Heterogeneity Of Mutations Research Articles

Low TP53 variant allele frequency as a biomarker for anti-programmed death (ligand) 1 monotherapy in lung adenocarcinoma.

TP53 mutation heterogeneity should be considered when using TP53 as a predictive biomarker for anti-programmed death (ligand) 1 (PD-(L)1) monotherapy in lung adenocarcinoma (LUAD). However, whether TP53 variant allele frequency (VAF) should also be considered remains unknown. Patients with LUAD from both published research and the local cohort were included to discover and validate the relationship between TP53 VAF and the efficacy of PD-(L)1inhibitors. The Cancer Genome Atlas (TCGA) LUAD data were included for genomic, transcriptomic, and tumor microenvironment analysis. Among 159 patients in the discovery cohort, low TP53 VAF patients (VAF ≤ 25%) experienced significantly longer progression-free survival (PFS) than both high TP53 VAF (5.4 vs. 3.3months; p=.021) and TP53-wild-type patients (5.4 vs. 2.5months; p=.011). Multivariate Cox regression revealed low TP53 VAF as an independent biomarker of better efficacy. Among 50 patients in the combined validation cohort, median PFS of low TP53 VAF patients was also significantly longer than that of high TP53 VAF patients (12.0 vs. 2.1months; p=.037). Analyzed with 469 TCGA LUAD samples, low TP53 VAF is associated with significantly higher PD-L1 expression, enrichment of gene sets related to T-cell activation, T cell-mediated immunity, and interferon-γ signaling pathways, and independently associated with more tumor-infiltrating CD8+ T cells compared with both high TP53 VAF and TP53-wild type. TP53 VAF should also be considered when using TP53 as a predictive biomarker. Only low TP53 VAF is independently associated with better efficacy of anti-PD-(L)1 monotherapy, which may result from higher PD-L1 expression and more tumor-infiltrating CD8+ T cells.

Loss of SYNCRIP unleashes APOBEC-driven mutagenesis, tumor heterogeneity, and AR-targeted therapy resistance in prostate cancer.

Tumor mutational burden and heterogeneity has been suggested to fuel resistance to many targeted therapies. The cytosine deaminase APOBEC proteins have been implicated in the mutational signatures of more than 70% of human cancers. However, the mechanism underlying how cancer cells hijack the APOBEC mediated mutagenesis machinery to promote tumor heterogeneity, and thereby foster therapy resistance remains unclear. We identify SYNCRIP as an endogenous molecular brake which suppresses APOBEC-driven mutagenesis in prostate cancer (PCa). Overactivated APOBEC3B, in SYNCRIP-deficient PCa cells, is a key mutator, representing the molecular source of driver mutations in some frequently mutated genes in PCa, including FOXA1, EP300. Functional screening identifies eight crucial drivers for androgen receptor (AR)-targeted therapy resistance in PCa that are mutated by APOBEC3B: BRD7, CBX8, EP300, FOXA1, HDAC5, HSF4, STAT3, and AR. These results uncover a cell-intrinsic mechanism that unleashes APOBEC-driven mutagenesis, which plays a significant role in conferring AR-targeted therapy resistance in PCa.

Linked-read based analysis of the medulloblastoma genome.

Medulloblastoma is the most common type of malignant pediatric brain tumor with group 4 medulloblastomas (G4 MBs) accounting for 40% of cases. However, the molecular mechanisms that underlie this subgroup are still poorly understood. Point mutations are detected in a large number of genes at low incidence per gene while the detection of complex structural variants in recurrently affected genes typically requires the application of long-read technologies. Here, we applied linked-read sequencing, which combines the long-range genome information of long-read sequencing with the high base pair accuracy of short read sequencing and very low sample input requirements. We demonstrate the detection of complex structural variants and point mutations in these tumors, and, for the first time, the detection of extrachromosomal DNA (ecDNA) with linked-reads. We provide further evidence for the high heterogeneity of somatic mutations in G4 MBs and add new complex events associated with it. We detected several enhancer-hijacking events, an ecDNA containing the MYCN gene, and rare structural rearrangements, such a chromothripsis in a G4 medulloblastoma, chromoplexy involving 8 different chromosomes, a TERT gene rearrangement, and a PRDM6 duplication.

