Landscape and function of multiple mutations within individual oncogenes

Trans-activating mutations of the pseudokinase ERBB3

Genetic changes in the ERBB family of receptor tyrosine kinases serve as oncogenic driver events and predictive biomarkers for ERBB inhibitor drugs. ERBB3 is a pseudokinase member of the family that, although lacking a fully active kinase domain, is well known for its potent signaling activity as a heterodimeric complex with ERBB2. Previous studies have identified few transforming ERBB3 mutations while the great majority of the hundreds of different somatic ERBB3 variants observed in different cancer types remain of unknown significance. Here, we describe an unbiased functional genetics screen of the transforming potential of thousands of ERBB3 mutations in parallel. The screen based on a previously described iSCREAM (in vitro screen of activating mutations) platform, and addressing ERBB3 pseudokinase signaling in a context of ERBB3/ERBB2 heterodimers, identified 18 hit mutations. Validation experiments in Ba/F3, NIH 3T3, and MCF10A cell backgrounds demonstrated the presence of both previously known and unknown transforming ERBB3 missense mutations functioning either as single variants or in cis as a pairwise combination. Drug sensitivity assays with trastuzumab, pertuzumab and neratinib indicated actionability of the transforming ERBB3 variants.

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.

Gene-specific somatic epigenetic mosaicism of FDFT1 underlies a non-hereditary localized form of porokeratosis

Porokeratosis is a clonal keratinization disorder characterized by solitary, linearly arranged, or generally distributed multiple skin lesions. Previous studies showed that genetic alterations in MVK, PMVK, MVD, or FDPS-genes in the mevalonate pathway-cause hereditary porokeratosis, with skin lesions harboring germline and lesion-specific somatic variants on opposite alleles. Here, we identified non-hereditary porokeratosis associated with epigenetic silencing of FDFT1, another gene in the mevalonate pathway. Skin lesions of the generalized form had germline and lesion-specific somatic variants on opposite alleles in FDFT1, representing FDFT1-associated hereditary porokeratosis identified in this study. Conversely, lesions of the solitary or linearly arranged localized form had somatic bi-allelic promoter hypermethylation or mono-allelic promoter hypermethylation with somatic genetic alterations on opposite alleles in FDFT1, indicating non-hereditary porokeratosis. FDFT1 localization was uniformly diminished within the lesions, and lesion-derived keratinocytes showed cholesterol dependence for cell growth and altered expression of genes related to cell-cycle and epidermal development, confirming that lesions form by clonal expansion of FDFT1-deficient keratinocytes. In some individuals with the localized form, gene-specific promoter hypermethylation of FDFT1 was detected in morphologically normal epidermis adjacent to methylation-related lesions but not distal to these lesions, suggesting that asymptomatic somatic epigenetic mosaicism of FDFT1 predisposes certain skin areas to the disease. Finally, consistent with its genetic etiology, topical statin treatment ameliorated lesions in FDFT1-deficient porokeratosis. In conclusion, we identified bi-allelic genetic and/or epigenetic alterations of FDFT1 as a cause of porokeratosis and shed light on the pathogenesis of skin mosaicism involving clonal expansion of epigenetically altered cells.

A recurrent NTRK1 tyrosine kinase domain mutation pair is characteristic in a subset of dedifferentiated liposarcomas

INTRODUCTION

Dedifferentiated liposarcoma (DDLPS) is a common form of liposarcoma with challenging treatment modalities. Pan-TRK immunopositivity can be often observed without NTRK gene fusion in soft tissue sarcomas with myogenic differentiation. Expression and the role of NTRK in DDLPS are under-studied. We sought to identify activating mutations of the NTRK genes.

MATERIALS AND METHODS

131 DDLPS patients were selected for pan-TRK immunohistochemistry and positive cases were analyzed by Sanger sequencing for NTRK1, NTRK2 and NTRK3 genes. Functional assays were performed using a lentiviral transduction system to study the effect of NTRK variants in fibroblast, immortalized fibroblast, and dedifferentiated liposarcoma cell lines.

RESULTS

Out of the 131 DDLPS cases, 75 immunohistochemical staining positive cases, 46 were successfully Sanger sequenced. A recurrent somatic mutation pair in cis position (NGS) of the NTRK1 c.1810C>T (p.H604Y) and c.1838G>T (p.G613V) was identified in six cases (13%) that have never been reported in DDLPS. NTRK fusions were excluded in all six cases by FISH and NGS. The phospho-AKT immunopositivity among the six mutated cases suggested downstream activation of the NTRK signaling pathway. Functional assays showed no transforming effects, but resistance to first- and second-line TRK inhibitors of the p.G613V and p.H604Y variant.

CONCLUSIONS

We detected (de novo/somatic) missense mutation variants in cis position of the NTRK1 gene in a subset of DDLPS indicating modifying mutations that may contribute to tumorigenesis in a subset of DDLPS. These variants beget resistance to TRK inhibitors indicating an interesting biomarker for other studies with TRK inhibitors.

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.

Potts Hamiltonian Models and Molecular Dynamics Free Energy Simulations for Predicting the Impact of Mutations on Protein Kinase Stability

Single-point mutations in kinase proteins can affect their stability and fitness, and computational analysis of these effects can provide insights into the relationships among protein sequence, structure, and function for this enzyme family. To assess the impact of mutations on protein stability, we used a sequence-based Potts Hamiltonian model trained on a kinase family multiple-sequence alignment (MSA) to calculate the statistical energy (fitness) effects of mutations and compared these against relative folding free energies (ΔΔGs) calculated from all-atom molecular dynamics free energy perturbation (FEP) simulations in explicit solvent. The fitness effects of mutations in the Potts model (ΔEs) showed good agreement with experimental thermostability data (Pearson r = 0.68), similar to the correlation we observed with ΔΔGs predicted from structure-based relative FEP simulations. Recognizing the possible advantages of using Potts models to rapidly estimate protein stability effects of kinase mutations seen in cancer genomics data, we used the Potts statistical energy model to estimate the stability effects of 65 conservative and nonconservative mutations across three distinct kinases (Wee1, Abl1, and Cdc7) with somatic mutations reported in the Genomic Data Commons (GDC) database. The ΔEs of these mutations calculated from the Potts model are consistent with the corresponding ΔΔGs from FEP simulations (Pearson ratio of 0.72). The agreement between these methods suggests that the Potts model may be used as a sequence-based tool for high-throughput screening of mutational effects as part of a computational pipeline for predicting the stability effects of mutations. We also demonstrate how the scalability of the fitness-based Potts model calculations permits analyses that are not easily accessed using FEP simulations. To this end, we employed site-saturation mutagenesis in the Potts model in order to investigate the relative stability effects of mutations seen in different cancer evolutionary scenarios. We used this approach to analyze the effects of drug pressure in Abl kinase by contrasting the relative fitness penalties of somatic mutations seen in miscellaneous cancer types with those calculated for mutations associated with cancer drug resistance. We observed that, in contrast to somatic mutations of Abl seen in various tumors that appear to have evolved neutrally, cancer mutations that evolved under drug pressure in Abl-targeted therapies tend to preserve enzyme stability.

