The cytidine deaminase APOBEC3C has unique sequence and genome feature preferences.

APOBEC proteins are cytidine deaminases that restrict the replication of viruses and transposable elements. Several members of the APOBEC3 family, APOBEC3A, APOBEC3B, and APOBEC3H-I, can access the nucleus and cause what is thought to be indiscriminate deamination of the genome, resulting in mutagenesis and genome instability. Although APOBEC3C is also present in the nucleus, the full scope of its deamination target preferences is unknown. By expressing human APOBEC3C in a yeast model system, I have defined the APOBEC3C mutation signature, as well as the preferred genome features of APOBEC3C targets. The APOBEC3C mutation signature is distinct from those of the known cancer genome mutators APOBEC3A and APOBEC3B. APOBEC3C produces DNA strand-coordinated mutation clusters, and APOBEC3C mutations are enriched near the transcription start sites of active genes. Surprisingly, APOBEC3C lacks the bias for the lagging strand of DNA replication that is seen for APOBEC3A and APOBEC3B. The unique preferences of APOBEC3C constitute a mutation profile that will be useful in defining sites of APOBEC3C mutagenesis in human genomes.

Beyond driver mutations: exploring the landscape of mutational signatures in adenocarcinomas of the bladder†.

The emergence of mutational signatures in cancer research represents a paradigm shift, offering profound insights into tumor biology, therapeutic strategies, and risk assessment. A recent article published in The Journal of Pathology delves into the significance of mutational signatures, assessing their role as molecular fingerprints that illuminate the etiology of individual cancer cases. By deciphering the diverse patterns of DNA alterations, in the context of urachal and nonurachal bladder adenocarcinomas, researchers can unravel intrinsic and environmental risk factors shaping cancer development. The study highlighted a predominance of environmental risk factors in Chinese populations affected by bladder adenocarcinomas. In this context, in this commentary, we highlight some of the potential applications of molecular signatures in differential diagnosis and therapy prediction. As the field continues to evolve, a deeper understanding of mutational signatures promises to revolutionize precision oncology by offering personalized approaches informed by comprehensive mutational patterns of tumors. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The mutagenic consequences of defective DNA repair.

Multiple separate repair mechanisms safeguard the genome against various types of DNA damage, and their failure can increase the rate of spontaneous mutagenesis. The malfunction of distinct repair mechanisms leads to genomic instability through different mutagenic processes. For example, defective mismatch repair causes high base substitution rates and microsatellite instability, whereas homologous recombination deficiency is characteristically associated with deletions and chromosome instability. This review presents a comprehensive collection of all mutagenic phenotypes associated with the loss of each DNA repair mechanism, drawing on data from a variety of model organisms and mutagenesis assays, and placing greatest emphasis on systematic analyses of human cancer datasets. We describe the latest theories on the mechanism of each mutagenic process, often explained by reliance on an alternative repair pathway or the error-prone replication of unrepaired, damaged DNA. Aided by the concept of mutational signatures, the genomic phenotypes can be used in cancer diagnosis to identify defective DNA repair pathways.

Prognostic mutation signature would serve as a potential prognostic predictor in patients with diffuse large B-cell lymphoma.

The present study aimed to elucidate the prognostic mutation signature (PMS) associated with long-term survival in a diffuse large B-cell lymphoma (DLBCL) cohort. All data including derivation and validation cohorts were retrospectively retrieved from The Cancer Genome Atlas (TCGA) database and whole-exome sequencing (WES) data. The Lasso Cox regression analysis was used to construct the PMS based on WES data, and the PMS was determined using the area under the receiver operating curve (AUC). The predictive performance of eligible PMS was analyzed by time-dependent receiver operating curve (ROC) analyses. After the initial evaluation, a PMS composed of 94 PFS-related genes was constructed. Notably, this constructed PMS accurately predicted the 12-, 36-, and 60-month PFS, with AUC values of 0.982, 0.983, and 0.987, respectively. A higher level of PMS was closely linked to a significantly worse PFS, regardless of the molecular subtype. Further evaluation by forest plot revealed incorporation of international prognostic index or tumor mutational burden into PMS increased the prediction capability for PFS. The drug-gene interaction and pathway exploration revealed the PFS-related genes were associated with DNA damage, TP53, apoptosis, and immune cell functions. In conclusion, this study utilizing a high throughput genetic approach demonstrated that the PMS could serve as a prognostic predictor in DLBCL patients. Furthermore, the identification of the key signaling pathways for disease progression also provides information for further investigation to gain more insight into novel drug-resistant mechanisms.