A personalized cancer vaccine that induces synergistic innate and adaptive immune responses.

To demonstrate potent efficacy, a cancer vaccine needs to activate both innate and adaptive immune cells. Personalized cancer vaccine strategies often require the identification of patient-specific neoantigens; however, the clonal and mutational heterogeneity of cancer cells presents inherent challenges. Here, we presentextracellular nanovesiclesderived fromalpha-galactosylceramide-conjugated autologous acute myeloid leukemia (AML) cells (ECNV-αGC)as a personalized therapeutic vaccine that activates both innate and adaptive immune responses, bypassing the need to identify patient-specific neoantigens. ECNV-αGC vaccination directly engaged with and activated both invariant natural killer T (iNKT) cells and leukemia-specific CD8+ T cells in mice with AML, thereby promoting long-term anti-leukemic immune memory. ECNV-αGC sufficiently served as an antigen-presenting platform that could directly activate antigen-specific CD8+ T cells even in the absence of dendritic cells, thereby demonstrating a multi-faceted cellular mechanism of immune activation. Moreover, ECNV-αGC vaccination resulted in a significantly lower AML burden and higher percentage of leukemia-free survivors among cytarabine-treated hosts with AML. Human AML-derived ECNV-αGCs activated iNKT cells in both healthy individuals and patients with AML regardless of responsiveness to conventional therapies. Together, autologous AML-derived ECNV-αGCs may be a promising personalized therapeutic vaccine that efficiently establishes AML-specific long-term immunity without requiring the identification of neoantigens. This article is protected by copyright. All rights reserved.

Genetic dissection of intratumor heterogeneity of PD-L1 expression in EGFR-mutated lung adenocarcinoma.

In this study, we investigated the association between PD-L1 expression in tumor cells and underlying genetic mutations, which was analyzed in detail using laser microdissection and next-generation sequencing analysis. To investigate whether driver mutations are involved in the background of PD-L1 expression, the EGFR major activating mutation was selected as the most frequent driver mutation. Surgical resection specimens were used to extract sufficient amounts of nucleic acids for analysis, and the high tumor proportion score (TPS:100%) and low (TPS: 0%) PD-L1-expressing parts of the tumor were each laser microdissected to examine the association between PD-L1 expression heterogeneity and genetic mutations within the same tumor. The association between PD-L1 heterogeneity and gene mutations within the same tumor was investigated. Analysis showed no association between PD-L1 expression heterogeneity and genetic variants, which were found to be almost identical. However, PD-L1 expression was found to be associated with the number of tumor infiltrating lymphocytes (TILs) present in the tumor, which may be related to whether or not lymphocytes can infiltrate into the tumor depending on the tumor histological type (solid pattern, lepidic pattern, etc.) and other factors.

Molecular characterization of phenylketonuria patients from the North Region of Brazil: State of Pará.

Phenylketonuria (PKU) is an autosomal recessive disease resulting from a deficiency of the enzyme phenylalanine hydroxylase (PAH). Hyperphenylalaninemias (HPA) due to PAH deficiency are accompanied by a wide variety of clinical, biochemical, and molecular features. To identify and characterize pathogenic variants in the PAH gene and establish a correlation between genotype and biochemical phenotype in patients with PKU from state of Pará in the North Region of Brazil. All 13 exons of the PAH gene from 32 patients (21 PKU and 11 non-PKU HPA) were amplified by PCR and submitted to DNA sequencing (Sanger). Biochemical data were obtained from the patients' medical records. Molecular analysis identified 17 pathogenic variants and 3 nonpathogenic variants. The most frequent pathogenic variants were IVS10-11G>A (7.9%), p. Arg261Gln (7.9%), p. Val388Met (6.3%) and p. Ile65Thr (4.7%). Was observed correlations and inconsistencies between genotype and biochemical phenotype. In PKU patients from state of Pará, North Region of Brazil, a heterogeneous mutation spectrum was revealed, in which the most frequent mutations are variants commonly observed in other Brazilian studies and in the region of the Iberian Peninsula.

Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models.

The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modeled by a realistic mutation rate and as part of a realistic distribution of fitness effects, as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modeled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false-positive rates are in excess of true-positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.

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.

Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations

Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitochondrial DNA (mtDNA) mutations as efficient lineage-tracing markers of tumor clonality. We applied multiregional sampling and high-depth mtDNA sequencing to determine the metastatic patterns in advanced-stage OC patients. Somatic mtDNA mutations were profiled from a total of 195 primary and 200 metastatic tumor tissue samples from 35 OC patients. Our results revealed remarkable sample-level and patient-level heterogeneity. In addition, distinct mtDNA mutational patterns were observed between primary and metastatic OC tissues. Further analysis identified the different mutational spectra between shared and private mutations among primary and metastatic OC tissues. Analysis of the clonality index calculated based on mtDNA mutations supported a monoclonal tumor origin in 14 of 16 patients with bilateral ovarian cancers. Notably, mtDNA-based spatial phylogenetic analysis revealed distinct patterns of OC metastasis, in which a linear metastatic pattern exhibited a low degree of mtDNA mutation heterogeneity and a short evolutionary distance, whereas a parallel metastatic pattern showed the opposite trend. Moreover, a mtDNA-based tumor evolutionary score (MTEs) related to different metastatic patterns was defined. Our data showed that patients with different MTESs responded differently to combined debulking surgery and chemotherapy. Finally, we observed that tumor-derived mtDNA mutations were more likely to be detected in ascitic fluid than in plasma samples. Our study presents an explicit view of the OC metastatic pattern, which sheds light on efficient treatment for OC patients.

Genes with dual proto-oncogene and tumor suppressor gene activities are frequently altered by protein losses in colon cancers

Cancer genes are largely categorized into tumor suppressor gene (TSG) and proto-oncogene, but many have dual activities depending on the cellular context. In the present study, we analyzed DYRK1B, ESRP1, MTSS1, ADAMTS1, and INPP5F genes known to possess the dual activities in sporadic colon cancers (CCs). By the mutation analysis, we identified DYRK1B, ESRP1, MTSS1, ADAMTS1, and INPP5F frameshift mutations in 2, 2, 3, 3, and 1 CCs in instability-high (MSI-H) cases (1.1–3.2% of MSI-H CCs), respectively, but not microsatellite stable (MSS) cases. One CC showed regional heterogeneous mutations (RHM) of ESRP1 mutation. Immunohistochemistry identified protein expression of ESRP1, MTSS1, and ADAMTS1 in the CCs, revealing that approximately 30% of CCs lost the protein expression irrespective of the MSI status. Our study showed that dual TSG and proto-oncogene genes DYRK1B, ESRP1, MTSS1, ADAMTS1, and INPP5F harbored low incidences of inactivating mutations, but that the protein losses were frequent in CCs. Our study suggests a possibility that the dual-function genes could be altered mainly at the expression level, which might contribute to CC pathogenesis.