Direct K-Ras Inhibitors to Treat Cancers: Progress, New Insights, and Approaches to Treat Resistance

Here we discuss approaches to K-Ras inhibition and drug resistance scenarios. A breakthrough offered a covalent drug against K-RasG12C. Subsequent innovations harnessed same-allele drug combinations, as well as cotargeting K-RasG12C with a companion drug to upstream regulators or downstream kinases. However, primary, adaptive, and acquired resistance inevitably emerge. The preexisting mutation load can explain how even exceedingly rare mutations with unobservable effects can promote drug resistance, seeding growth of insensitive cell clones, and proliferation. Statistics confirm the expectation that most resistance-related mutations are in cis, pointing to the high probability of cooperative, same-allele effects. In addition to targeted Ras inhibitors and drug combinations, bifunctional molecules and innovative tri-complex inhibitors to target Ras mutants are also under development. Since the identities and potential contributions of preexisting and evolving mutations are unknown, selecting a pharmacologic combination is taxing. Collectively, our broad review outlines considerations and provides new insights into pharmacology and resistance.

Drugging the undruggable: Advances in targeting KRAS signaling in solid tumors

Cancer remains the leading cause of global mortality, prompting a paradigm shift in its treatment and outcomes with the advent of targeted therapies. Among the most prevalent mutations in RAS-driven cancers, Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations account for approximately 86% of cases worldwide, particularly in lung, pancreatic, and colon cancers, contributing to poor prognosis and reduced overall survival. Despite numerous efforts to understand the biology of KRAS mutants and their pivotal role in cancer development, the lack of well-defined drug-binding pockets has deemed KRAS an "undruggable" therapeutic target, presenting significant challenges for researchers and clinicians alike. Through significant biochemical and technological advances, the last decade has witnessed promising breakthroughs in targeted therapies for KRAS-mutated lung, colon, and pancreatic cancers, marking a critical turning point in the field. In this chapter, we provide an overview of the characteristics of KRAS mutations across various solid tumors, highlighting ongoing cutting-edge research on the immune microenvironment, the development of KRAS-driven mice models, and the recent progress in the exploration of specific KRAS mutant-targeted therapeutic approaches. By comprehensive understanding of the intricacies of KRAS signaling in solid tumors and the latest therapeutic developments, this chapter will shed light on the potential for novel therapeutic strategies to combat KRAS-driven tumors and improve patient outcomes.

Subclonal accumulation of immune escape mechanisms in microsatellite instability-high colorectal cancers

BACKGROUND

Intratumor heterogeneity (ITH) in microsatellite instability-high (MSI-H) colorectal cancer (CRC) has been poorly studied. We aimed to clarify how the ITH of MSI-H CRCs is generated in cancer evolution and how immune selective pressure affects ITH.

METHODS

We reanalyzed public whole-exome sequencing data on 246 MSI-H CRCs. In addition, we performed a multi-region analysis from 6 MSI-H CRCs. To verify the process of subclonal immune escape accumulation, a novel computational model of cancer evolution under immune pressure was developed.

RESULTS

Our analysis presented the enrichment of functional genomic alterations in antigen-presentation machinery (APM). Associative analysis of neoantigens indicated the generation of immune escape mechanisms via HLA alterations. Multiregion analysis revealed the clonal acquisition of driver mutations and subclonal accumulation of APM defects in MSI-H CRCs. Examination of variant allele frequencies demonstrated that subclonal mutations tend to be subjected to selective sweep. Computational simulations of tumour progression with the interaction of immune cells successfully verified the subclonal accumulation of immune escape mutations and suggested the efficacy of early initiation of an immune checkpoint inhibitor (ICI) -based treatment.

CONCLUSIONS

Our results demonstrate the heterogeneous acquisition of immune escape mechanisms in MSI-H CRCs by Darwinian selection, providing novel insights into ICI-based treatment strategies.

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.

A workflow to study mechanistic indicators for driver gene prediction with Moonlight

Prediction of driver genes (tumor suppressors and oncogenes) is an essential step in understanding cancer development and discovering potential novel treatments. We recently proposed Moonlight as a bioinformatics framework to predict driver genes and analyze them in a system-biology-oriented manner based on -omics integration. Moonlight uses gene expression as a primary data source and combines it with patterns related to cancer hallmarks and regulatory networks to identify oncogenic mediators. Once the oncogenic mediators are identified, it is important to include extra levels of evidence, called mechanistic indicators, to identify driver genes and to link the observed gene expression changes to the underlying alteration that promotes them. Such a mechanistic indicator could be for example a mutation in the regulatory regions for the candidate gene. Here, we developed new functionalities and released Moonlight2 to provide the user with a mutation-based mechanistic indicator as a second layer of evidence. These functionalities analyze mutations in a cancer cohort to classify them into driver and passenger mutations. Those oncogenic mediators with at least one driver mutation are retained as the final set of driver genes. We applied Moonlight2 to the basal-like breast cancer subtype, lung adenocarcinoma and thyroid carcinoma using data from The Cancer Genome Atlas. For example, in basal-like breast cancer, we found four oncogenes (COPZ2, SF3B4, KRTCAP2 and POLR2J) and nine tumor suppressor genes (KIR2DL4, KIF26B, ARL15, ARHGAP25, EMCN, GMFG, TPK1, NR5A2 and TEK) containing a driver mutation in their promoter region, possibly explaining their deregulation. Moonlight2R is available at https://github.com/ELELAB/Moonlight2R.

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.

