Somatic Copy Number Alterations Research Articles

Abstract B059: Assessment of ctDNA analysis methods using high purity ctDNA from the aqueous humor of retinoblastoma eyes

Abstract Background: Whole-genome sequencing (WGS) of cell-free DNA (cfDNA) paired with methods like ichorCNA and DELFI has become a valuable approach for detecting circulating tumor DNA (ctDNA). However, the mixture of ctDNA with non-tumor cfDNA in plasma complicates accurate validation of ctDNA detection methods. In contrast, aqueous humor (AH) from treatment-free retinoblastoma (RB) eyes is uniquely enriched in ctDNA, providing an optimal source for generating reference samples. This study leverages AH-derived biological ctDNA to evaluate two established ctDNA analysis methods. Methods: Biologically derived cfDNA mixtures were created by combining WGS reads from two AH samples with pooled reads from non-tumor blood samples (N=20). One AH sample (RB_023_OS) showed >99% tumor fraction (TFx) with ichorCNA, while the other (RB_025_OD) had confirmed presence of ctDNA based on >99% variant allele frequency (VAF) for an RB1 variant, despite being somatic copy number alteration (SCNA)-negative. Mixtures were prepared across a range of TFx values (0.01-0.5) and unique sequencing coverages (0.1x, 0.5x, 1x, and 2x). TFx was calculated using ichorCNA with standard parameters and optimized parameters for low TFx levels. We also tested an enrichment strategy targeting shorter ctDNA fragments (≤150 base pairs) and generated genome-wide fragmentation profiles using the DELFI method to assess short-to-long (S:L) fragment ratios across 5-Mb bins. Results: We evaluated the impact of sequencing coverage, parameter selection, and fragment size selection on TFx estimation by ichorCNA. Standard ichorCNA parameters demonstrated limited sensitivity, detecting ctDNA only in samples with TFx of 5-6% or higher. Increasing sequencing coverage did not substantially improve the limit of detection (LoD) or the accuracy of TFx quantification. Optimized parameters reduced the LoD to 3% TFx, but only in samples with ≥0.5x coverage, indicating a dependence on sequencing depth for accurate ctDNA detection and quantification. In RB_025_OD, where no SCNAs were present, ichorCNA failed to estimate the TFx despite an RB1 VAF exceeding 99%, highlighting the platform's reliance on SCNAs for accurate TFx detection. Short fragment enrichment (≤150 base pairs) significantly increased TFx values across all samples but could be mapped back to the original TFx values accurately using polynomial curve fitting (R-squared=0.97). Genome- wide fragmentation profiles showed increasing deviation from non-tumor controls as TFx increased, with SCNA-positive samples exhibiting greater deviations than SCNA-negative samples. Conclusions: These findings demonstrate the dependence on sequencing coverage and the presence of SCNAs by current ctDNA analysis methods, highlighting their limitations for accurately detecting ctDNA in challenging scenarios. Citation Format: Nikki Higa, Peter Kuhn, Jesse L Berry, Liya Xu. Assessment of ctDNA analysis methods using high purity ctDNA from the aqueous humor of retinoblastoma eyes [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B059.

Hallmarks of a genomically distinct subclass of head and neck cancer

Cancer is caused by an accumulation of somatic mutations and copy number alterations (CNAs). Besides mutations, these copy number changes are key characteristics of cancer development. Nonetheless, some tumors show hardly any CNAs, a remarkable phenomenon in oncogenesis. Head and neck squamous cell carcinomas (HNSCCs) arise by either exposure to carcinogens, or infection with the human papillomavirus (HPV). HPV-negative HNSCCs are generally characterized by many CNAs and frequent mutations in CDKN2A, TP53, FAT1, and NOTCH1. Here, we present the hallmarks of the distinct subgroup of HPV-negative HNSCC with no or few CNAs (CNA-quiet) by genetic profiling of 802 oral cavity squamous cell carcinomas (OCSCCs). In total, 73 OCSCC (9.1%) are classified as CNA-quiet and 729 as CNA-other. The CNA-quiet group is characterized by wild-type TP53, frequent CASP8 and HRAS mutations, and a less immunosuppressed tumor immune microenvironment with lower density of regulatory T cells. Patients with CNA-quiet OCSCC are older, more often women, less frequently current smokers, and have a better 5-year overall survival compared to CNA-other OCSCC. This study demonstrates that CNA-quiet OCSCC should be considered as a distinct, clinically relevant subclass. Given the clinical characteristics, the patient group with these tumors will rapidly increase in the aging population.

