Phase and context shape the function of composite oncogenic mutations

Oncogenic composite mutations can be predicted by co-mutations and their chromosomal location

Genetic heterogeneity in tumors can show a remarkable selectivity when two or more independent genetic events occur in the same gene. This phenomenon, called composite mutation, points toward a selective pressure, which frequently causes therapy resistance to mutation-specific drugs. Since composite mutations have been described to occur in sub-clonal populations, they are not always captured through biopsy sampling. Here, we provide a proof of concept to predict composite mutations to anticipate which patients might be at risk for sub-clonally driven therapy resistance. We found that composite mutations occur in 5% of cancer patients, mostly affecting the PIK3CA, EGFR, BRAF, and KRAS genes, which are common precision medicine targets. Furthermore, we found a strong and significant relationship between the frequencies of composite mutations with commonly co-occurring mutations in a non-composite context. We also found that co-mutations are significantly enriched on the same chromosome. These observations were independently confirmed using cell line data. Finally, we show the feasibility of predicting compositive mutations based on their co-mutations (AUC 0.62, 0.81, 0.82, and 0.91 for EGFR, PIK3CA, KRAS, and BRAF, respectively). This prediction model could help to stratify patients who are at risk of developing therapy resistance-causing mutations.

Pan-Cancer Analysis of ART1 and its Potential Value in Gastric Cancer

Objective: To comprehensively explore the impact of Mono-ADP-ribosyltransferases-1 expression on both prognosis and the intricate landscape of the tumor immune microenvironment across diverse cancer types, our study seeks to delve into the multifaceted interplay between Mono-ADP-ribosyltransferases-1 expression levels and their implications for clinical outcomes and the dynamic milieu of immune responses within tumors. Methods: Genomic, transcriptomic, and clinical datasets spanning diverse cancer types were meticulously curated from The Cancer Genome Atlas and Genotypic Tissue Expression repositories. Initially, our inquiry focused on discerning the prognostic significance and immunological implications of Mono-ADP-ribosyltransferases-1 expression across this heterogeneous spectrum of malignancies. Subsequently, we scrutinized the relationships between Mono-ADP-ribosyltransferases-1 expression levels and a spectrum of factors including RNA modification genes, genetic mutations, and the emergent concept of tumor stemness. Employing functional enrichment analyses, we endeavored to unravel the underlying mechanistic pathways modulated by Mono-ADP-ribosyltransferases-1. Leveraging Bayesian co-localization analysis, we sought to discern the spatial convergence of Mono-ADP-ribosyltransferases-1 expression particularly within the context of digestive tract tumors. Lastly, to corroborate our findings, we conducted in vitro experiments, specifically focusing on Gastric Cancer, thus corroborating the putative oncogenic role attributed to Mono-ADP-ribosyltransferases-1 in this malignancy. Results: Across diverse tumor types, Mono-ADP-ribosyltransferases-1 expression exhibits distinctive patterns compared to normal and adjacent tissues, thereby intertwining with the prognostic outcomes of numerous cancer patients. Noteworthy findings from our immune role identification underscore the pivotal involvement of Mono-ADP-ribosyltransferases-1 in the landscape of tumor immunotherapy. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis elucidates the enrichment of Mono-ADP-ribosyltransferases-1-associated genes predominantly within the NF-kB, Foxo, and PI3K-Akt signaling cascades, shedding light on potential mechanistic pathways underlying its influence. Bayesian co-localization analysis unveils a compelling genetic correlation between Mono-ADP-ribosyltransferases-1 and digestive tract tumors, accentuating its relevance within this specific oncological domain. Importantly, experimental validation attests to the therapeutic promise of targeting Mono-ADP-ribosyltransferases-1 in the treatment paradigm of gastric cancer, thereby underscoring its potential as a viable therapeutic target deserving of further exploration and clinical translation. Conclusion: This comprehensive pan-cancer analysis unveils crucial insights into the intricate role played by Mono-ADP-ribosyltransferases-1 in the tumorigenesis of diverse malignancies, thereby establishing a robust theoretical framework for subsequent in-depth investigations. Leveraging these insights, targeting Mono-ADP-ribosyltransferases-1-related signaling pathways within the dynamic tumor microenvironment emerges as a promising avenue for novel therapeutic interventions in the realm of tumor immunotherapy. By delineating the interplay between Mono-ADP-ribosyltransferases-1 expression and tumorigenic processes across various cancer types, this study paves the way for innovative therapeutic strategies aimed at disrupting oncogenic signaling cascades and bolstering immune-mediated antitumor responses.