565-P: A Case of Atypical Diabetes, Monogenic Diabetes

A Case of Atypical Diabetes, Monogenic Diabetes, Monogenic diabetes formerly known as maturity onset diabetes of the young (MODY) is typically diagnosed in younger patients, usually age <25 years. It is a heterogenous disorder and typically accounts for 2-5% of diabetes. Clinical findings tend not to be reliable in determining the underlying etiology, hence patients may be misdiagnosed as type 1 or type 2 diabetes mellitus (DM). Patient is a 42-year-old non-obese male (BMI 21.9) with past medical history of type 2 diabetes mellitus who presented to establish care. He was diagnosed at age 25 with type 2 diabetes. At presentation, he had a hemoglobin A1c of 12.4% and was being managed with metformin, glimepiride and semaglutide by his primarry care physician. He has never been developed diabetes ketoacidosis or been on insulin. Also, his BMI has always been <25. He endorsed an extensive family history of DM but none of them require insulin or are overweight. His father, mother, brother, paternal grandfather and grandmother all have type 2 DM, most mainly diagnosed in their twenties and thirties. Laboratory studies including c-peptide and islet cell autoantibody screen panel were obtained which were low-normal (0.7ng/ml) and negative respectively. Repeat C-peptide was normal at 3.1ng/ml. Given these findings and his extensive family history of DM in non-obese persons, MODY was suspected. Hence genetic testing was done and revealed a heterogenous mutation, ABCC8 Variant in KATPase consistent with MODY12. This variant is typically sulfonylurea responsive. No screening test currently exists for monogenic diabetes. This case demonstrates the misdiagnosis of monogenic diabetes and the need for updated screening guidelines to aid with early diagnosis to prevent the associated comorbidities. Also, early diagnosis will prompt genetic testing in patients off springs and aid in adequate treatment. Finally, the value of a comprehensive history cannot be overemphasized in aiding to make a diagnosis of monogenic diabetes Disclosure R.Attah: None.

Modelling genetic stability in engineered cell populations

Predicting the evolution of engineered cell populations is a highly sought-after goal in biotechnology. While models of evolutionary dynamics are far from new, their application to synthetic systems is scarce where the vast combination of genetic parts and regulatory elements creates a unique challenge. To address this gap, we here-in present a framework that allows one to connect the DNA design of varied genetic devices with mutation spread in a growing cell population. Users can specify the functional parts of their system and the degree of mutation heterogeneity to explore, after which our model generates host-aware transition dynamics between different mutation phenotypes over time. We show how our framework can be used to generate insightful hypotheses across broad applications, from how a device’s components can be tweaked to optimise long-term protein yield and genetic shelf life, to generating new design paradigms for gene regulatory networks that improve their functionality.

Single-cell sequencing in primary intraocular tumors: understanding heterogeneity, the microenvironment, and drug resistance.

Retinoblastoma (RB) and uveal melanoma (UM) are the most common primary intraocular tumors in children and adults, respectively. Despite continued increases in the likelihood of salvaging the eyeball due to advancements in local tumor control, prognosis remains poor once metastasis has occurred. Traditional sequencing technology obtains averaged information from pooled clusters of diverse cells. In contrast, single-cell sequencing (SCS) allows for investigations of tumor biology at the resolution of the individual cell, providing insights into tumor heterogeneity, microenvironmental properties, and cellular genomic mutations. SCS is a powerful tool that can help identify new biomarkers for diagnosis and targeted therapy, which may in turn greatly improve tumor management. In this review, we focus on the application of SCS for evaluating heterogeneity, microenvironmental characteristics, and drug resistance in patients with RB and UM.

Abstract PR001: An endogenous molecular brake preventing APOBEC-driven tumor mutational burden, heterogeneity and AR therapy resistance

