation. Notably, cancer-specific changes fuel the synthesis of monomeric building blocks and machinery for production of long-chain polymers that alter the physical and chemical structure of the glycocalyx. In this Review, we discuss these changes and their physical consequences on receptor function and emergent cell behaviours.

Cancer-associated arginine-to-histidine mutations confer a gain in pH sensing to mutant proteins

The intracellular pH (pHi) of most cancers is constitutively higher than that of normal cells and enhances proliferation and cell survival. We found that increased pHi enabled the tumorigenic behaviors caused by somatic arginine-to-histidine mutations, which are frequent in cancer and confer pH sensing not seen with wild-type proteins. Experimentally raising the pHi increased the activity of R776H mutant epidermal growth factor receptor (EGFR-R776H), thereby increasing proliferation and causing transformation in fibroblasts. An Arg-to-Gly mutation did not confer these effects. Molecular dynamics simulations of EGFR suggested that decreased protonation of His⁷⁷⁶ at high pH causes conformational changes in the αC helix that may stabilize the active form of the kinase. An Arg-to-His, but not Arg-to-Lys, mutation in the transcription factor p53 (p53-R273H) decreased its transcriptional activity and attenuated the DNA damage response in fibroblasts and breast cancer cells with high pHi. Lowering pHi attenuated the tumorigenic effects of both EGFR-R776H and p53-R273H. Our data suggest that some somatic mutations may confer a fitness advantage to the higher pHi of cancer cells.