Integrative multi-omic cancer profiling reveals DNA methylation patterns associated with therapeutic vulnerability and cell-of-origin

DNA methylation plays a critical role in establishing and maintaining cellular identity. However, it is frequently dysregulated during tumor development and is closely intertwined with other genetic alterations. Here, we leveraged multi-omic profiling of 687 tumors and matched non-involved adjacent tissues from the kidney, brain, pancreas, lung, head and neck, and endometrium to identify aberrant methylation associated with RNA and protein abundance changes and build a Pan-Cancer catalog. We uncovered lineage-specific epigenetic drivers including hypomethylated FGFR2 in endometrial cancer. We showed that hypermethylated STAT5A is associated with pervasive regulon downregulation and immune cell depletion, suggesting that epigenetic regulation of STAT5A expression constitutes a molecular switch for immunosuppression in squamous tumors. We further demonstrated that methylation subtype-enrichment information can explain cell-of-origin, intra-tumor heterogeneity, and tumor phenotypes. Overall, we identified cis-acting DNA methylation events that drive transcriptional and translational changes, shedding light on the tumor's epigenetic landscape and the role of its cell-of-origin.

The mechanisms of class 1A PI3K and Wnt/β-catenin coupled signaling in breast cancer

The class IA PI3K signaling pathway is activated by growth factor stimulation and regulates a signaling cascade that promotes diverse events including cell growth, proliferation, migration and metabolism. PI3K signaling is one of the most commonly hyperactivated pathways in breast cancer, leading to increased tumor growth and progression. PI3K hyperactivation occurs via a number of genetic and epigenetic mechanisms including mutation or amplification of PIK3CA, the gene encoding the p110α subunit of PI3Kα, as well as via dysregulation of the upstream growth factor receptors or downstream signaling effectors. Over the past decade, extensive efforts to develop therapeutics that suppress oncogenic PI3K signaling have been undertaken. Although FDA-approved PI3K inhibitors are now emerging, their clinical success remains limited due to adverse effects and negative feedback mechanisms which contribute to their reduced efficacy. There is an emerging body of evidence demonstrating crosstalk between the PI3K and Wnt/β-catenin pathways in breast cancer. However, PI3K exhibits opposing effects on Wnt/β-catenin signaling in distinct tumor subsets, whereby PI3K promotes Wnt/β-catenin activation in ER+ cancers, but paradoxically suppresses this pathway in ER- breast cancers. This review discusses the molecular mechanisms for PI3K-Wnt crosstalk in breast cancer, and how Wnt-targeted therapies have the potential to contribute to treatment regimens for breast cancers with PI3K dysregulation.

Inter- and intra-tumor heterogeneity of genetic and immune profiles in inherited renal cell carcinoma

Patients with von Hippel-Lindau disease (vHL) are at risk of developing spatially and temporally multiple clear cell renal cell carcinomas (ccRCCs), which offers a valuable opportunity to analyze inter- and intra-tumor heterogeneity of genetic and immune profiles within the same patient. Here, we perform whole-exome and RNA sequencing, digital gene expression, and immunohistochemical analyses for 81 samples from 51 ccRCCs of 10 patients with vHL. Inherited ccRCCs are clonally independent and have less genomic alterations than sporadic ccRCCs. Hierarchical clustering of transcriptome profiles shows two clusters with distinct immune signatures: immune hot and cold clusters. Interestingly, not only samples from the same tumors but also different tumors from the same patients tend to show a similar immune signature, whereas samples from different patients frequently exhibit different signatures. Our findings reveal the genetic and immune landscape of inherited ccRCCs, demonstrating the relevance of host factors in shaping anti-tumor immunity.

Cancer driver mutations: predictions and reality

Cancer cells accumulate many genetic alterations throughout their lifetime, but only a few of them drive cancer progression, termed driver mutations. Driver mutations may vary between cancer types and patients, can remain latent for a long time and become drivers at particular cancer stages, or may drive oncogenesis only in conjunction with other mutations. The high mutational, biochemical, and histological tumor heterogeneity makes driver mutation identification very challenging. In this review we summarize recent efforts to identify driver mutations in cancer and annotate their effects. We underline the success of computational methods to predict driver mutations in finding novel cancer biomarkers, including in circulating tumor DNA (ctDNA). We also report on the boundaries of their applicability in clinical research.

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.

Oncogenic RAS promotes leukemic transformation of CUX1-deficient cells

-7/del(7q) is prevalent across subtypes of myeloid neoplasms. CUX1, located on 7q22, encodes a homeodomain-containing transcription factor, and, like -7/del(7q), CUX1 inactivating mutations independently carry a poor prognosis. As with loss of 7q, CUX1 mutations often occur early in disease pathogenesis. We reported that CUX1 deficiency causes myelodysplastic syndrome in mice but was insufficient to drive acute myeloid leukemia (AML). Given the known association between -7/del(7q) and RAS pathway mutations, we mined cancer genome databases and explicitly linked CUX1 mutations with oncogenic RAS mutations. To determine if activated RAS and CUX1 deficiency promote leukemogenesis, we generated mice bearing NrasG12D and CUX1-knockdown which developed AML, not seen in mice with either mutation alone. Oncogenic RAS imparts increased self-renewal on CUX1-deficient hematopoietic stem/progenitor cells (HSPCs). Reciprocally, CUX1 knockdown amplifies RAS signaling through reduction of negative regulators of RAS/PI3K signaling. Double mutant HSPCs were responsive to PIK3 or MEK inhibition. Similarly, low expression of CUX1 in primary AML samples correlates with sensitivity to the same inhibitors, suggesting a potential therapy for malignancies with CUX1 inactivation. This work demonstrates an unexpected convergence of an oncogene and tumor suppressor gene on the same pathway.

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.

Microbiota-Liver Diseases Interactions

Gut microbiota regulates essential processes of host metabolism and physiology: synthesis of vitamins, digestion of foods non-digestible by the host (such as fibers), and-most important-protects the digestive tract from pathogens. In this study, we focus on the CRISPR/Cas9 technology, which is extensively used to correct multiple diseases, including liver diseases. Then, we discuss the non-alcoholic fatty liver disease (NAFLD), affecting more than 25% of the global population; colorectal cancer (CRC) is second in mortality. We give space to rarely discussed topics, such as pathobionts and multiple mutations. Pathobionts help to understand the origin and complexity of the microbiota. Since several types of cancers have as target the gut, it is vital extending the research of multiple mutations to the type of cancers affecting the gut-liver axis.