Abstract Tumor mutational burden and heterogeneity fuel resistance to many targeted therapies, which inevitably limits the clinical outcome of patients. The cytosine deaminase APOBEC proteins are major drivers of mutagenesis in human cancer, with over 70% of tumors exhibiting a mutational signature that is impacted by APOBEC activity. Nevertheless, the mechanisms through which tumor cells hijack the powerful APOBEC mutagenesis machinery to promote heterogeneity and therapy resistance remain largely unknown. Through a multi-disciplinary approach integrating bulk and single cell RNA-Seq (scRNA-Seq), whole-genome exome-sequencing (WES), and CRISPR library screening, we identified a long sought-after cell-intrinsic mechanism that prevents APOBEC-driven mutagenesis in non-malignant cells. The loss of this “molecular brake” unleashes APOBEC3B-driven mutagenesis in malignant cells, which then becomes a key mutator and represents the long sought-after molecular source of driver mutations in some frequently mutated genes in cancers, including FOXA1, EP300, and AR. Functional screening identified eight crucial drivers for Androgen Receptor (AR)-targeted therapy resistance in prostate cancer that are mutated by APOBEC3B: BRD7, CBX8, EP300, FOXA1, HDAC5, HSF4, STAT3, and AR. Finally, contrary to conventional understanding, our study reveals that driver mutations in FOXA1 induced by APOBEC3B, not mutations in AR, evolutionarily outcompete other driver mutations and eventually dominate the resistant tumors. Collectively, these results uncover a cell-intrinsic mechanism that unleashes APOBEC-driven mutagenesis, which plays a significant role in conferring targeted therapy resistance and could be the potential therapeutic targets to overcome resistance. Citation Format: Ping Mu, Xiaoling Li, Yunguan Wang. An endogenous molecular brake preventing APOBEC-driven tumor mutational burden, heterogeneity and AR therapy resistance [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr PR001.

Mutational profiling of true single circulating tumor cells (sCTC) in metastatic lung cancer to determine genomic heterogeneity and drug-resistance signatures.

e21024 Background: Omics of single Circulating tumor cells (CTCs) is highly envisioned though challenging. . Genotyping of TRUE sCTC capture and omics data can determine the molecular heterogeneity of a single cell without the stringent need for deep sequencing compared to tissue or blood (1/100th fold compared to ctDNA). Here, we show the utility of sCTC genome profiling to determine inter and intra-patient mutational heterogeneity and compare the outcome with matched ensembled ctDNA mutational profiles. Methods: OncoRADAR an antibody-affinity-based platform was used to capture live sCTCs without cell fixing. 50 sCTCs (90 %) and clusters (10 %) were isolated from 20 metastatic lung cancer pts for mutational genotyping. Amplified whole genomes were subjected to targeted hybrid-capture comprehensive genome profiling. Libraries prepared using a custom-designed comprehensive gene panel OncoIndx, targeting 600 cancer-relevant exons including MSI and HRR pathway genes, were sequenced in paired-end mode on the Illumina platform. Variant calling was performed using an in-house developed bioinformatics pipeline. Pathway enrichment analysis was performed manually using data enriched from different gene pathway databases. Results: 81 mutations were detected in 56 genes across all sCTCs with pathogenic, likely pathogenic, and unknown significance. The mutational landscape included SNVs (38.6%), splice variants (10%), frameshift mutations (0.8%), and truncations (50.4%). From a subset of patients (10 %), multiple sCTCs showed PTEN variant cooccurring with ESR1 and MET. This suggest a clonal selection and emergence of subclones during progression. Pathways related to drug resistance, migration, deregulated cell cycle, and signaling were significantly enriched in multiple sCTCs when compared to plasma genotyping. Low average TMB (1.89), LOH (3.9) and HRD (14.67%), and high MSI (28.68%) scores were observed. In contrast, matching ctDNA had higher average LOH (18.67), HRD (45.08%), and lower MSI (0.99) scores. Multiple sCTCs from a small fraction of patients had comparable values for genome stability indicators, suggesting maintained genome stability. Genotyping of sCTC among patients showed a high variability compared to comprehensive analysis at the ctDNA level. Conclusions: Targeted gene profiling of true sCTCs revealed multiple variants that remained undetected in ctDNA, enabling a better understanding of tumor heterogeneity. Analysis of multiple sCTCs from the same patient underscores the importance of clonal evolution and plasticity during metastasis. Longitudinal monitoring of sCTCs may reveal personalized markers for disease prevalence, metastasis and relapse. sCTC genotyping may help design personalized therapy with better precision.