How CRISPR Is Revolutionizing the Generation of New Models for Cancer Research

Cancers arise through acquisition of mutations in genes that regulate core biological processes like cell proliferation and cell death. Decades of cancer research have led to the identification of genes and mutations causally involved in disease development and evolution, yet defining their precise function across different cancer types and how they influence therapy responses has been challenging. Mouse models have helped define the in vivo function of cancer-associated alterations, and genome-editing approaches using CRISPR have dramatically accelerated the pace at which these models are developed and studied. Here, we highlight how CRISPR technologies have impacted the development and use of mouse models for cancer research and discuss the many ways in which these rapidly evolving platforms will continue to transform our understanding of this disease.

Multiple Somatic Mutations of SMARCA4 in Small Cell Carcinoma of the Ovary, Hypercalcemic Type: A Case Report

Small-cell carcinoma of the ovary, the hypercalcemic type (SCCOHT) is a rare, aggressive tumor that primarily affects young females. It is a monogenic disorder caused by germline and/or somatic SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 4 (SMARCA4) mutations. Here, we report a case of SCCOHT harboring multiple previously unreported somatic mutations in SMARCA4 (c.2866_2867delC>T; c.3543del). A 28-year-old breastfeeding Japanese female presented to a previous hospital with nausea and vomiting. She had no family history of relevant malignancies, including ovarian cancer. Based on an evaluation performed at another institution, she was referred to a gynecologist for suspected ovarian cancer. Imaging studies revealed a 16×15 cm heterogenous enhancing mass within the right ovary without lymph node or distant metastasis. She had mild ascites without peritoneal dissemination, but there was an elevation in the serum calcium level (15.1 mg/dL). The patient underwent cytoreductive surgery and was pathologically diagnosed with SCCOHT. Auxiliary immunohistochemical staining confirmed the loss of SMARCA4 protein expression. The patient was diagnosed with the International Federation of Gynecology and Obstetrics (FIGO) 2014 stage IA (pT1a pN0 M0). The serum calcium levels returned to normal post-surgery. Matched-pair analysis using tumor tissue and peripheral blood revealed multiple somatic mutations in SMARCA4, but no deleterious germline mutations were present. Microsatellite instability was not significant, and the patients had a heterozygous mutation of uridine diphosphate glucuronosyl transferase 1A1 (UGT1A1)*6. She underwent six cycles of irinotecan hydrochloride plus cisplatin chemotherapy and achieved complete remission. The patient was finally examined and evaluated 45 months postoperatively; there was no evidence of the disease. Overall, the genetic findings will not aid in the SCCOHT diagnosis and relevant genetic counseling; however, they may have implications for the treatment of this disease in the future.

Decoding p53 tumor suppression: a crosstalk between genomic stability and epigenetic control?

Genomic instability, a hallmark of cancer, is a direct consequence of the inactivation of the tumor suppressor protein p53. Genetically modified mouse models and human tumor samples have revealed that p53 loss results in extensive chromosomal abnormalities, from copy number alterations to structural rearrangements. In this perspective article we explore the multifaceted relationship between p53, genomic stability, and epigenetic control, highlighting its significance in cancer biology. p53 emerges as a critical regulator of DNA repair mechanisms, influencing key components of repair pathways and directly participating in DNA repair processes. p53 role in genomic integrity however extends beyond its canonical functions. p53 influences also epigenetic landscape, where it modulates DNA methylation and histone modifications. This epigenetic control impacts the expression of genes involved in tumor suppression and oncogenesis. Notably, p53 ability to ensure cellular response to DNA demethylation contributes to the maintenance of genomic stability by preventing unscheduled transcription of repetitive non-coding genomic regions. This latter indicates a causative relationship between the control of epigenetic stability and the maintenance of genomic integrity in p53-mediated tumor suppression. Understanding these mechanisms offers promising avenues for innovative therapeutic strategies targeting epigenetic dysregulation in cancer and emphasizes the need for further research to unravel the complexities of this relationship. Ultimately, these insights hold the potential to transform cancer treatment and prevention strategies.