Molecular profiling and prognostic analysis in Chinese cholangiocarcinoma: an observational, retrospective single-center study.

Cholangiocarcinoma (CCA) is a primary malignancy which is often diagnosed when it is advanced and inoperable due to the lack of effective biomarkers and poor sensitivity of clinical diagnosis. Molecular profiling may provide information for improved clinical management, particularly targeted therapy. The study aimed to improve the understanding of molecular characteristics and its association with prognosis in Chinese CCA. We enrolled 41 Chinese patients with CCA, including 6 intrahepatic CCA (iCCA), 14 perihilar CCA (pCCA), and 21 distal CCA (dCCA) cases, all patients underwent radical operations and tumor samples underwent next-generation sequencing (NGS) by Foundation One Dx, which analyzed 324 genes. The patients' genetic characteristics, clinical management, and prognosis were analyzed. The most mutated genes were TP53 (68%, 28/41), CDKN2A (37%, 15/41), and SMAD4 (29%, 12/41). The genetic mutations in dCCA, pCCA, and iCCA were significantly different. For example, NOTCH3 mutations were not found in dCCA. The gene mutations of AXL were specifically associated with lymph node metastasis in patients with CCA, whereas gene mutations of SMAD4 were specifically associated with lymphovascular invasion. Furthermore, mutations in APC, DAXX, FANCA, LTK, MAP2K4, and NOTCH1 were associated with a poor prognosis (P < 0.05). This study provides an overview of genetic alterations in Chinese patients with CCA, which will provide novel potential biomarkers for the diagnosis of CCA and may guide targeted therapeutic strategies for Chinese patients with CCA.

The Prognosis Performance of a Neutrophil- and Lymphocyte-Associated Gene Mutation Score in a Head and Neck Cancer Cohort.

The treatment of head and neck squamous cell carcinomas (HNSCCs) is multimodal, and chemoradiotherapy (CRT) is a critical component. However, the availability of predictive or prognostic markers in patients with HNSCC is limited. Inflammation is a well-documented factor in cancer, and several parameters have been studied, with the neutrophil-to-lymphocyte ratio (NLR) being the most promising. The NLR is the most extensively researched clinical biomarker in various solid tumors, including HNSCC. In our study, we collected clinical and next-generation sequencing (NGS) data with targeted sequencing information from 107 patients with HNSCC who underwent CRT. The difference in the NLR between the good response group and the poor response group was significant, with more patients having a high NLR in the poor response group. We also examined the genetic alterations linked to the NLR and found a total of 41 associated genes across eight common pathways searched from the KEGG database. The overall mutation rate was low, and there was no significant mutation difference between the low- and high-NLR groups. Using a multivariate binomial generalized linear model, we identified three candidate genes (MAP2K2, MAP2K4, and ABL1) that showed significant results and were used to create a gene mutation score (GMS). Using the NLR-GMS category, we noticed that the high-NLR-GMS group had significantly shorter relapse-free survival compared to the intermediate- or low-NLR-GMS groups.

A 20-gene mutation signature predicts the efficacy of immune checkpoint inhibitor therapy in advanced non-small cell lung cancer patients.