Spatial genomic diversity associated with APOBEC mutagenesis in squamous cell carcinoma arising from ovarian teratoma

Although the gross and microscopic features of squamous cell carcinoma arising from ovarian mature cystic teratoma (MCT-SCC) vary from case to case, the spatial spreading of genomic alterations within the tumor remains unclear. To clarify the spatial genomic diversity in MCT-SCCs, we performed whole-exome sequencing by collecting 16 samples from histologically different parts of two MCT-SCCs. Both cases showed histological diversity within the tumors (case 1: nonkeratinizing and keratinizing SCC and case 2: nonkeratinizing SCC and anaplastic carcinoma) and had different somatic mutation profiles by histological findings. Mutation signature analysis revealed a significantly enriched apolipoprotein B mRNA editing enzyme catalytic subunit (APOBEC) signature at all sites. Intriguingly, the spread of genomic alterations within the tumor and the clonal evolution patterns from nonmalignant epithelium to cancer sites differed between cases. TP53 mutation and copy number alterations were widespread at all sites, including the nonmalignant epithelium, in case 1. Keratinizing and nonkeratinizing SCCs were differentiated by the occurrence of unique somatic mutations from a common ancestral clone. In contrast, the nonmalignant epithelium showed almost no somatic mutations in case 2. TP53 mutation and the copy number alteration similarities were observed only in nonkeratinizing SCC samples. Nonkeratinizing SCC and anaplastic carcinoma shared almost no somatic mutations, suggesting that each locally and independently arose in the MCT. We demonstrated that two MCT-SCCs with different histologic findings were highly heterogeneous tumors with clearly different clones associated with APOBEC-mediated mutagenesis, suggesting the importance of evaluating intratumor histological and genetic heterogeneity among multiple sites of MCT-SCC.

Comprehensive analysis of nicotinamide metabolism-related signature for predicting prognosis and immunotherapy response in breast cancer

Background

Breast cancer (BC) is the most common malignancy among women. Nicotinamide (NAM) metabolism regulates the development of multiple tumors. Herein, we sought to develop a NAM metabolism-related signature (NMRS) to make predictions of survival, tumor microenvironment (TME) and treatment efficacy in BC patients.

Methods

Transcriptional profiles and clinical data from The Cancer Genome Atlas (TCGA) were analyzed. NAM metabolism-related genes (NMRGs) were retrieved from the Molecular Signatures Database. Consensus clustering was performed on the NMRGs and the differentially expressed genes between different clusters were identified. Univariate Cox, Lasso, and multivariate Cox regression analyses were sequentially conducted to develop the NAM metabolism-related signature (NMRS), which was then validated in the International Cancer Genome Consortium (ICGC) database and Gene Expression Omnibus (GEO) single-cell RNA-seq data. Further studies, such as gene set enrichment analysis (GSEA), ESTIMATE, CIBERSORT, SubMap, and Immunophenoscore (IPS) algorithm, cancer-immunity cycle (CIC), tumor mutation burden (TMB), and drug sensitivity were performed to assess the TME and treatment response.

Results

We identified a 6-gene NMRS that was significantly associated with BC prognosis as an independent indicator. We performed risk stratification according to the NMRS and the low-risk group showed preferable clinical outcomes (P < 0.001). A comprehensive nomogram was developed and showed excellent predictive value for prognosis. GSEA demonstrated that the low-risk group was predominantly enriched in immune-associated pathways, whereas the high-risk group was enriched in cancer-related pathways. The ESTIMATE and CIBERSORT algorithms revealed that the low-risk group had a higher abundance of anti-tumor immunocyte infiltration (P < 0.05). Results of Submap, IPS, CIC, TMB, and external immunotherapy cohort (iMvigor210) analyses showed that the low-risk group were indicative of better immunotherapy response (P < 0.05).

Conclusions

The novel signature offers a promising way to evaluate the prognosis and treatment efficacy in BC patients, which may facilitate clinical practice and management.

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.

A New View of Activating Mutations in Cancer

A vast effort has been invested in the identification of driver mutations of cancer. However, recent studies and observations call into question whether the activating mutations or the signal strength are the major determinant of tumor development. The data argue that signal strength determines cell fate, not the mutation that initiated it. In addition to activating mutations, factors that can impact signaling strength include (i) homeostatic mechanisms that can block or enhance the signal, (ii) the types and locations of additional mutations, and (iii) the expression levels of specific isoforms of genes and regulators of proteins in the pathway. Because signal levels are largely decided by chromatin structure, they vary across cell types, states, and time windows. A strong activating mutation can be restricted by low expression, whereas a weaker mutation can be strengthened by high expression. Strong signals can be associated with cell proliferation, but too strong a signal may result in oncogene-induced senescence. Beyond cancer, moderate signal strength in embryonic neural cells may be associated with neurodevelopmental disorders, and moderate signals in aging may be associated with neurodegenerative diseases, like Alzheimer's disease. The challenge for improving patient outcomes therefore lies in determining signaling thresholds and predicting signal strength.

Molecular Subclasses of Clear Cell Ovarian Carcinoma and Their Impact on Disease Behavior and Outcomes

PURPOSE

To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes.

EXPERIMENTAL DESIGN

We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival.

RESULTS

We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy.

CONCLUSIONS

Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838.

C-CAT: The National Datacenter for Cancer Genomic Medicine in Japan

SUMMARY

Since June 2019, under the umbrella of the national health insurance system, Japan has started cancer genomic medicine (CGM) with comprehensive genomic profiling (CGP) tests. The Ministry of Health, Labour and Welfare (MHLW) of Japan constructed a network of CGM hospitals (a total of 233 institutes as of July 1, 2022) and established the Center for Cancer Genomics and Advanced Therapeutics (C-CAT), the national datacenter for CGM. Clinical information and genomic data from the CGP tests are securely transferred to C-CAT, which then generates "C-CAT Findings" reports containing information of clinical annotation and matched clinical trials based on the CGP data. As of June 30, 2022, a total of 36,340 datapoints of clinical/genomic information are aggregated in C-CAT, and the number is expected to increase swiftly. The data are now open for sharing with not only the CGM hospitals but also other academic institutions and industries.

Overview and clinical significance of multiple mutations in individual genes in hepatocellular carcinoma

Background

Multiple mutation (MM) within a single gene has recently been reported as a mechanism involved in carcinogenesis. The present study investigated the clinical significance of MMs in hepatocellular carcinoma (HCC).

Methods

Two hundred twenty-three surgically resected HCCs were subjected to gene expression profiling and whole-exome sequencing.