Experimental validation and pan-cancer analysis identified COL10A1 as a novel oncogene and potential therapeutic target in prostate cancer

BACKGROUND

Type X collagen (COL10) is a homologous trimeric non-fibrillar collagen found in the extracellular matrix of human tissues, and it exhibits a distinctive white appearance. Type X collagen α1 chain (COL10A1) is a specific cleaved fragment of type X collagen. However, the expression, prognostic significance, clinicopathological attributes and immune-related associations of COL10A1 in prostate cancer as well as in pan-cancer contexts remain poorly understood.

METHODS

Using bioinformatic analysis of data from the most recent databases (TCGA, GTEx and GEO databases), we have extensively elucidated the role played by COL10A1 in terms of its expression patterns, prognostic implications, and immune efficacy across a pan-cancer spectrum. Subsequently, the biological functions of COL10A1 in prostate cancer were elucidated by experimental validation.

RESULTS

Our findings have confirmed that COL10A1 was highly expressed in most cancers and was associated with poorer prognosis in cancer patients. Immune correlation analysis of COL10A1 in various cancers showed its significant correlation with Tumor mutational burden (TMB), microsatellite instability (MSI) and immune cell infiltration. In addition, knockdown of COL10A1 in prostate cancer resulted in a substantial reduction in the proliferation, migration, and invasive potential of prostate cancer cells.

CONCLUSION

Our pan-cancer analysis of COL10A1 gene provided novel insights into its pivotal role in cancer initiation, progression, and therapeutic implications, underscoring its potential significance in prognosis and immunotherapeutic interventions for cancer, particularly prostate cancer.

Multiple Mutations within Individual Oncogenes: Examples and Clinical Implications

Gain-of-function mutations had been believed to function as a single mutation in oncogenes, although some secondary mutations, such as EGFR T790M mutations, are frequently acquired in patients that are resistant to tyrosine kinase inhibitor treatment. Recently, we and other investigators have reported that multiple mutations (MMs) frequently occur in the same oncogene before any therapy. In a recent pan-cancer study, we identified 14 pan-cancer oncogenes (such as PIK3CA and EGFR) and 6 cancer type-specific oncogenes that are significantly affected by MMs. Of these, 9% of cases with at least one mutation have MMs that are cis-presenting on the same allele. Interestingly, MMs show distinct mutational patterns in various oncogenes relative to single mutations in terms of mutation type, position, and amino acid substitution. Specifically, functionally weak, uncommon mutations are overrepresented in MMs, which enhance oncogenic activity in combination. Here, we present an overview of the current understanding of oncogenic MMs in human cancers and provide insights into their underlying mechanisms and clinical implications.

Acquired Secondary HER2 Mutations Enhance HER2/MAPK Signaling and Promote Resistance to HER2 Kinase Inhibition in Breast Cancer

HER2 mutations drive the growth of a subset of breast cancers and are targeted with HER2 tyrosine kinase inhibitors (TKI) such as neratinib. However, acquired resistance is common and limits the durability of clinical responses. Most HER2-mutant breast cancers progressing on neratinib-based therapy acquire secondary mutations in HER2. It is unknown whether these secondary HER2 mutations, other than the HER2T798I gatekeeper mutation, are causal to neratinib resistance. Herein, we show that secondary acquired HER2T862A and HER2L755S mutations promote resistance to HER2 TKIs via enhanced HER2 activation and impaired neratinib binding. While cells expressing each acquired HER2 mutation alone were sensitive to neratinib, expression of acquired double mutations enhanced HER2 signaling and reduced neratinib sensitivity. Computational structural modeling suggested that secondary HER2 mutations stabilize the HER2 active state and reduce neratinib binding affinity. Cells expressing double HER2 mutations exhibited resistance to most HER2 TKIs but retained sensitivity to mobocertinib and poziotinib. Double-mutant cells showed enhanced MEK/ERK signaling, which was blocked by combined inhibition of HER2 and MEK. Together, these findings reveal the driver function of secondary HER2 mutations in resistance to HER2 inhibition and provide a potential treatment strategy to overcome acquired resistance to HER2 TKIs in HER2-mutant breast cancer.

SIGNIFICANCE

HER2-mutant breast cancers acquire secondary HER2 mutations that drive resistance to HER2 tyrosine kinase inhibitors, which can be overcome by combined inhibition of HER2 and MEK.