SARS-CoV-2 spike protein diversity at an intra-host level, among SARS-CoV-2 infected individuals in South Africa, 2020 to 2022.

Intra-host diversity studies are used to characterise the mutational heterogeneity of SARS-CoV-2 infections in order to understand the impact of virus-host adaptations. This study investigated the frequency and diversity of the spike (S) protein mutations within SARS-CoV-2 infected South African individuals. The study included SARS-CoV-2 respiratory samples, from individuals of all ages, received at the National Health Laboratory Service at Charlotte Maxeke Johannesburg Academic hospital, Gauteng, South Africa, from June 2020 to May 2022. Single nucleotide polymorphism (SNP) assays and whole genome sequencing were performed on a random selection of SARS-CoV-2 positive samples. The allele frequency (AF) was determined using TaqMan Genotyper software for SNP PCR analysis and galaxy.eu for analysis of FASTQ reads from sequencing. The SNP assays identified 5.3% (50/948) of Delta cases with heterogeneity at delY144 (4%; 2/50), E484Q (6%; 3/50), N501Y (2%; 1/50) and P681H (88%; 44/50), however only heterogeneity for E484Q and delY144 were confirmed by sequencing. From sequencing we identified 9% (210/2381) of cases with Beta, Delta, Omicron BA.1, BA.2.15, and BA.4 lineages that had heterogeneity in the S protein. Heterogeneity was primarily identified at positions 19 (1.4%) with T19IR (AF 0.2-0.7), 371 (92.3%) with S371FP (AF 0.1-1.0), and 484 (1.9%) with E484AK (0.2-0.7), E484AQ (AF 0.4-0.5) and E484KQ (AF 0.1-0.4). Mutations at heterozygous amino acid positions 19, 371 and 484 are known antibody escape mutations, however the impact of the combination of multiple substitutions identified at the same position is unknown. Therefore, we hypothesise that intra-host SARS-CoV-2 quasispecies with heterogeneity in the S protein facilitate competitive advantage of variants that can completely/partially evade host's natural and vaccine-induced immune responses.

The joint role of methylation and immune-related lncRNAs in ovarian cancer: Defining molecular subtypes and developing prognostic signature

IntroductionComplex outcome of ovarian cancer (OC) stems from the tumor immune microenvironment (TIME) influenced by genetic and epigenetic factors. This study aimed to comprehensively explored the subclasses of OC through lncRNAs related to both N6-methyladenosine (m6A)/N1-methyladenosine (m1A)/N7-methylguanosine (m7G)/5-methylcytosine (m5C) in terms of epigenetic variability and immune molecules and develop a new set of risk predictive systems. Material and methodsThe lncRNA data of OC were collected from TCGA. Spearman correlation analysis on lncRNA data of OC with immune-related gene expression and with m6A/m5C/m1A/m7G were respectively conducted. The m6A/m5C/m1A/m7G-related m6A/m5C/m1A/m7G related immune lncRNA subtypes were identified on the basis of the prognostic lncRNAs. Heterogeneity among subtypes was evaluated by tumor mutation analysis, tumor microenvironment (TME) component analysis, response to immune checkpoint blocked (ICB) and chemotherapeutic drugs. A risk predictive system was developed based on the results of Cox regression analysis and random survival forest analysis of the differences between each specific cluster and other clusters. ResultsThree m6A/m5C/m1A/m7G-related immune lncRNA subtypes of OC showing distinct differences in prognosis, mutation pattern, TIME components, immunotherapy and chemotherapy response were identified. A set of risk predictive system consisting of 10 lncRNA for OC was developed, according to which the risk score of samples in each OC dataset was calculated and risk type was defined. ConclusionsThis study classified three m6A/m5C/m1A/m7G-related immune lncRNA subtypes with distinct heterogeneous mutation patterns, TME components, ICB therapy and immune response, and provided a set of risk predictive system consisted of 10 lncRNA for OC.