Results

MMs in individual genes were detected in 178 samples (MM tumors: 79.8%). The remaining samples all carried a single mutation (SM tumors: 20.2%). Recurrence-free survival in the MM group was significantly worse in comparison to the SM group (P = 0.012). A Cox proportional hazard analysis revealed that MM tumor was an independent predictor for worse a prognosis (hazard ratio, 1.72; 95% confidence interval, 1.01–3.17; P = 0.045). MMs were frequently observed across in various genes, especially MUC16 (15% of samples had at least one mutation in the gene) and CTNNB1 (14%). Although the MUC16 mRNA expression of MUC16 wild-type and MUC16 SM tumors did not differ to a statistically significant extent, the expression in MUC16 MM tumors was significantly enhanced in comparison to MUC16 SM tumors (P < 0.001). In MUC16, MMs were associated with viral hepatitis, higher tumor marker levels and vascular invasion. The MUC16 MMs group showed significantly worse recurrence-free survival in comparison to the MUC16 SM group (P = 0.022), while no significant difference was observed between the MUC16 SM group and the MUC16 wild-type group (P = 0.324).

Conclusions

MM was a relatively common event that may occur selectively in specific oncogenes and is involved in aggressive malignant behavior.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10143-z.

Allostery: Allosteric Cancer Drivers and Innovative Allosteric Drugs

Here, we discuss the principles of allosteric activating mutations, propagation downstream of the signals that they prompt, and allosteric drugs, with examples from the Ras signaling network. We focus on Abl kinase where mutations shift the landscape toward the active, imatinib binding-incompetent conformation, likely resulting in the high affinity ATP outcompeting drug binding. Recent pharmacological innovation extends to allosteric inhibitor (GNF-5)-linked PROTAC, targeting Bcr-Abl1 myristoylation site, and broadly, allosteric heterobifunctional degraders that destroy targets, rather than inhibiting them. Designed chemical linkers in bifunctional degraders can connect the allosteric ligand that binds the target protein and the E3 ubiquitin ligase warhead anchor. The physical properties and favored conformational state of the engineered linker can precisely coordinate the distance and orientation between the target and the recruited E3. Allosteric PROTACs, noncompetitive molecular glues, and bitopic ligands, with covalent links of allosteric ligands and orthosteric warheads, increase the effective local concentration of productively oriented and placed ligands. Through covalent chemical or peptide linkers, allosteric drugs can collaborate with competitive drugs, degrader anchors, or other molecules of choice, driving innovative drug discovery.

Haplotype phasing of a bipolar disorder pedigree revealed rare multiple mutations of SPOCD1 gene in the 1p36-35 susceptibility locus

BACKGROUND

The etiology of bipolar disorder (BD) is poorly understood. Considering the complexity of BD, pedigree-based sequencing studies focusing on haplotypes at specific loci may be practical to discover high-impact risk variants. This study comprehensively examined the haplotype sequence at 1p36-35 BD and recurrent depressive disorder (RDD) susceptibility loci.

METHODS

We surveyed BD families in Okinawa, Japan. We performed linkage analysis and determined the phased sequence of the affected haplotype using whole genome sequencing. We filtered rare missense variants on the haplotype. For validation, we conducted a case-control genetic association study on approximately 3000 Japanese subjects.

RESULTS

We identified a three-generation multiplex pedigree with BD and RDD. Strikingly, we identified a significant linkage with mood disorders (logarithm of odds [LOD] = 3.61) at 1p36-35, supported in other ancestry studies. Finally, we determined the entire sequence of the 6.4-Mb haplotype shared by all affected subjects. Moreover, we found a rare triplet of missense variants in the SPOCD1 gene on the haplotype. Notably, despite the rare frequency, one heterozygote with multiple SPOCD1 variants was identified in an independent set of 88 BD type I genotyping samples.

LIMITATIONS

The 1p36-35 sequence was obtained from only a single pedigree. The replicate sample was small. Short-read sequencing might miss structural variants. A polygenic risk score was not analyzed.

CONCLUSION

The 1p36-35 haplotype sequence may be valuable for future BD variant studies. In particular, SPOCD1 is a promising candidate gene and should be validated.

CD8+ T cell trajectory subtypes decode tumor heterogeneity and provide treatment recommendations for hepatocellular carcinoma

Introduction

Mounting evidence has revealed that the interactions and dynamic alterations among immune cells are critical in shaping the tumor microenvironment and ultimately map onto heterogeneous clinical outcomes. Currently, the underlying clinical significance of immune cell evolutions remains largely unexplored in hepatocellular carcinoma (HCC).

Methods

A total of 3,817 immune cells and 1,750 HCC patients of 15 independent public datasets were retrieved. The Seurat and Monocle algorithms were used to depict T cell evolution, and nonnegative matrix factorization (NMF) was further applied to identify the molecular classification. Subsequently, the prognosis, biological characteristics, genomic variations, and immune landscape among distinct clusters were decoded. The clinical efficacy of multiple treatment approaches was further investigated.

Results

According to trajectory gene expression, three heterogeneous clusters with different clinical outcomes were identified. C2, with a more advanced pathological stage, presented the most dismal prognosis relative to C1 and C3. Eight independent external cohorts validated the robustness and reproducibility of the three clusters. Further explorations elucidated C1 to be characterized as lipid metabolic HCC, and C2 was referred to as cell-proliferative HCC, whereas C3 was defined as immune inflammatory HCC. Moreover, C2 also displayed the most conspicuous genomic instability, and C3 was deemed as “immune-hot”, having abundant immune cells and an elevated expression of immune checkpoints. The assessments of therapeutic intervention suggested that patients in C1 were suitable for transcatheter arterial chemoembolization treatment, and patients in C2 were sensitive to tyrosine kinase inhibitors, while patients in C3 were more responsive to immunotherapy. We also identified numerous underlying therapeutic agents, which might be conducive to clinical transformation in the future.

Conclusions

Our study developed three clusters with distinct characteristics based on immune cell evolutions. For specifically stratified patients, we proposed individualized treatment strategies to improve the clinical outcomes and facilitate the clinical management.