Characterization of pancreatic cancer with ultra-low tumor mutational burden

In pancreatic cancer (PC), Tumor mutation burden (TMB) has been reported to be lower than in other cancers, with its clinical significance remaining unclear. We analyzed the dataset of whole-exome sequencing and gene expression profiling of 93 resected PC cases. The median TMB was 0.24. The TMB was classified as High (≥ 5.0), Low (< 5.0, ≥ 1.0), or Ultra-low (< 1.0). Nineteen samples (20%) were classified as TMB-low, and 74 (80%) were classified as TMB-ultra-low; no samples were TMB-high. TMB-ultra-low PC had significantly fewer borderline resectable lesions (P = 0.028) and fewer adenosquamous carcinomas (P = 0.003) than TBM-low PC. Furthermore, the TMB-ultra-low PC showed significantly lower detection rates of driver mutations and copy number variations. Microsatellite instability was not significantly correlated with the TMB status. The TMB-ultra-low PC had a significantly better prognosis than TBM-low PC (P = 0.023). A multivariate analysis identified TMB-ultra-low PC as an independent favorable prognostic factor (hazard ratio, 2.11; P = 0.019). A gene expression analysis showed that TMB-ultra-low PC was associated with reduced TP53 inactivation (P = 0.003) and reduced chromosomal instability (P = 0.001) compared to TBM-low PC. TMB-ultra-low PC had specific gene expression signatures and a better prognosis than TMB-low PC.

Pan-cancer clinical impact of latent drivers from double mutations

Here, we discover potential 'latent driver' mutations in cancer genomes. Latent drivers have low frequencies and minor observable translational potential. As such, to date they have escaped identification. Their discovery is important, since when paired in cis, latent driver mutations can drive cancer. Our comprehensive statistical analysis of the pan-cancer mutation profiles of ~60,000 tumor sequences from the TCGA and AACR-GENIE cohorts identifies significantly co-occurring potential latent drivers. We observe 155 same gene double mutations of which 140 individual components are cataloged as latent drivers. Evaluation of cell lines and patient-derived xenograft response data to drug treatment indicate that in certain genes double mutations may have a prominent role in increasing oncogenic activity, hence obtaining a better drug response, as in PIK3CA. Taken together, our comprehensive analyses indicate that same-gene double mutations are exceedingly rare phenomena but are a signature for some cancer types, e.g., breast, and lung cancers. The relative rarity of doublets can be explained by the likelihood of strong signals resulting in oncogene-induced senescence, and by doublets consisting of non-identical single residue components populating the background mutational load, thus not identified.

Interrogating the Human Diplome: Computational Methods, Emerging Applications, and Challenges

Human DNA sequencing protocols have revolutionized human biology, biomedical science, and clinical practice, but still have very important limitations. One limitation is that most protocols do not separate or assemble (i.e., "phase") the nucleotide content of each of the maternally and paternally derived chromosomal homologs making up the 22 autosomal pairs and the chromosomal pair making up the pseudo-autosomal region of the sex chromosomes. This has led to a dearth of studies and a consequent underappreciation of many phenomena of fundamental importance to basic and clinical genomic science. We discuss a few protocols for obtaining phase information as well as their limitations, including those that could be used in tumor phasing settings. We then describe a number of biological and clinical phenomena that require phase information. These include phenomena that require precise knowledge of the nucleotide sequence in a chromosomal segment from germline or somatic cells, such as DNA binding events, and insight into unique cis vs. trans-acting functionally impactful variant combinations-for example, variants implicated in a phenotype governed by compound heterozygosity. In addition, we also comment on the need for reliable and consensus-based diploid-context computational workflows for variant identification as well as the need for laboratory-based functional verification strategies for validating cis vs. trans effects of variant combinations. We also briefly describe available resources, example studies, as well as areas of further research, and ultimately argue that the science behind the study of human diploidy, referred to as "diplomics," which will be enabled by nucleotide-level resolution of phased genomes, is a logical next step in the analysis of human genome biology.

Pan-cancer landscape of AID-related mutations, composite mutations, and their potential role in the ICI response

Activation-induced cytidine deaminase, AICDA or AID, is a driver of somatic hypermutation and class-switch recombination in immunoglobulins. In addition, this deaminase belonging to the APOBEC family may have off-target effects genome-wide, but its effects at pan-cancer level are not well elucidated. Here, we used different pan-cancer datasets, totaling more than 50,000 samples analyzed by whole-genome, whole-exome, or targeted sequencing. AID mutations are present at pan-cancer level with higher frequency in hematological cancers and higher presence at transcriptionally active TAD domains. AID synergizes initial hotspot mutations by a second composite mutation. AID mutational load was found to be independently associated with a favorable outcome in immune-checkpoint inhibitors (ICI) treated patients across cancers after analyzing 2000 samples. Finally, we found that AID-related neoepitopes, resulting from mutations at more frequent hotspots if compared to other mutational signatures, enhance CXCL13/CCR5 expression, immunogenicity, and T-cell exhaustion, which may increase ICI sensitivity.