Identifying Cancer Driver Pathways Based on the Mouth Brooding Fish Algorithm.

Identifying the driver genes of cancer progression is of great significance in improving our understanding of the causes of cancer and promoting the development of personalized treatment. In this paper, we identify the driver genes at the pathway level via an existing intelligent optimization algorithm, named the Mouth Brooding Fish (MBF) algorithm. Many methods based on the maximum weight submatrix model to identify driver pathways attach equal importance to coverage and exclusivity and assign them equal weight, but those methods ignore the impact of mutational heterogeneity. Here, we use principal component analysis (PCA) to incorporate covariate data to reduce the complexity of the algorithm and construct a maximum weight submatrix model considering different weights of coverage and exclusivity. Using this strategy, the unfavorable effect of mutational heterogeneity is overcome to some extent. Data involving lung adenocarcinoma and glioblastoma multiforme were tested with this method and the results compared with the MDPFinder, Dendrix, and Mutex methods. When the driver pathway size was 10, the recognition accuracy of the MBF method reached 80% in both datasets, and the weight values of the submatrix were 1.7 and 1.89, respectively, which are better than those of the compared methods. At the same time, in the signal pathway enrichment analysis, the important role of the driver genes identified by our MBF method in the cancer signaling pathway is revealed, and the validity of these driver genes is demonstrated from the perspective of their biological effects.

Chinese Expert Consensus on Non-small Cell Lung Cancer with EGFR Exon 20 Insertion Mutations (2023 Edition)

With the development of precision diagnosis and treatment for non-small cell lung cancer (NSCLC), the epidermal growth factor receptor (EGFR) exon 20 insertion (ex20ins) mutations, as a rare subset of EGFR mutaions, have gradually attracted attention recently. The heterogeneity of EGFR ex20ins mutations is very high, different variants have different clinical benefits, and the prognosis is extremely poor. The available traditional treatment outcomes are poor in patients with EGFR ex20ins positive NSCLC and polymerase chain reaction (PCR) tests would miss aprocimately 50% of the variants. Therefore, high attention should be paid to EGFR ex20ins positive NSCLC during the clinical practice. The expert panel has formed a consensus on the standardized clinical diagnosis and treatment of EGFR ex20ins mutation NSCLC through reference to literature and clinical data, and combined with the experts' own clinical experience, the consensus recommendations including clinicopathologic characteristics, therapies, testing methods and recent relevant clinical trials for NSCLC patients with EGFR ex20ins mutation, in order to provide medication reference for clinical physicians at all levels.

Longitudinal Analyses of Mutational Subclonal Architecture and Tumor Subtypes in Recurrent Bladder Cancer.

Longitudinal tumor sequencing of recurrent bladder cancer (BC) can facilitate the investigation of BC progression-associated genomic and transcriptomic alterations. In this study, we analyzed 18 tumor specimens including distant and locoregional metastases obtained during tumor progression for five BC patients using whole-exome and transcriptome sequencing. Along with the substantial level of intratumoral mutational heterogeneity across the cases, we observed that clonal mutations were enriched with known BC driver genes and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC)-associated mutation signatures compared with subclonal mutations, suggesting the genetic makeup for BC tumorigenesis associated with APOBEC deaminase activity was accomplished early in the cancer evolution. Mutation-based phylogenetic analyses also revealed temporal dynamics of mutational clonal architectures in which the number of mutational clones varied along the BC progression and notably was often punctuated by clonal sweeps associated with chemotherapy. The bulk-level transcriptome sequencing revealed frequent subtype switching in which transcriptionally defined BC subtypes may vary during tumor progression. Longitudinal whole-exome and transcriptome sequencing of recurrent BC may advance our understanding into the BC heterogeneity in terms of somatic mutations, cell clones and transcriptome-based tumor subtypes during disease progression.