Comprehensive mutational profiling identifies new driver events in cutaneous leiomyosarcoma.

Cutaneous leiomyosarcoma (cLMS) is a rare soft tissue neoplasm, showing smooth muscle differentiation, that arises from the mesenchymal cells of the dermis. To-date, genetic investigation of these tumours has involved studies with small sample sizes and limited analyses that identified recurrent somatic mutations in RB1 and TP53, copy number gain of MYCOD and IGF1R, and copy number loss of PTEN. To better understand the molecular pathogenesis of cLMS, we comprehensively explored the mutational landscape of these rare tumours to identify candidate driver events. In this retrospective, multi-institutional study, we performed whole-exome sequencing and RNA sequencing on 38 cases of cLMS. TP53 and RB1 were identified as significantly mutated, thus, represent validated driver genes of cLMS. COSMIC mutational signatures SBS7a/b and DBS1 were recurrent, thus, ultraviolet light exposure may be an aetiological factor driving cLMS. Analysis of significantly recurrent somatic copy number alterations, which represent candidate driver events, found focal (<10Mb) deletions encompassing TP53 and KDM6B, and amplifications encompassing ZMYM2, MYOCD, MAP2K4 and NCOR1. A larger (24 Mb) recurrent deletion encompassing CYLD was also identified as significant. Significantly recurrent broad copy number alterations, involving at least half of a chromosome arm, included deletions of 6p/q, 10p/q, 11q, 12q, 13q and 16p/q, and amplification of 15q. Notably PTEN is located on 10q, RB1 on 13q and IGFR1 on 15q. Fusion gene analysis identified recurrent CRTC1/3::MAML2 fusions, as well as many novel fusions in individual samples. Our analysis of the largest number of cLMS cases to-date highlights the importance of large cohort sizes and the exploration beyond small targeted gene panels when performing molecular analyses, as it allowed a comprehensive exploration of the mutational landscape of these tumours and identification of novel candidate driver events. It also uniquely afforded the opportunity to compare the molecular phenotype of cLMS with LMS of other tissue types, such as uterine and soft tissue LMS. Given that molecular profiling has resulted in the development of novel targeted treatment approaches for uterine and soft tissue LMS, our study now allows the same opportunities to become available for patients with cLMS.

Single-Cell Detection of Somatic Copy Number Alterations in Human Kidney by Chromatin Accessibility Profiling

Single-Cell Detection of Somatic Copy Number Alterations in Human Kidney by Chromatin Accessibility Profiling

Abstract C106: Enhanced characterization of molecular attributes through multi-omics analysis and comprehensive evaluation of global and local genomic ancestry in colorectal cancer among Hispanic-Latinos