Genomic and Metabolic Hallmarks of SDH- and FH-deficient Renal Cell Carcinomas

BACKGROUND

Succinate dehydrogenase-deficient and fumarate hydratase-deficient renal cell carcinomas (SDHRCC and FHRCC) are rare kidney cancers driven by loss of TCA cycle enzymes.

OBJECTIVE

To define and compare the genomic and metabolomic hallmarks of SDHRCC and FHRCC.

DESIGN, SETTING, AND PARTICIPANTS

We analyzed SDHRCC and FHRCC tumors with either immunohistochemical evidence of loss of protein expression or genomically confirmed biallelic inactivation of SDHA/B/C/D/AF2 or FH.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Somatic alterations were identified using clinical pipelines, with allele-specific copy number alterations (CNAs) identified using FACETS. Mass spectrometry-based metabolomic profiling was performed on available SDHRCC and FHRCC tumors.

RESULTS AND LIMITATIONS

Tumors were analyzed for 42 patients (25 FHRCC, 17 SDHRCC). In the germline analysis, 16/17 SDHRCCs harbored a germline alteration in SDHB, whereas only 17/22 FHRCCs had pathogenic germline FH variants. SDHRCCs had a lower mutation burden (p = 0.02) and CNA burden (p = 0.0002) than FHRCCs. All SDHRCCs presented with deletion of chromosome 1p (overlapping SDHB), whereas FHRCCs demonstrated high but not ubiquitous loss of 1q (FH locus). Both SDHRCCs and FHRCCs exhibited significant idiopathic accumulation of the metabolite guanine. FHRCC tumors had elevated levels of urea cycle metabolites (argininosuccinate, citrulline, and fumarate), whereas SDHRCC tumors had elevation of numerous acylcarnitines. These characteristic metabolic changes allowed identification of a previously unrecognized SDH-deficient RCC.

CONCLUSIONS

Despite sharing similar genetic etiology, SDHRCC and FHRCC represent distinct molecular entities with unique genetic and metabolic abnormalities.

PATIENT SUMMARY

Kidney cancers driven by loss of the gene encoding either the succinate dehydrogenase or fumarate hydratase enzyme are rare. We sought to define and compare the genetic and metabolic features of these cancer entities.

Base editing sensor libraries for high-throughput engineering and functional analysis of cancer-associated single nucleotide variants

Base editing can be applied to characterize single nucleotide variants of unknown function, yet defining effective combinations of single guide RNAs (sgRNAs) and base editors remains challenging. Here, we describe modular base-editing-activity 'sensors' that link sgRNAs and cognate target sites in cis and use them to systematically measure the editing efficiency and precision of thousands of sgRNAs paired with functionally distinct base editors. By quantifying sensor editing across >200,000 editor-sgRNA combinations, we provide a comprehensive resource of sgRNAs for introducing and interrogating cancer-associated single nucleotide variants in multiple model systems. We demonstrate that sensor-validated tools streamline production of in vivo cancer models and that integrating sensor modules in pooled sgRNA libraries can aid interpretation of high-throughput base editing screens. Using this approach, we identify several previously uncharacterized mutant TP53 alleles as drivers of cancer cell proliferation and in vivo tumor development. We anticipate that the framework described here will facilitate the functional interrogation of cancer variants in cell and animal models.

Open Structural Data in Precision Medicine

Three-dimensional protein structural data at the molecular level are pivotal for successful precision medicine. Such data are crucial not only for discovering drugs that act to block the active site of the target mutant protein but also for clarifying to the patient and the clinician how the mutations harbored by the patient work. The relative paucity of structural data reflects their cost, challenges in their interpretation, and lack of clinical guidelines for their utilization. Rapid technological advancements in experimental high-resolution structural determination increasingly generate structures. Computationally, modeling algorithms, including molecular dynamics simulations, are becoming more powerful, as are compute-intensive hardware, particularly graphics processing units, overlapping with the inception of the exascale era. Accessible, freely available, and detailed structural and dynamical data can be merged with big data to powerfully transform personalized pharmacology. Here we review protein and emerging genome high-resolution data, along with means, applications, and examples underscoring their usefulness in precision medicine. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Pan-Cancer Analysis Identified CD93 as a Valuable Biomarker for Predicting Patient Prognosis and Immunotherapy Response

Background: The rapid development of immunotherapy has significantly improved patient outcomes in recent years. CD93, a novel biomarker expressed on vascular endothelial cells, is essential for tumor angiogenesis. Recent studies have shown that CD93 is closely related to immune cell infiltration and immunotherapy. However, its role in pan-cancer has not been reported.