A 2-tier subdivision of papillary proliferations of the endometrium (PPE) only emphasizing the complexity of papillae precisely predicts the neoplastic risk and reflects the neoplasia-related molecular characteristics-a single-centered analysis of 207 cases

Papillary proliferation of the endometrium (PPE) is subdivided based on the complexity of the papillae and the proliferation of lesions, and the complex group is considered to have an increased risk of concurrent/subsequent endometrial neoplasia. However, the current subdivision criteria fail to prove the equivalence of the quantity of simple papillae and structural complexity. In this study, we divided PPE of 207 cases from 2014 to 2022 into 3 groups according to structural complexity and proliferation degrees: Group 1 equaled to the simple PPE with a simple papillary structure and typical localized proliferation; group 2 had the simple structure similar to group 1 but occupy over 50% of the endometrial polyp or > 2 lesions in the surface of nonpolypoid endometrium; group 3 had the truly complex branching papillae despite of its proportion. Group 3 was implicated with significantly more concurrent endometrial neoplasia (EAH and carcinoma) compared with groups 1 and 2 (P < 0.01), while no difference was found between groups 1 and 2. In 128 cases with no concurrent endometrial abnormalities in the initial biopsy or curettage specimens, 4 cases presented endometrial neoplasia (3 carcinoma and 1 atypical hyperplasia) in the subsequent specimens, all of which presented PPE of group 3 but not group 1 or 2 in the prior tissues (P < 0.01). The immunochemistry of 83 cases showed similar expressions of ER, PTEN, ARID1A, PTEN, p16, β-catenin, and p53 between PPE and the surrounding normal endometrium. Nearly 100% of PPE cases lost expressions of PR. A total of 2/83 cases showing PAX2 expression were all in the group 3 and correlated with endometrial neoplasia (2/17, 11.76%, P < 0.05). 76/83 (91.57%) of PPE lesions had KRAS mutations, and the distributions of which were similar among 3 groups. The frequency of mucinous metaplasia was significantly higher in the PPE lesions with KRAS mutations (72/74, 97.30%, P < 0.01). Group 3 showed higher frequency of single KRAS mutations compared with the combination of groups 1 and 2 (P < 0.01). Finally, the concordance of KRAS mutation profiles between PPE and endometrial neoplasia was significantly higher in group 3 than either group 1 or 2 (P < 0.01), while no difference was found between group 1 and 2. Thus, a new 2-tier subdivision system only emphasizing the complexity of papillae is recommended, which might precisely predict the risk of endometrial neoplasia and neoplasia-related molecular characteristics.

At a crossroads: how to translate the roles of PI3K in oncogenic and metabolic signalling into improvements in cancer therapy

Numerous agents targeting various phosphatidylinositol 3-kinase (PI3K) pathway components, including PI3K, AKT and mTOR, have been tested in oncology clinical trials, resulting in regulatory approvals for the treatment of selected patients with breast cancer, certain other solid tumours or particular haematological malignancies. However, given the prominence of PI3K signalling in cancer and the crucial role of this pathway in linking cancer growth with metabolism, these clinical results could arguably be improved upon. In this Review, we discuss past and present efforts to overcome the somewhat limited clinical efficacy of PI3Kα pathway inhibitors, including optimization of inhibitor specificity, patient selection and biomarkers across cancer types, with a focus on breast cancer, as well as identification and abrogation of signalling-related and metabolic mechanisms of resistance, and interventions to improve management of prohibitive adverse events. We highlight the advantages and limitations of laboratory-based model systems used to study the PI3K pathway, and propose technologies and experimental inquiries to guide the future clinical deployment of PI3K pathway inhibitors in the treatment of cancer.

PIK3CA mutations-mediated downregulation of circLHFPL2 inhibits colorectal cancer progression via upregulating PTEN

BACKGROUND

PIK3CA mutation and PTEN suppression lead to tumorigenesis and drug resistance in colorectal cancer (CRC). There is no research on the role of circular RNAs (circRNAs) in regulating PIK3CA mutation and MEK inhibitor resistance in CRC.

METHODS

The expression of circLHFPL2 in PIK3CA-mutant and wild-type cells and tissues was quantified by RNA-sequencing and qRT-PCR. CCK-8 assay and colony formation assay were used to evaluate cell viability. Annexin V/PI staining was implemented to assess cell apoptosis. Luciferase assay, biotin-coupled microRNA capture, and RIP assay were used to validate the interaction among potential targets. Western blotting and qRT-PCR assays were used to evaluate the expression of involved targets. Xenograft tumor in a nude mouse model was used to explore the role of circRNAs in vivo.

RESULTS

RNA sequencing defined downregulated expression of circLHFPL2 in both PIK3CA^H1047R (HCT116) and PIK3CA^E545K (DLD1) cells. CircLHFPL2 was also downregulated in PIK3CA-mutant CRC primary cells and tissues, which was correlated with poor prognosis. CircLHFPL2 was mainly localized in the cytoplasm and its downregulation was attributed to the PI3K/AKT signaling pathway activated by phosphorylating Foxo3a. CircLHFPL2 inhibited PI3KCA-Mut CRC progression both in vitro and in vivo. Furthermore, our work indicated that circLHFPL2 acts as a ceRNA to sponge miR-556-5p and miR-1322 in CRC cells and in turn modulate the expression of PTEN. Importantly, circLHFPL2 was able to overcome PIK3CA-mediated MEK inhibitor resistance in CRC cells.

CONCLUSIONS

Downregulation of circLHFPL2 sustains the activation of the PI3K/AKT signaling pathway via a positive feedback loop in PIK3CA-mutant CRC. In addition, downregulation of circLHFPL2 leads to MEK inhibitor resistance in CRC. Therefore, targeting circLHFPL2 could be an effective approach for the treatment of CRC patients harboring oncogenic PIK3CA mutations.

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.

Allostery, and how to define and measure signal transduction

Here we ask: What is productive signaling? How to define it, how to measure it, and most of all, what are the parameters that determine it? Further, what determines the strength of signaling from an upstream to a downstream node in a specific cell? These questions have either not been considered or not entirely resolved. The requirements for the signal to propagate downstream to activate (repress) transcription have not been considered either. Yet, the questions are pivotal to clarify, especially in diseases such as cancer where determination of signal propagation can point to cell proliferation and to emerging drug resistance, and to neurodevelopmental disorders, such as RASopathy, autism, attention-deficit/hyperactivity disorder (ADHD), and cerebral palsy. Here we propose a framework for signal transduction from an upstream to a downstream node addressing these questions. Defining cellular processes, experimentally measuring them, and devising powerful computational AI-powered algorithms that exploit the measurements, are essential for quantitative science.