Abstract Introduction: Colorectal cancer (CRC) remains a significant public health challenge, representing the second leading cause of cancer-related mortality in the United States. Although mortality rates have generally decreased, the Hispanic/Latino (H/L) population in the Los Angeles area still experiences mortality rates up to 20% higher than those of their Caucasian American counterparts. Additionally, they are often diagnosed at a younger age and with more advanced disease stages, highlighting significant disparities in CRC outcomes. Currently, there are limited studies integrating clinical and multi-omics data from H/L populations, which are crucial for understanding the implications of colorectal tumorigenesis and addressing these disparities effectively. Methods: Clinical and genomic sequencing data were obtained from 60 primary CRC Tumor/Normal (T/N) samples within the Hispanic/Latino (H/L) population in the Los Angeles area through the PE-CGS network. For comparison, we analyzed 3,578 samples from non-Hispanic Whites (NHW) obtained from public databases. Additionally, we retrieved three CRC samples with spatial transcriptomic (ST) data from the 10xGenomics database. Using Whole Exome and RNA sequencing data, we performed somatic mutations, somatic copy number alterations (SCNAs), differential gene expression, cellular pathways, gene fusions, and global &amp; local genomic ancestry analyses. The ST data underwent analysis utilizing newly released bioinformatics tools. Clinical and genomic data were integrated. Results: In these studies, distinct Amerindian (AMR) genomic ancestry proportion, age at diagnosis, and tumor localization patterns were observed, alongside significant mutations in key genes such as APC, TP53, and KRAS. The studies revealed evident cancer heterogeneity, influenced by factors such as mutation type, microsatellite instability, tumor subsite, and ethnicity. Additionally, several previously well-defined SCNAs were detected in the majority of tumors. Comparative analysis of gene expression and cellular pathways between H/L and NHW samples revealed distinct patterns. Furthermore, we identified gene fusions that potentially contribute to oncogenic activity in CRC. Ancestry analysis pointed to a predominant AMR ancestry. Notably, distinct associations of genetic ancestry with CRC tumor clinicopathological characteristics were identified. ST analysis delineated separate cancer, immune, and stroma components within the tumors. Conclusion: Our research has explored the molecular profiling of CRC tumors in H/L patients, providing crucial insights into the characterization of CRC tumors at the DNA and RNA levels, as well as the complex clinical and genomic diversity within our target population. Additionally, it offers valuable insights into the heterogeneity of CRC tumors and the tumor microenvironment. These findings establish the groundwork for subsequent projects, potentially leading to precision medicine approaches. Citation Format: Enrique I. Velazquez-Villarreal, Brigette Waldrup, Yonatan Amzaleg, Yuxin Jin, Mackenzie Postel, Donna Loza, Serina Ovalle, Elizabeth Quino, Carmen Chavez, Julie Culver, Mariana C. Stern, Heinz-Josef Lenz, David W. Craig, John D. Carpten. Enhanced characterization of molecular attributes through multi-omics analysis and comprehensive evaluation of global and local genomic ancestry in colorectal cancer among Hispanic-Latinos [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C106.

A multi-task deep learning model based on comprehensive feature integration and self-attention mechanism for predicting response to anti-PD1/PD-L1

BackgroundImmune checkpoint inhibitor (ICI) has been widely used in the treatment of advanced cancers, but predicting their efficacy remains challenging. Traditional biomarkers are numerous but exhibit heterogeneity within populations. For comprehensively utilizing the ICI-related biomarkers, we aim to conduct multidimensional feature selection and deep learning model construction. MethodsWe used statistical and machine learning methods to map features of different levels to next-generation sequencing gene expression. We integrated genes from different sources into the feature input of a deep learning model, by means of self-attention mechanism. ResultsWe performed feature selection at the single-cell sequencing level, PD-L1 (CD274) analysis level, tumor mutational burden (TMB)/mismatch repair (MMR) level, and somatic copy number alteration (SCNA) level, obtaining 96 feature genes. Based on the pan-cancer dataset, we trained a multi-task deep learning model. We tested the model in the bladder urothelial carcinoma testing set 1 (AUC = 0.62, n = 298), bladder urothelial carcinoma testing set 2 (AUC = 0.66, n = 89), non-small cell lung cancer testing set (AUC = 0.85, n = 27), and skin cutaneous melanoma testing set (AUC = 0.71, n = 27). ConclusionOur study demonstrates the potential of the deep learning model for integrating multidimensional features in predicting the outcome of ICI. Our study also provides a potential methodological case for medical scenarios requiring the integration of multiple levels of features.

Multi-regional genomic and transcriptomic characterization of a melanoma-associated oral cavity cancer provide evidence for CASP8 alteration-mediated field cancerization