Methods: The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), cbioportal, Gene Expression Omnibus (GEO), Tumor Immune Estimation Resource (TIMER2.0), and the Tumor–Immune System Interactions and Drug Bank (TISIDB) databases were used to analyze CD93 in pan-cancers. R software was used for statistical analysis and mapping.

Results: There were significant differences in the expression of CD93 between tumor tissues and adjacent normal tissues in pan-cancer. The high expression of CD93 was associated with poor prognosis and high TNM stage in multiple tumor types. However, a high expression of CD93 was a protective factor in kidney renal clear cell carcinoma (KIRC). In addition, CD93 was closely related to immune cell infiltration in tumor tissues. Moreover, CD93 presented a robust correlation with immune modulators and immunotherapeutic markers [e.g., tumor mutation burden (TMB) and microsatellite instability (MSI)]. The results of gene set enrichment analysis (GSEA) showed that CD93 was correlated with tumor angiogenesis. Importantly, patients with a low expression of CD93 were more sensitive to immunotherapy in urothelial cancer.

Conclusion: CD93, which is involved in various immune responses, controls immune cell infiltration and impacts on the malignant properties of various cancer types. Therefore, CD93 has potential value to be biomarker for determining the prognosis and immune infiltration in multiple cancers.

The cAMP-signaling cancers: Clinically-divergent disorders with a common central pathway

The cAMP-signaling cancers, which are defined by functionally-significant somatic mutations in one or more elements of the cAMP signaling pathway, have an unexpectedly wide range of cell origins, clinical manifestations, and potential therapeutic options. Mutations in at least 9 cAMP signaling pathway genes (TSHR, GPR101, GNAS, PDE8B, PDE11A, PRKARA1, PRKACA, PRKACB, and CREB) have been identified as driver mutations in human cancer. Although all cAMP-signaling pathway cancers are driven by mutation(s) that impinge on a single signaling pathway, the ultimate tumor phenotype reflects interactions between five critical variables: (1) the precise gene(s) that undergo mutation in each specific tumor type; (2) the effects of specific allele(s) in any given gene; (3) mutations in modifier genes (mutational "context"); (4) the tissue-specific expression of various cAMP signaling pathway elements in the tumor stem cell; and (5) and the precise biochemical regulation of the pathway components in tumor cells. These varying oncogenic mechanisms reveal novel and important targets for drug discovery. There is considerable diversity in the "druggability" of cAMP-signaling components, with some elements (GPCRs, cAMP-specific phosphodiesterases and kinases) appearing to be prime drug candidates, while other elements (transcription factors, protein-protein interactions) are currently refractory to robust drug-development efforts. Further refinement of the precise driver mutations in individual tumors will be essential for directing priorities in drug discovery efforts that target these mutations.

Transcriptional Networks Identify BRPF1 as a Potential Drug Target Based on Inflammatory Signature in Primary Lower-Grade Gliomas

Gliomas are the most common tumors of the central nervous system and are classified into grades I-IV based on their histological characteristics. Lower-grade gliomas (LGG) can be divided into grade II diffuse low-grade gliomas and grade III moderate gliomas and have a relatively good prognosis. However, LGG often develops into high-grade glioma within a few years. This study aimed to construct and identify the prognostic value of an inflammatory signature and discover potential drug targets for primary LGG. We first screened differentially expressed genes in primary LGG (TCGA) compared with normal brain tissue (GTEx) that overlapped with inflammation-related genes from MSigDB. After survival analysis, nine genes were selected to construct an inflammatory signature. LGG patients with a high inflammatory signature score had a poor prognosis, and the inflammatory signature was a strong independent prognostic factor in both the training cohort (TCGA) and validation cohort (CGGA). Compared with the low-inflammatory signature group, differentially expressed genes in the high-inflammatory signature group were mainly enriched in immune-related signaling pathways, which is consistent with the distribution of immune cells in the high- and low-inflammatory signature groups. Integrating driver genes, upregulated genes and drug targets data, bromodomain and PHD finger-containing protein 1 (BRPF1) was selected as a potential drug target. Inhibition of BRPF1 function or knockdown of BRPF1 expression attenuated glioma cell proliferation and colony formation.