BACKGROUND: There is an unmet need to identify novel predictive biomarkers that enable more accurate identification of individuals who can benefit from immune checkpoint inhibitor (ICI) therapy. The US FDA recently approved tumor mutational burden (TMB) score of ≥ 10 mut/Mb as a threshold for pembrolizumab treatment of solid tumors. Our study aimed to test the hypothesis that specific gene mutation signature may predict the efficacy of ICI therapy more precisely than high TMB (≥ 10). METHODS: We selected 20 candidate genes that may predict for the efficacy of ICI therapy by the analysis of data from a published cohort of 350 advanced non-small cell lung cancer (NSCLC) patients. Then, we compared the influences of various gene mutation signatures on the efficacy of ICI treatment. They were also compared with PD-L1 and TMB. The Kaplan-Meier method was utilized to evaluate the prognosis univariates, while selected univariates were adopted to develop a systematic nomogram. RESULTS: A high mutation signature, where three or more of the 20 selected genes were mutated, was associated with the significant benefits of ICI therapy. Specifically, patients with high mutation signature were confirmed to have better prognosis for ICI treatment, compared with those with wild type (the median PFS: 7.17 vs. 2.90 months, p = 0.0004, HR = 0.47 (95% [CI]:0.32-0.68); the median OS: unreached vs. 9 months, p = 1.8E-8, HR = 0.17 (95% [CI]:0.11-0.25)). Moreover, those patients with the high mutation signature achieved significant ICI treatment benefits, while there was no difference of OS and PFS between patients without the signature but TMB-H (≥ 10) and those without the signature and low TMB(< 10). Finally, we constructed a novel nomogram to evaluate the efficacy of ICI therapy. CONCLUSION: A high mutational signature with 3 or more of the 20-gene panel could provide more accurate predictions for the outcomes of ICI therapy than TMB ≥ 10 in NSCLC patients.

Comparing Genomic Landscapes of Oral and Cutaneous Squamous Cell Carcinoma of the Head and Neck: Quest for Novel Diagnostic Markers.

Squamous cell carcinoma is the most common head and neck malignancy arising from the oral mucosa and the skin. The histologic and immunohistochemical features of oral squamous cell carcinoma (OSCC) and head and neck cutaneous squamous cell carcinoma (HNcSCC) are similar, making it difficult to identify the primary site in cases of metastases. With the advent of immunotherapy, reliable distinction of OSCC and HNcSCC at metastatic sites has important treatment and prognostic implications. Here, we investigate and compare the genomic landscape of OSCC and HNcSCC to identify diagnostically useful biomarkers. Whole-genome sequencing data from 57 OSCC and 41 HNcSCC patients were obtained for tumor and matched normal samples. Tumor mutation burden (TMB), Catalogue of Somatic Mutations in Cancer (COSMIC) mutational signatures, frequent chromosomal alterations, somatic single nucleotide, and copy number variations were analyzed. The median TMB of 3.75 in primary OSCC was significantly lower (P < .001) than that of 147.51 mutations/Mb in primary HNcSCC. The COSMIC mutation signatures were significantly different (P < .001) between OSCC and HNcSCC. OSCC showed COSMIC single-base substitution (SBS) mutation signature 1 and AID/APOBEC activity-associated signature 2 and/or 13. All except 1 HNcSCC from hair-bearing scalp showed UV damage-associated COSMIC SBS mutation signature 7. Both OSCC and HNcSCC demonstrated a predominance of tumor suppressor gene mutations, predominantly TP53. The most frequently mutated oncogenes were PIK3CA and MUC4 in OSCC and HNcSCC, respectively. The metastases of OSCC and HNcSCC demonstrated TMB and COSMIC SBS mutation signatures similar to their primary counterparts. The combination of high TMB and UV signature in a metastatic keratinizing squamous cell carcinoma suggests HNcSCC as the primary site and may also facilitate decisions regarding immunotherapy. HNcSCC and OSCC show distinct genomic profiles despite histologic and immunohistochemical similarities. Their genomic characteristics may underlie differences in behavior and guide treatment decisions in recurrent and metastatic settings.

A pathway-based mutation signature to predict the clinical outcomes and response to CTLA-4 inhibitors in melanoma.