Intertumor and intratumor heterogeneity of PIK3CA mutations in extramammary Paget's disease

Although the prognosis of patients with extramammary Paget's disease (EMPD) treated with radical resection is good, the prognosis of EMPD with distant metastasis is very poor. PIK3CA mutations predict a good response to PIK3CA inhibitors. The aim of this study was to investigate the occurrence rate of PIK3CA mutations (including multiple mutations [MM]) related to the intertumor and intratumor heterogeneity in EMPD and to evaluate the correlation between these mutations and clinical parameters of EMPD. We performed droplet digital polymerase chain reaction to detect PIK3CA mutations (E542K, E545K, H1047R, and MM) in 68 patients with EMPD. In addition, we investigated the presence of PIK3CA mutations at multiple sites in 16 patients with PIK3CA mutations to assess the intratumor heterogeneity of PIK3CA mutations in EMPD. The frequency of one or more PIK3CA mutations in patients with EMPD was 30.8% (21/68). The frequency of E542K, E545K, H1047R, and MM were 10.2% (7/68), 13.2% (9/68), 11.7% (8/68), and 4.4% (3/68), respectively. No significant correlation was found between PIK3CA mutation patterns and clinical parameters. Of the 21 patients with PIK3CA mutations, 16 with tissue samples that could be analyzed at multiple sites were examined. The proportion of patients with the same PIK3CA mutations at all sites was 12.5% (2/16). The proportion of patients with the same PIK3CA mutations at least two or more sites, but not at all sites, was 31.2% (5/16). The proportion of patients with no PIK3CA mutations at other sites was 37.5% (6/16). The proportion of patients with other PIK3CA mutations at other sites was 18.7% (3/16). There is intertumor and intratumor heterogeneity of PIK3CA mutations. PIK3CA mutations in EMPD may be progressor mutations in EMPD.

Comparative assessment of genes driving cancer and somatic evolution in non-cancer tissues: an update of the Network of Cancer Genes (NCG) resource

Background

Genetic alterations of somatic cells can drive non-malignant clone formation and promote cancer initiation. However, the link between these processes remains unclear and hampers our understanding of tissue homeostasis and cancer development.

Results

Here, we collect a literature-based repertoire of 3355 well-known or predicted drivers of cancer and non-cancer somatic evolution in 122 cancer types and 12 non-cancer tissues. Mapping the alterations of these genes in 7953 pan-cancer samples reveals that, despite the large size, the known compendium of drivers is still incomplete and biased towards frequently occurring coding mutations. High overlap exists between drivers of cancer and non-cancer somatic evolution, although significant differences emerge in their recurrence. We confirm and expand the unique properties of drivers and identify a core of evolutionarily conserved and essential genes whose germline variation is strongly counter-selected. Somatic alteration in even one of these genes is sufficient to drive clonal expansion but not malignant transformation.

Conclusions

Our study offers a comprehensive overview of our current understanding of the genetic events initiating clone expansion and cancer revealing significant gaps and biases that still need to be addressed. The compendium of cancer and non-cancer somatic drivers, their literature support, and properties are accessible in the Network of Cancer Genes and Healthy Drivers resource at http://www.network-cancer-genes.org/.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02607-z.

An Unbiased Functional Genetics Screen Identifies Rare Activating ERBB4 Mutations

Despite the relatively high frequency of somatic ERBB4 mutations in various cancer types, only a few activating ERBB4 mutations have been characterized, primarily due to lack of mutational hotspots in the ERBB4 gene. Here, we utilized our previously published pipeline, an in vitro screen for activating mutations, to perform an unbiased functional screen to identify potential activating ERBB4 mutations from a randomly mutated ERBB4 expression library. Ten potentially activating ERBB4 mutations were identified and subjected to validation by functional and structural analyses. Two of the 10 ERBB4 mutants, E715K and R687K, demonstrated hyperactivity in all tested cell models and promoted cellular growth under two-dimensional and three-dimensional culture conditions. ERBB4 E715K also promoted tumor growth in in vivo Ba/F3 cell mouse allografts. Importantly, all tested ERBB4 mutants were sensitive to the pan-ERBB tyrosine kinase inhibitors afatinib, neratinib, and dacomitinib. Our data indicate that rare ERBB4 mutations are potential candidates for ERBB4-targeted therapy with pan-ERBB inhibitors.

STATEMENT OF SIGNIFICANCE

ERBB4 is a member of the ERBB family of oncogenes that is frequently mutated in different cancer types but the functional impact of its somatic mutations remains unknown. Here, we have analyzed the function of over 8,000 randomly mutated ERBB4 variants in an unbiased functional genetics screen. The data indicate the presence of rare activating ERBB4 mutations in cancer, with potential to be targeted with clinically approved pan-ERBB inhibitors.

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.

Higher order genetic interactions switch cancer genes from two-hit to one-hit drivers

The classic two-hit model posits that both alleles of a tumor suppressor gene (TSG) must be inactivated to cause cancer. In contrast, for some oncogenes and haploinsufficient TSGs, a single genetic alteration can suffice to increase tumor fitness. Here, by quantifying the interactions between mutations and copy number alterations (CNAs) across 10,000 tumors, we show that many cancer genes actually switch between acting as one-hit or two-hit drivers. Third order genetic interactions identify the causes of some of these switches in dominance and dosage sensitivity as mutations in other genes in the same biological pathway. The correct genetic model for a gene thus depends on the other mutations in a genome, with a second hit in the same gene or an alteration in a different gene in the same pathway sometimes representing alternative evolutionary paths to cancer.

Anticancer drug resistance: An update and perspective

Driver mutations promote initiation and progression of cancer. Pharmacological treatment can inhibit the action of the mutant protein; however, drug resistance almost invariably emerges. Multiple studies revealed that cancer drug resistance is based upon a plethora of distinct mechanisms. Drug resistance mutations can occur in the same protein or in different proteins; as well as in the same pathway or in parallel pathways, bypassing the intercepted signaling. The dilemma that the clinical oncologist is facing is that not all the genomic alterations as well as alterations in the tumor microenvironment that facilitate cancer cell proliferation are known, and neither are the alterations that are likely to promote metastasis. For example, the common KRasG12C driver mutation emerges in different cancers. Most occur in NSCLC, but some occur, albeit to a lower extent, in colorectal cancer and pancreatic ductal carcinoma. The responses to KRasG12C inhibitors are variable and fall into three categories, (i) new point mutations in KRas, or multiple copies of KRAS G12C which lead to higher expression level of the mutant protein; (ii) mutations in genes other than KRAS; (iii) original cancer transitioning to other cancer(s). Resistance to adagrasib, an experimental antitumor agent exerting its cytotoxic effect as a covalent inhibitor of the G12C KRas, indicated that half of the cases present multiple KRas mutations as well as allele amplification. Redundant or parallel pathways included MET amplification; emerging driver mutations in NRAS, BRAF, MAP2K1, and RET; gene fusion events in ALK, RET, BRAF, RAF1, and FGFR3; and loss-of-function mutations in NF1 and PTEN tumor suppressors. In the current review we discuss the molecular mechanisms underlying drug resistance while focusing on those emerging to common targeted cancer drivers. We also address questions of why cancers with a common driver mutation are unlikely to evolve a common drug resistance mechanism, and whether one can predict the likely mechanisms that the tumor cell may develop. These vastly important and tantalizing questions in drug discovery, and broadly in precision medicine, are the focus of our present review. We end with our perspective, which calls for target combinations to be selected and prioritized with the help of the emerging massive compute power which enables artificial intelligence, and the increased gathering of data to overcome its insatiable needs.