Determinants of anti-PD-1 response and resistance in clear cell renal cell carcinoma

ADAPTeR is a prospective, phase II study of nivolumab (anti-PD-1) in 15 treatment-naive patients (115 multiregion tumor samples) with metastatic clear cell renal cell carcinoma (ccRCC) aiming to understand the mechanism underpinning therapeutic response. Genomic analyses show no correlation between tumor molecular features and response, whereas ccRCC-specific human endogenous retrovirus expression indirectly correlates with clinical response. T cell receptor (TCR) analysis reveals a significantly higher number of expanded TCR clones pre-treatment in responders suggesting pre-existing immunity. Maintenance of highly similar clusters of TCRs post-treatment predict response, suggesting ongoing antigen engagement and survival of families of T cells likely recognizing the same antigens. In responders, nivolumab-bound CD8+ T cells are expanded and express GZMK/B. Our data suggest nivolumab drives both maintenance and replacement of previously expanded T cell clones, but only maintenance correlates with response. We hypothesize that maintenance and boosting of a pre-existing response is a key element of anti-PD-1 mode of action.

PI3K inhibitors are finally coming of age

Overactive phosphoinositide 3-kinase (PI3K) in cancer and immune dysregulation has spurred extensive efforts to develop therapeutic PI3K inhibitors. Although progress has been hampered by issues such as poor drug tolerance and drug resistance, several PI3K inhibitors have now received regulatory approval - the PI3Kα isoform-selective inhibitor alpelisib for the treatment of breast cancer and inhibitors mainly aimed at the leukocyte-enriched PI3Kδ in B cell malignancies. In addition to targeting cancer cell-intrinsic PI3K activity, emerging evidence highlights the potential of PI3K inhibitors in cancer immunotherapy. This Review summarizes key discoveries that aid the clinical translation of PI3Kα and PI3Kδ inhibitors, highlighting lessons learnt and future opportunities.

Co-occurring gain-of-function mutations in HER2 and HER3 modulate HER2/HER3 activation, oncogenesis, and HER2 inhibitor sensitivity

Activating mutations in HER2 (ERBB2) drive the growth of a subset of breast and other cancers and tend to co-occur with HER3 (ERBB3) missense mutations. The HER2 tyrosine kinase inhibitor neratinib has shown clinical activity against HER2-mutant tumors. To characterize the role of HER3 mutations in HER2-mutant tumors, we integrate computational structural modeling with biochemical and cell biological analyses. Computational modeling predicts that the frequent HER3E928G kinase domain mutation enhances the affinity of HER2/HER3 and reduces binding of HER2 to its inhibitor neratinib. Co-expression of mutant HER2/HER3 enhances HER2/HER3 co-immunoprecipitation and ligand-independent activation of HER2/HER3 and PI3K/AKT, resulting in enhanced growth, invasiveness, and resistance to HER2-targeted therapies, which can be reversed by combined treatment with PI3Kα inhibitors. Our results provide a mechanistic rationale for the evolutionary selection of co-occurring HER2/HER3 mutations and the recent clinical observations that HER3 mutations are associated with a poor response to neratinib in HER2-mutant cancers.

Mutant p53 in cell-cell interactions

In this review, Pilley et al. examine the impact of different p53 mutations and focus on how heterogeneity of p53 status can affect relationships between cells within a tumor.

p53 is an important tumor suppressor, and the complexities of p53 function in regulating cancer cell behaviour are well established. Many cancers lose or express mutant forms of p53, with evidence that the type of alteration affecting p53 may differentially impact cancer development and progression. It is also clear that in addition to cell-autonomous functions, p53 status also affects the way cancer cells interact with each other. In this review, we briefly examine the impact of different p53 mutations and focus on how heterogeneity of p53 status can affect relationships between cells within a tumor.

Targeting SHIP1 and SHIP2 in Cancer

Simple Summary

Phosphoinositol signaling pathways and their dysregulation have been shown to have a fundamental role in health and disease, respectively. The SH2-containing 5′ inositol phosphatases, SHIP1 and SHIP2, are regulators of the PI3K/AKT pathway that have crucial roles in cancer progression. This review aims to summarize the role of SHIP1 and SHIP2 in cancer signaling and the immune response to cancer, the discovery and use of SHIP inhibitors and agonists as possible cancer therapeutics.