Immune checkpoint inhibitor (ICI) therapy has become a powerful clinical strategy for treating melanoma. The relationship between somatic mutations and the clinical benefits of immunotherapy has been widely recognized. However, the gene-based predictive biomarkers are less stable due to the heterogeneity of cancer at the individual gene level. Recent studies have suggested that the accumulation of gene mutations in biological pathways may activate antitumor immune responses. Herein, a novel pathway mutation signature (PMS) was constructed to predict the survival and efficacy of ICI therapy. In a dataset of melanoma patients treated with anti-CTLA-4, we mapped the mutated genes into the pathways and then identified seven significant mutation pathways associated with survival and immunotherapy response, which were used to construct the PMS model. According to the PMS model, the patients in the PMS-high group showed better overall survival (hazard ratio (HR) = 0.37; log-rank test, p < 0.0001) and progression-free survival (HR = 0.52; log-rank test, p = 0.014) than those in the PMS-low group. The PMS-high patients also showed a significantly higher objective response rate to anti-CTLA-4 therapy than the PMS-low patients (Fisher's exact test, p = 0.0055), and the predictive power of the PMS model was superior to that of TMB. Finally, the prognostic and predictive value of the PMS model was validated in two independent validation sets. Our study demonstrated that the PMS model can be considered a potential biomarker to predict the clinical outcomes and response to anti-CTLA-4 therapy in melanoma patients.

Prognosis and Personalized Treatment Prediction in Different Mutation-Signature Hepatocellular Carcinoma.

Introduction: Mutation patterns have been extensively explored to decipher the etiologies of hepatocellular carcinoma (HCC). However, the study and potential clinical role of mutation patterns to stratify high-risk patients and optimize precision therapeutic strategies remain elusive in HCC. Methods: Using exon-sequencing data in public (n=362) and in-house (n=30) cohorts, mutation signatures were extracted to decipher relationships with the etiology and prognosis in HCC. The proteomics (n=159) and cell-line transcriptome data (n=1019) were collected to screen the implication of sensitive drugs. A novel multi-step machine-learning framework was then performed to construct a classification predictor, including recognizing stable reversed gene pairs, establishing a robust prediction model, and validating the robustness of the predictor in five independent cohorts (n=900). Results: Two heterogeneous mutation signature clusters were identified, and a high-risk prognosis cluster was recognized for further analysis. Notably, mutation signature cluster 1 (MSC1) was featured by activated anti-tumor immune and metabolism dysfunctional states, higher genomic instability (high TMB, SNV neoantigen, indel neoantigens, and total neoantigens), and a dismal prognosis. Notably, MSC performed as an independent risk factor than clinical traits (eg, stage, vascular invasion). Additionally, afatinib and canertinib were recognized which might have potential therapeutic implications in MSC1, and the targets of these drugs presented a higher expression in both gene and protein levels in HCC. Discussion: Our studies may provide a promising platform for improving prognosis and tailoring therapy in HCC.

Non-CpG sites preference in G:C > A:T transition of TP53 in gastric cancer of Eastern Europe (Poland, Romania and Hungary) compared to East Asian countries (China and Japan).