BackgroundPrecancerous and malignant tumours arise within the oral cavity from a predisposed “field” of epithelial cells upon exposure to carcinogenic stimulus. This phenomenon is known as “Field Cancerization”. The molecular genomic and transcriptomic alterations that lead to field cancerization and tumour progression is unknown in Indian Oral squamous cell carcinoma (OSCC) patients.MethodsWe have performed whole exome sequencing, copy-number variation array and whole transcriptome sequencing from five tumours and dysplastic lesions (sampled from distinct anatomical subsites - one each from buccal anterior and posterior alveolus, dorsum of tongue–mucosal melanoma, lip and left buccal mucosa) and blood from a rare OSCC patient with field cancerization.ResultsA missense CASP8 gene mutation (p.S375F) was observed to be the initiating event in oral tumour field development. APOBEC mutation signatures, arm-level copy number alterations, depletion of CD8 + T cells and activated NK cells and enrichment of pro-inflammatory mast cells were features of early-originating tumours. Pharmacological inhibition of CASP8 protein in a CASP8-wild type OSCC cell line showed enhanced levels of cellular migration and viability.ConclusionCASP8 alterations are the earliest driving events in oral field carcinogenesis, whereas additional somatic mutational, copy number and transcriptomic alterations ultimately lead to OSCC tumour formation and progression.

Comprehensive Analyses of Somatic Copy Number Alterations and Mutations Based on the Adenoma-Carcinoma Sequence.

Identifying molecular alterations in the adenoma and carcinoma components within the same tumor would greatly contribute to understanding the neoplastic progression of early colorectal cancer. We examined somatic copy number alterations (SCNAs) and mutations involved in the adenoma and carcinoma components obtained from the same tumor in 46 cases of microsatellite-stable carcinoma in adenoma, using a genome-wide SNP array and gene mutation panel. In addition, we also performed hierarchical clustering to determine the SCNA frequencies in the tumors, resulting in stratification of the samples into two subgroups according to SCNA frequency. Subgroup 1 was characterized by multiple SCNAs and carcinoma components exclusively, while Subgroup 2 was characterized by a low frequency of SCNAs and both the adenoma and carcinoma components. The numbers of total genes and genes with gains were higher in the carcinoma than adenoma components. The three most frequent gains in both components were located at 1p36.33-1q44, 2p25.3-2q37.3, and 3p26.3-3q29. However, no candidate genes mapped to these regions. APC and KRAS mutations were common in both components, whereas the frequency of TP53 mutations was statistically higher in the carcinoma than adenoma component. However, TP53 mutations were not correlated with SCNA frequency. We suggest that considerable SCNAs and TP53 mutations are required for progression from adenoma to carcinoma within the same intramucosal neoplastic lesion.

TGF-β signaling-related signature for predicting prognosis and therapeutic response in lower-grade glioma.

Low-grade glioma (LGG) is a tumor that includes World Health Organization (WHO) grade II and III glioma, the treatment of which consistently results in relapse and drug resistance. Transforming growth factor-beta (TGF-β) is a multifunctional cytokine that regulates various cellular processes, which is found to be abnormal in tumors and promotes glioma development and progression. In this study, we aimed to systematically evaluate the importance of the genes associated with TGF-β in LGG and discover the role of these genes in the prognosis and treatment response of LGG. We used the "Bioconductor Limma" and "consensusClusterplus" R packages to screen differential and prognostic TGF-β-related genes. The R package "GSVA" was used to estimate the infiltration of immune cells and metabolism signature. The drug sensitivity for each TGF-β subtype was assessed by the R package "pRRophetic". The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to assess the copy number variation (CNV). The onco-print tool of the "complexheatmap package" was employed to visualize the somatic mutation and copy number alteration (CNA) among TGF clusters. We reported three subtypes (A, B, and C) of LGG according to the classification of TGF-β-related genes, where subtype A showed the best prognosis. Subtype B was highly enriched in immune cells. Somatic variations were observed to be diverse in all of the three TGF-β subtypes. Furthermore, another three genes (SHA, AC062021.1, and SNCG) related to TGF-β were identified, which can be a superior predictor of prognosis with a risk score. LGG can be divided into three subtypes based on TGF-β signaling-related genes with distinct immune infiltration, metabolism, somatic variations, and prognosis.

914P The landscape of somatic copy number alterations of head and neck squamous cell carcinoma across different anatomic sites

914P The landscape of somatic copy number alterations of head and neck squamous cell carcinoma across different anatomic sites

104P The development of a classifier of somatic copy number alteration burden in liquid biopsy with potential clinical impact in advanced non-small cell lung cancer (NSCLC)

104P The development of a classifier of somatic copy number alteration burden in liquid biopsy with potential clinical impact in advanced non-small cell lung cancer (NSCLC)

Genomic Amplification of TBC1D31 Promotes Hepatocellular Carcinoma Through Reducing the Rab22A-Mediated Endolysosomal Trafficking and Degradation of EGFR.