Positive correlation between transcriptomic stemness and PI3K/AKT/mTOR signaling scores in breast cancer, and a counterintuitive relationship with PIK3CA genotype

A PI3Kα-selective inhibitor has recently been approved for use in breast tumors harboring mutations in PIK3CA, the gene encoding p110α. Preclinical studies have suggested that the PI3K/AKT/mTOR signaling pathway influences stemness, a dedifferentiation-related cellular phenotype associated with aggressive cancer. However, to date, no direct evidence for such a correlation has been demonstrated in human tumors. In two independent human breast cancer cohorts, encompassing nearly 3,000 tumor samples, transcriptional footprint-based analysis uncovered a positive linear association between transcriptionally-inferred PI3K/AKT/mTOR signaling scores and stemness scores. Unexpectedly, stratification of tumors according to PIK3CA genotype revealed a "biphasic" relationship of mutant PIK3CA allele dosage with these scores. Relative to tumor samples without PIK3CA mutations, the presence of a single copy of a hotspot PIK3CA variant was associated with lower PI3K/AKT/mTOR signaling and stemness scores, whereas the presence of multiple copies of PIK3CA hotspot mutations correlated with higher PI3K/AKT/mTOR signaling and stemness scores. This observation was recapitulated in a human cell model of heterozygous and homozygous PIK3CAH1047R expression. Collectively, our analysis (1) provides evidence for a signaling strength-dependent PI3K-stemness relationship in human breast cancer; (2) supports evaluation of the potential benefit of patient stratification based on a combination of conventional PI3K pathway genetic information with transcriptomic indices of PI3K signaling activation.

Mechanism of activation and the rewired network: New drug design concepts

Precision oncology benefits from effective early phase drug discovery decisions. Recently, drugging inactive protein conformations has shown impressive successes, raising the cardinal questions of which targets can profit and what are the principles of the active/inactive protein pharmacology. Cancer driver mutations have been established to mimic the protein activation mechanism. We suggest that the decision whether to target an inactive (or active) conformation should largely rest on the protein mechanism of activation. We next discuss the recent identification of double (multiple) same-allele driver mutations and their impact on cell proliferation and suggest that like single driver mutations, double drivers also mimic the mechanism of activation. We further suggest that the structural perturbations of double (multiple) in cis mutations may reveal new surfaces/pockets for drug design. Finally, we underscore the preeminent role of the cellular network which is deregulated in cancer. Our structure-based review and outlook updates the traditional Mechanism of Action, informs decisions, and calls attention to the intrinsic activation mechanism of the target protein and the rewired tumor-specific network, ushering innovative considerations in precision medicine.

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.

The SCF Complex Is Essential to Maintain Genome and Chromosome Stability

The SKP1, CUL1, F-box protein (SCF) complex encompasses a group of 69 SCF E3 ubiquitin ligase complexes that primarily modify protein substrates with poly-ubiquitin chains to target them for proteasomal degradation. These SCF complexes are distinguishable by variable F-box proteins, which determine substrate specificity. Although the function(s) of each individual SCF complex remain largely unknown, those that have been characterized regulate a wide array of cellular processes, including gene transcription and the cell cycle. In this regard, the SCF complex regulates transcription factors that modulate cell signaling and ensures timely degradation of primary cell cycle regulators for accurate replication and segregation of genetic material. SCF complex members are aberrantly expressed in a myriad of cancer types, with altered expression or function of the invariable core SCF components expected to have a greater impact on cancer pathogenesis than that of the F-box proteins. Accordingly, this review describes the normal roles that various SCF complexes have in maintaining genome stability before discussing the impact that aberrant SCF complex expression and/or function have on cancer pathogenesis. Further characterization of the SCF complex functions is essential to identify and develop therapeutic approaches to exploit aberrant SCF complex expression and function.

Comprehensive functional evaluation of variants of fibroblast growth factor receptor genes in cancer

Various genetic alterations of the fibroblast growth factor receptor (FGFR) family have been detected across a wide range of cancers. However, inhibition of FGFR signaling by kinase inhibitors demonstrated limited clinical effectiveness. Herein, we evaluated the transforming activity and sensitivity of 160 nonsynonymous FGFR mutations and ten fusion genes to seven FGFR tyrosine kinase inhibitors (TKI) using the mixed-all-nominated-in-one (MANO) method, a high-throughput functional assay. The oncogenicity of 71 mutants was newly discovered in this study. The FGFR TKIs showed anti-proliferative activities against the wild-type FGFRs and their fusions, while several hotspot mutants were relatively resistant to those TKIs. The drug sensitivities assessed with the MANO method were well concordant with those evaluated using in vitro and in vivo assays. Comprehensive analysis of published FGFR structures revealed a possible mechanism through which oncogenic FGFR mutations reduce sensitivity to TKIs. It was further revealed that recurrent compound mutations within FGFRs affect the transforming potential and TKI-sensitivity of corresponding kinases. In conclusion, our study suggests the importance of selecting suitable inhibitors against individual FGFR variants. Moreover, it reveals the necessity to develop next-generation FGFR inhibitors, which are effective against all oncogenic FGFR variants.

FSCN1 Promotes Radiation Resistance in Patients With PIK3CA Gene Alteration

Radiotherapy is one of the standard treatments for cervical cancer and head and neck cancer. However, the clinical efficacy of this treatment is limited by radioresistance. The discovery of effective prognostic biomarkers and the identification of new therapeutic targets have helped to overcome the problem of radioresistance. In this study, we show that in the context of PIK3CA mutation or amplification, high expression of fascin actin-bundling protein 1 (FSCN1) (using the median as the cut-off value) is associated with poor prognosis and radiotherapy response in cancer patients. Silencing FSCN1 enhances radiosensitivity and promotes apoptosis in cancer cells with PIK3CA alterations, and this process may be associated with the downregulation of YWHAZ. These results reveal that FSCN1 may be a key regulator of radioresistance and could be a potential target for improving radiotherapy efficacy in cervical cancer and head and neck cancer patients with PIK3CA alterations.