AIM: Mutation spectrum of TP53 in gastric cancer (GC) has been investigated world-widely, but a comparison of mutation spectrum among GCs from various regions in the world are still sparsely documented. In order to identify the difference of TP53 mutation spectrum in GCs in Eastern Europe and in East Asia, we sequenced TP53 in GCs from Eastern Europe, Lujiang (China), and Yokohama, Kanagawa (Japan) and identified the feature of TP53 mutations of GC in these regions. SUBJECTS AND METHOD: In total, 689 tissue samples of GC were analyzed: 288 samples from East European populations (25 from Hungary, 71 from Poland and 192 from Romania), 268 from Yokohama, Kanagawa, Japan and 133 from Lujiang, Anhui province, China. DNA was extracted from FFPE tissue of Chinese, East European cases; and from frozen tissue of Japanese GCs. PCR products were direct-sequenced by Sanger method, and in ambiguous cases, PCR product was cloned and up to 8 clones were sequenced. We used No. NC_000017.11(hg38) as the reference sequence of TP53. Mutation patterns were categorized into nine groups: six base substitutions, insertion, deletion and deletion-insertion. Within G:C > A:T mutations the mutations in CpG and non-CpG sites were divided. The Cancer Genome Atlas data (TCGA, ver.R20, July, 2019) having somatic mutation list of GCs from Whites, Asians, and other ethnicities were used as a reference for our data. RESULTS: The most frequent base substitutions were G:C > A:T transition in all the areas investigated. The G:C > A:T transition in non-CpG sites were prominent in East European GCs, compared with Asian ones. Mutation pattern from TCGA data revealed the same trend between GCs from White (TCGA category) vs Asian countries. Chinese and Japanese GCs showed higher ratio of G:C > A:T transition in CpG sites and A:T > G:C mutation was more prevalent in Asian countries. CONCLUSION: The divergence in mutation spectrum of GC in different areas in the world may reflect various pathogeneses and etiologies of GC, region to region. Diversified mutation spectrum in GC in Eastern Europe may suggest GC in Europe has different carcinogenic pathway of those from Asia.

The two faces of DNA oxidation in genomic and functional mosaicism during aging in human neurons.

Maintaining genomic integrity in post-mitotic neurons in the human brain is paramount because these cells must survive for an individual's entire lifespan. Due to life-long synaptic plasticity and electrochemical transmission between cells, the brain engages in an exceptionally high level of mitochondrial metabolic activity. This activity results in the generation of reactive oxygen species with 8-oxo-7,8-dihydroguanine (8-oxoG) being one of the most prevalent oxidation products in the cell. 8-oxoG is important for the maintenance and transfer of genetic information into proper gene expression: a low basal level of 8-oxoG plays an important role in epigenetic modulation of neurodevelopment and synaptic plasticity, while a dysregulated increase in 8-oxoG damages the genome leading to somatic mutations and transcription errors. The slow yet persistent accumulation of DNA damage in the background of increasing cellular 8-oxoG is associated with normal aging as well as neurological disorders such as Alzheimer's disease and Parkinson's disease. This review explores the current understanding of how 8-oxoG plays a role in brain function and genomic instability, highlighting new methods being used to advance pathological hallmarks that differentiate normal healthy aging and neurodegenerative disease.

Identification and validation of a genomic mutation signature as a predictor for immunotherapy in NSCLC.

Currently, the benefits of immune checkpoint inhibitor (ICI) therapy prediction via emerging biomarkers have been identified, and the association between genomic mutation signatures (GMS) and immunotherapy benefits has been widely recognized as well. However, the evidence about non-small cell lung cancer (NSCLC) remains limited. We analyzed 310 immunotherapy patients with NSCLC from the Memorial Sloan Kettering Cancer Center (MSKCC) cohort. Lasso Cox regression was used to construct a GMS, and the prognostic value of GMS could be able to verify in the Rizvi cohort (N=240) and Hellmann cohort (N=75). We further conducted immunotherapy-related characteristics analysis in The Cancer Genome Atlas (TCGA) cohort (N=1052). A total of seven genes (ZFHX3, NTRK3, EPHA7, MGA, STK11, EPHA5, TP53) were identified for GMS model construction. Compared with GMS-high patients, patients with GMS-low had longer overall survival (OS; P<0.001) in the MSKCC cohort and progression-free survival (PFS; P<0.001) in the validation cohort. Multivariate Cox analysis revealed that GMS was an independent predictive factor for NSCLC patients in both the MSKCC and validation cohort. Meanwhile, we found that GMS-low patients reflected enhanced antitumor immunity in TCGA cohort. The results indicated that GMS had not only potential predictive value for the benefit of immunotherapy but also may serve as a potential biomarker to guide clinical ICI treatment decisions for NSCLC.