Hepatocellular carcinomas (HCCs) are characterized by a vast spectrum of somatic copy number alterations (CNAs); however, their functional relevance is largely unknown. By performing a genome-wide survey on prognosis-associated focal CNAs in 814 HCC patients by an integrative computational framework based on transcriptomic data, genomic amplification is identified at 8q24.13 as a promising candidate. Further evidence is provided that the 8q24.13 amplification-driven overexpression of Rab GTPase activating protein TBC1D31 exacerbates HCC growth and metastasis both in vitro and in vivo through activating Epidermal growth factor receptor (EGFR) signaling. Mechanistically, TBC1D31 acts as a Rab GTPase activating protein to catalyze GTP hydrolysis for Rab22A and then reduces the Rab22A-mediated endolysosomal trafficking and degradation of EGFR. Notably, overexpression of TBC1D31 markedly increases the resistance of HCC cells to lenvatinib, whereas inhibition of the TBC1D31-EGFR axis can reverse this resistance phenotype. This study highlights that TBC1D31 at 8q24.13 is a new critical oncogene, uncovers a novel mechanism of EGFR activation in HCC, and proposes the potential strategies for treating HCC patients with TBC1D31 amplification or overexpression.

Genomic landscape of early-stage prostate adenocarcinoma in Mexican patients: an exploratory study

BackgroundHealth disparities have been highlighted among patient with prostate adenocarcinoma (PRAD) due to ethnicity. Mexican men present a more aggressive disease than other patients resulting in less favorable treatment outcome. We aimed to identify the mutational landscape which could help to reduce the health disparities among minority groups and generate the first genomics exploratory study of PRAD in Mexican patients.MethodsParaffin-embedded formalin-fixed tumoral tissue from 20 Mexican patients with early-stage PRAD treated at The Instituto Nacional de Cancerología, Mexico City from 2017 to 2019 were analyzed. Tumoral DNA was prepared for whole exome sequencing, the resulting files were mapped against h19 using BWA-MEM. Strelka2 and Lancet packages were used to identify single nucleotide variants (SNV) and insertions or deletions. FACETS was used to determine somatic copy number alterations (SCNA). Cancer Genome Interpreter web interface was used to determine the clinical relevance of variants.ResultsPatients were in an early clinical stage and had a mean age of 59.55 years (standard deviation [SD]: 7.1 years) with 90% of them having a Gleason Score of 7. Follow-up time was 48.50 months (SD: 32.77) with recurrences and progression in 30% and 15% of the patients, respectively. NUP98 (20%), CSMD3 (15%) and FAT1 (15%) were the genes most frequently affected by SNV; ARAF (75%) and ZNF419 (70%) were the most frequently affected by losses and gains SNCA’s. One quarter of the patients had mutations useful as biomarkers for the use of PARP inhibitors, they comprise mutations in BRCA, RAD54L and ATM. SBS05, DBS03 and ID08 were the most common mutational signatures present in this cohort. No associations with recurrence or progression were identified.ConclusionsThis pilot study reveals the mutational landscape of early-stage prostate adenocarcinoma in Mexican men, providing a first approach to understand the mutational patterns and actionable mutations in early prostate cancer can inform personalized treatment approaches and reduce the underrepresentation in genomic cancer studies.

Comprehensive genomic profiling of infiltrative follicular variant of papillary thyroid carcinoma.