Abstract

Membrane-anchored and soluble inositol phospholipid species are critical mediators of intracellular cell signaling cascades. Alterations in their normal production or degradation are implicated in the pathology of a number of disorders including cancer and pro-inflammatory conditions. The SH2-containing 5′ inositol phosphatases, SHIP1 and SHIP2, play a fundamental role in these processes by depleting PI(3,4,5)P₃, but also by producing PI(3,4)P₂ at the inner leaflet of the plasma membrane. With the intent of targeting SHIP1 or SHIP2 selectively, or both paralogs simultaneously, small molecule inhibitors and agonists have been developed and tested in vitro and in vivo over the last decade in various disease models. These studies have shown promising results in various pre-clinical models of disease including cancer and tumor immunotherapy. In this review the potential use of SHIP inhibitors in cancer is discussed with particular attention to the molecular structure, binding site and efficacy of these SHIP inhibitors.

Multiple mutations within individual oncogenes

Recent studies of the cancer genome have identified numerous patients harboring multiple mutations (MM) within individual oncogenes. These MM (de novo MM) in cis synergistically activate the mutated oncogene and promote tumorigenesis, indicating a positive epistatic interaction between mutations. The relatively frequent de novo MM suggest that intramolecular positive epistasis is widespread in oncogenes. Studies also suggest that negative and higher-order epistasis affects de novo MM. Comparison of de novo MM and MM associated with drug-resistant secondary mutations (secondary MM) revealed several similarities with respect to allelic configuration, mutational selection and functionality of individual mutations. Conversely, they have several differences, most notably the difference in drug sensitivities. Secondary MM usually confer resistance to molecularly targeted therapies, whereas several de novo MM are associated with increased sensitivity, implying that both can be useful as therapeutic biomarkers. Unlike secondary MM in which specific secondary resistant mutations are selected, minor (infrequent) functionally weak mutations are convergently selected in de novo MM, which may provide an explanation as to why such mutations accumulate in cancer. The third type of MM is MM from different subclones. This type of MM is associated with parallel evolution, which may contribute to relapse and treatment failure. Collectively, MM within individual oncogenes are diverse, but all types of MM are associated with cancer evolution and therapeutic response. Further evaluation of oncogenic MM is warranted to gain a deeper understanding of cancer genetics and evolution.

Discovery through clinical sequencing in oncology

The molecular characterization of tumors now informs clinical cancer care for many patients. This advent of molecular oncology is driven by the expanding number of therapeutic biomarkers that can predict sensitivity to both approved and investigational agents. Beyond its role in driving clinical trial enrollments and guiding therapy in individual patients, large-scale clinical genomics in oncology also represents a rapidly expanding research resource for translational scientific discovery. Here, we review the progress, opportunities, and challenges of scientific and translational discovery from prospective clinical genomic screening programs now routinely conducted in cancer patients.

Characterization of tumors with ultralow tumor mutational burden in Japanese cancer patients

Tumor mutational burden analysis using whole‐exome sequencing highlights features of tumors with various mutations or known driver alterations. Cancers with few changes in the exon regions have unclear characteristics, even though low‐mutated tumors are often detected in pan‐cancer analysis. In the present study, we analyzed tumors with low tumor mutational burden listed in the Japanese version of The Cancer Genome Atlas, a data set of 5020 primary solid tumors. Our analysis revealed that detection rates of known driver mutations and copy number variation were decreased in samples with tumor mutational burden below 1.0 (ultralow tumor), compared with those in samples with low tumor mutational burden (≤5 mutations/Mb). This trend was also observed in The Cancer Genome Atlas data set. In the ultralow tumor mutational burden tumors, expression analysis showed decreased TP53 inactivation and chromosomal instability. TP53 inactivation frequently correlated with PI3K/mTOR‐related gene expression, implying suppression of the PI3K/mTOR pathway in ultralow tumor mutational burden tumors. In common with mutational burden, the T cell‐inflamed gene expression profiling signature was a potential marker for prediction of an immune checkpoint inhibitor response, and some ultralow tumor mutational burden tumor populations highly expressed this signature. Our analysis focused on how these tumors could provide insight into tumors with low somatic alteration that are difficult to detect solely using whole‐exome sequencing.