Pancancer analysis of a potential gene mutation model in the prediction of immunotherapy outcomes.

Background: Immune checkpoint blockade (ICB) represents a promising treatment for cancer, but predictive biomarkers are needed. We aimed to develop a cost-effective signature to predict immunotherapy benefits across cancers. Methods: We proposed a study framework to construct the signature. Specifically, we built a multivariate Cox proportional hazards regression model with LASSO using 80% of an ICB-treated cohort (n = 1661) from MSKCC. The desired signature named SIGP was the risk score of the model and was validated in the remaining 20% of patients and an external ICB-treated cohort (n = 249) from DFCI. Results: SIGP was based on 18 candidate genes (NOTCH3, CREBBP, RNF43, PTPRD, FAM46C, SETD2, PTPRT, TERT, TET1, ROS1, NTRK3, PAK7, BRAF, LATS1, IL7R, VHL, TP53, and STK11), and we classified patients into SIGP high (SIGP-H), SIGP low (SIGP-L) and SIGP wild type (SIGP-WT) groups according to the SIGP score. A multicohort validation demonstrated that patients in SIGP-L had significantly longer overall survival (OS) in the context of ICB therapy than those in SIGP-WT and SIGP-H (44.00 months versus 13.00 months and 14.00 months, p < 0.001 in the test set). The survival of patients grouped by SIGP in non-ICB-treated cohorts was different, and SIGP-WT performed better than the other groups. In addition, SIGP-L + TMB-L (approximately 15% of patients) had similar survivals to TMB-H, and patients with both SIGP-L and TMB-H had better survival. Further analysis on tumor-infiltrating lymphocytes demonstrated that the SIGP-L group had significantly increased abundances of CD8+ T cells. Conclusion: Our proposed model of the SIGP signature based on 18-gene mutations has good predictive value for the clinical benefit of ICB in pancancer patients. Additional patients without TMB-H were identified by SIGP as potential candidates for ICB, and the combination of both signatures showed better performance than the single signature.

APOBEC-Induced Mutagenesis in Cancer.

The initiation, progression, and relapse of cancers often result from mutations occurring within somatic cells. Consequently, processes that elevate mutation rates accelerate carcinogenesis and hinder the development of long-lasting therapeutics. Recent sequencing of human cancer genomes has identified patterns of mutations, termed mutation signatures, many of which correspond to specific environmentally induced and endogenous mutation processes. Some of the most frequently observed mutation signatures are caused by dysregulated activity of APOBECs, which deaminate cytidines in single-stranded DNA at specific sequence motifs causing C-to-T and C-to-G substitutions. In humans, APOBEC-generated genetic heterogeneity in tumor cells contributes to carcinogenesis, metastasis, and resistance to therapeutics. Here, we review the current understanding of APOBECs' role in cancer mutagenesis and impact on disease and the biological processes that influence APOBEC mutagenic capacity.

Duplex sequencing identifies genomic features that determine susceptibility to benzo(a)pyrene-induced in vivo mutations.

Exposure to environmental mutagens increases the risk of cancer and genetic disorders. We used Duplex Sequencing (DS), a high-accuracy error-corrected sequencing technology, to analyze mutation induction across twenty 2.4 kb intergenic and genic targets in the bone marrow of MutaMouse males exposed to benzo(a)pyrene (BaP), a widespread environmental pollutant. DS revealed a linear dose-related induction of mutations across all targets with low intra-group variability. Heterochromatic and intergenic regions exhibited the highest mutation frequencies (MF). C:G > A:T transversions at CCA, CCC and GCC trinucleotides were enriched in BaP-exposed mice consistent with the known etiology of BaP mutagenesis. However, GC-content had no effect on mutation susceptibility. A positive correlation was observed between DS and the "gold-standard" transgenic rodent gene mutation assay. Overall, we demonstrate that DS is a promising approach to study in vivo mutagenesis and yields critical insight into the genomic features governing mutation susceptibility, spectrum, and variability across the genome.