Infiltrative follicular variant of papillary thyroid carcinoma (IFVPTC) exhibits nuclear characteristics typical of papillary thyroid carcinoma (PTC) but demonstrates a follicular growth pattern. The diagnosis of IFVPTC presenting with atypical nuclear features of PTC poses challenges for both preoperative cytopathology and postoperative histopathology. In such cases, molecular markers are needed to serve as diagnostic aids. Given the limited knowledge of IFVPTC's genomic features, this study aimed to characterize its genetic alterations and identify clinically relevant molecular markers. Whole-exome sequencing of 50 IFVPTC tumor-normal pairs identified single-nucleotide variants, somatic copy number alterations (sCNAs), and subclonal architecture. Key mutations were verified via polymerase chain reaction and Sanger sequencing, whereas valuable biomarkers were validated via immunohistochemistry (IHC). This study found that endogenous processes rather than exogenous mutagens dominated the shaping of the genome of IFVPTC during tumorigenesis. BRAF V600E was the only common trunk mutation and significantly mutated gene in IFVPTC. Subcloning analysis found that most IFVPTC samples harbored two or more coexisting clones. sCNA analysis revealed that human leukocyte antigen C (HLA-C) and HLA-A were significantly amplified. Subsequent IHC investigations indicated that HLA-C shows promise in averting the misclassification of challenging-to-interpret IFVPTC and invasive encapsulated follicular variant of PTC (I-EFVPTC) as noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP). Although there were several similarities between classic PTC and IFVPTC, they differed significantly in their sCNA patterns. This study provides valuable insights into IFVPTC's genetic alterations and highlights the potential of HLA-C IHC to distinguish challenging-to-interpret IFVPTC and I-EFVPTC from NIFTP, which will enhance the understanding of its molecular features for improved diagnosis and management.

The molecular profile of gastric intraepithelial foveolar type neoplasia based on somatic copy number alterations and multiple mutation analysis

BackgroundGastric foveolar type neoplasia is a rare histological variant of gastric tumors. It is very difficult to differentiate between benign and malignant intraepithelial foveolar neoplasia (IFN). Although limited molecular alterations have been identified in IFNs, somatic copy number alterations (SCNAs), which are linked to tumor progression, have not been systematically evaluated in IFN.MethodsThe aim of the present study was to comprehensively examine SCNAs using a SNP array in 37 cases of IFN, compared with intestinal type dysplasia, including 39 low grade (LGD) and 32 high grade dysplasia (HGD) cases. In addition, gene mutations were evaluated using a gene panel. Finally, we attempted to determine molecular profiles using a hierarchical clustering analysis.ResultsTwo patterns could be categorized according to the SCNAs in 108 tumors examined: high (subgroup 1) and low (subgroup 2) frequencies of SCNAs. Although IFN and LGD were associated with subgroup 2, HGD was found in both subgroups. The median numbers of total SCNAs and copy number gains were higher in IFN or HGD than in LGD. In addition, the IFN genotype was characterized by altered genes located at 4p13–4q35.2, including RAP1GDS1 and LEF1, which may be associated with IFN development. Finally, no significant mutations were found in IFNs using a gene panel.ConclusionsThe current molecular profiles of IFN may help elucidate the mechanisms of IFN development.

Robust analysis of allele-specific copy number alterations from scRNA-seq data with XClone

Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

Genomics and proteomics to determine novel molecular subtypes and predict the response to immunotherapy and the effect of bevacizumab in glioblastoma

Glioblastoma (GBM) is a highly aggressive, infiltrative malignancy that cannot be completely cured by current treatment modalities, and therefore requires more precise molecular subtype signatures to predict treatment response for personalized precision therapy. Expression subtypes of GBM samples from the Cancer Genome Atlas (TCGA) were identified using BayesNM and compared with existing molecular subtypes of GBM. Biological features of the subtypes were determined by single-sample gene set enrichment analysis. Genomic and proteomic data from GBM samples were combined and Genomic Identification of Significant Targets in Cancer analysis was used to screen genes with recurrent somatic copy-number alterations phenomenon. The immune environment among subtypes was compared by assessing the expression of immune molecules and the infiltration of immune cells. Molecular subtypes adapted to immunotherapy were identified based on Tumor Immune Dysfunction and Exclusion (TIDE) score. Finally, least absolute shrinkage and selection operator (LASSO) logistic regression was performed on the expression profiles of S2, S3 and S4 in TCGA-GBM and RPPA to determine the respective corresponding best predictive model. Four novel molecular subtypes were classified. Specifically, S1 exhibited a low proliferative profile; S2 exhibited the profile of high proliferation, IDH1 mutation, TP53 mutation and deletion; S3 was characterized by high immune scores, innate immunity and adaptive immune infiltration scores, with the lowest TIDE score and was most likely to benefit from immunotherapy; S4 was characterized by high proliferation, EGFR amplification, and high protein abundance, and was the most suitable subtype for bevacizumab. LASSO analysis constructed the best prediction model composed of 13 genes in S2 with an accuracy of 96.7%, and the prediction model consisting of 17 genes in S3 with an accuracy of 86.7%, and screened 14 genes as components of the best prediction model in S4 with an accuracy of 93%. To conclude, our study classified reproducible and robust molecular subtypes of GBM, and these findings might contribute to the identification of patients responding to immunotherapy, thereby improving GBM prognosis.