Mutation signatures to Pan-Cancer Atlas: Investigation of the genomic landscape of muscle-invasive bladder cancer.

The Cancer Genome Atlas (TCGA) for bladder cancer was published in 2014 with updated annotation of over 400 patients with muscle-invasive bladder cancer (MIBC) in 2017. This tremendous work established the foundation of the genomic landscape of MIBC. The next steps to utilize information from The Cancer Genome Atlas is to (1) identify the causes of mutation, (2) determine the significant differences and sources of heterogeneity, and (3) apply these tools toward patient care. In this review, we discuss the full spectrum of the genomic landscape of MIBC toward the goal of therapeutic application.

Gaining insights into relevance across cancers based on mutation features of TP53 gene.

The tumor suppressor gene TP53, one of the most frequently mutated genes, is recognized as the guardian of genome and can provide a significant barrier to neoplastic transformation and tumor progression. Traditional theory believes that TP53 mutations are equal among cancer types. However, to date, no study has explored the TP53 mutation profile from a holistic and systematic standpoint to discovery its relevance and feature with cancers. Mutation signature, an unbiased approach to identify the mutational processes, can be a potent indicator for exploring mutation-driven tumor occurrence and progression. In this research, several features such as hotspots, mutability and mutation signature of somatic TP53 mutations derived from 18 types of cancer tissues from cBioPortal were analyzed and manifested the organizational preference among cancers. Mutation signatures found in almost all cancer types were Signature 6 related to mismatch repair deficiency, and Signature 1 that reflects the natural decomposition of 5-methylcytosine into thymine associated with aging. Meanwhile, several signatures of TP53 mutations displayed tissue-selective. Mutations enriched in bladder, skin, lung cancer were associated with signatures of APOBEC activity (Signature 2 and 13), alkylating agents (Signature 11), and tobacco smoke (Signature 4), respectively. Moreover, Signature 4 and 29 associated with tobacco smoking or chewing found in lung, sarcoma, esophageal, and head and neck cancer may be related to their smoking history. In addition, several digestive cancers, including colorectal, stomach, pancreatic and esophageal cancers, showed the high correlation in context and mutation signature profiles. Our study suggests that the tissue-selective activity of mutational processes would reflect the tissue-specific enrichment of TP53 mutations and provides a new perspective to understand the relevance of diverse diseases based on the spectrum of TP53 mutations.

Genetic alteration and clonal evolution of primary glioblastoma into secondary gliosarcoma.

AIMS: Secondary gliosarcoma (SGS) rarely arises post treatment of primary glioblastoma multiforme (GBM), and contains gliomatous and sarcomatous components. The origin and clonal evolution of SGS sarcomatous components remain uncharacterized. Therapeutic radiation is mutagenic and can induce sarcomas in patients with other tumor phenotypes, but possible causal relationships between radiotherapy and induction of SGS sarcomatous components remain unexplored. Herein, we investigated the clonal origin of SGS in a patient with primary GBM progressing into SGS post-radiochemotherapy. METHODS: Somatic mutation profile in GBM and SGS was examined using whole-genome sequencing and deep-whole-exome sequencing. Mutation signatures were characterized to investigate relationships between radiochemotherapy and SGS pathogenesis. RESULTS: A mutation cluster containing two founding mutations in tumor-suppressor genes NF1 (variant allele frequency [VAF]: 50.0% in GBM and 51.1% in SGS) and TP53 (VAF: 26.7% in GBM and 50.8% in SGS) was shared in GBM and SGS. SGS exhibited an overpresented C>A (G>T) transversion (oxidative DNA damage signature) but no signature 11 mutations (alkylating-agents - exposure signature). Since radiation induces DNA lesions by generating reactive oxygen species, the mutations observed in this case of SGS were likely the result of radiotherapy rather than chemotherapy. CONCLUSIONS: Secondary gliosarcoma components likely have a monoclonal origin, and the clone possessing mutations in NF1 and TP53 was likely the founding clone in this case of SGS.