Comprehensive genomic analysis reveals clonal origin and subtype-specific evolution in a case of sporadic multiple meningiomas.

Meningioma is the most common primary intracranial tumor in adults, with up to 10% manifesting as multiple tumors. Data on the genomic and molecular changes in sporadic multiple meningiomas are scarce, leading to ongoing debates regarding their evolutionary processes. A comprehensive genetic analysis of a large number of lesions, including precursor lesions, is necessary to explore these two possible origins: clonal and independent. In the present study, we performed whole-exome sequencing and analyzed somatic single-nucleotide variants (SNVs), insertions/deletions (INDELs), and copy number alterations (CNAs) in a patient with sporadic multiple meningiomas. These meningiomas included two mass-forming lesions of different histological subtypes (transitional and chordoid) and two small meningothelial nests. Genetic analysis revealed CNAs on chromosomes 22q and Y as common abnormalities in the two largest tumors. Furthermore, we identified SNV/INDELs unique to each focus, with NF2 mutation prevalent in the transitional meningioma and CREBBP mutation in the chordoid meningioma. Loss of chromosome 22 was detected in two small meningothelial nests. Overall, we elucidated the clonal origin and subtype-specific evolution of multiple meningiomas in this case. CNAs may serve as the initial driving event in meningioma development.

The genomic landscape of lung cancer in never-smokers from the Women's Health Initiative.

Over 200,000 individuals are diagnosed with lung cancer in the United States every year, with a growing proportion of cases, especially lung adenocarcinoma, occurring in individuals who have never smoked. Women over the age of 50 comprise the largest affected demographic. To understand the genomic drivers of lung adenocarcinoma and therapeutic response in this population, we performed whole genome and/or whole exome sequencing on 73 matched lung tumor/normal pairs from postmenopausal women who participated in the Women's Health Initiative. Somatic copy number alterations showed little variation by smoking status, suggesting that aneuploidy may be a general characteristic of lung cancer regardless of smoke exposure. Similarly, clock-like and APOBEC mutation signatures were prevalent but did not differ in tumors from smokers and never-smokers. However, mutations in both EGFR and KRAS showed unique allelic differences determined by smoking status that are known to alter tumor response to targeted therapy. Mutations in the MYC-network member MGA were more prevalent in tumors from smokers. Fusion events in ALK, RET, and ROS1 were absent, likely due to age-related differences in fusion prevalence. Our work underscores the profound effect of smoking status, age, and sex on the tumor mutational landscape and identifies areas of unmet medical need.

Copy number losses of oncogenes and gains of tumor suppressor genes generate common driver mutations

Cancer driver genes can undergo positive selection for various types of genetic alterations, including gain-of-function or loss-of-function mutations and copy number alterations (CNA). We investigated the landscape of different types of alterations affecting driver genes in 17,644 cancer exomes and genomes. We find that oncogenes may simultaneously exhibit signatures of positive selection and also negative selection in different gene segments, suggesting a method to identify additional tumor types where an oncogene is a driver or a vulnerability. Next, we characterize the landscape of CNA-dependent selection effects, revealing a general trend of increased positive selection on oncogene mutations not only upon CNA gains but also upon CNA deletions. Similarly, we observe a positive interaction between mutations and CNA gains in tumor suppressor genes. Thus, two-hit events involving point mutations and CNA are universally observed regardless of the type of CNA and may signal new therapeutic opportunities. An analysis with focus on the somatic CNA two-hit events can help identify additional driver genes relevant to a tumor type. By a global inference of point mutation and CNA selection signatures and interactions thereof across genes and tissues, we identify 9 evolutionary archetypes of driver genes, representing different mechanisms of (in)activation by genetic alterations.