Genomic profiles of Japanese patients with vulvar squamous cell carcinoma.

The incidence of vulvar carcinoma varies by race; however, it is a rare disease, and its genomic profiles remain largely unknown. This study examined the characteristics of vulvar squamous cell carcinoma (VSCC) in Japanese patients, focusing on genomic profiles and potential racial disparities. The study included two Japanese groups: the National Cancer Center Hospital (NCCH) group comprised 19 patients diagnosed between 2015 and 2023, and the Center for Cancer Genomics and Advanced Therapeutics group comprised 29 patients diagnosed between 2019 and 2022. Somatic mutations were identified by targeted or panel sequencing, and TP53 was identified as the most common mutation (52-81%), followed by HRAS (7-26%), CDKN2A (21-24%), and PIK3CA (5-10%). The mutation frequencies, except for TP53, were similar to those of Caucasian cohorts. In the NCCH group, 16 patients of HPV-independent tumors were identified by immunohistochemistry and genotyping. Univariate analysis revealed that TP53-mutated patients were associated with a poor prognosis (log-rank test, P = 0.089). Japanese VSCC mutations resembled those of Caucasian vulvar carcinomas, and TP53 mutations predicted prognosis regardless of ethnicity. The present findings suggest potential molecular-targeted therapies for select VSCC patients.

Mechanism of ERBB2 gene overexpression by the formation of super-enhancer with genomic structural abnormalities in lung adenocarcinoma without clinically actionable genetic alterations.

BACKGROUND: In an extensive genomic analysis of lung adenocarcinomas (LUADs), driver mutations have been recognized as potential targets for molecular therapy. However, there remain cases where target genes are not identified. Super-enhancers and structural variants are frequently identified in several hundred loci per case. Despite this, most cancer research has approached the analysis of these data sets separately, without merging and comparing the data, and there are no examples of integrated analysis in LUAD. METHODS: We performed an integrated analysis of super-enhancers and structural variants in a cohort of 174 LUAD cases that lacked clinically actionable genetic alterations. To achieve this, we conducted both WGS and H3K27Ac ChIP-seq analyses using samples with driver gene mutations and those without, allowing for a comprehensive investigation of the potential roles of super-enhancer in LUAD cases. RESULTS: We demonstrate that most genes situated in these overlapped regions were associated with known and previously unknown driver genes and aberrant expression resulting from the formation of super-enhancers accompanied by genomic structural abnormalities. Hi-C and long-read sequencing data further corroborated this insight. When we employed CRISPR-Cas9 to induce structural abnormalities that mimicked cases with outlier ERBB2 gene expression, we observed an elevation in ERBB2 expression. These abnormalities are associated with a higher risk of recurrence after surgery, irrespective of the presence or absence of driver mutations. CONCLUSIONS: Our findings suggest that aberrant gene expression linked to structural polymorphisms can significantly impact personalized cancer treatment by facilitating the identification of driver mutations and prognostic factors, contributing to a more comprehensive understanding of LUAD pathogenesis.

Clinical features and impact of p53 status on sporadic mismatch repair deficiency and Lynch syndrome in uterine cancer.

The clinical features of sporadic mismatch repair deficiency (MMRd) and Lynch syndrome (LS) in Japanese patients with endometrial cancer (EC) were examined by evaluating the prevalence and prognostic factors of LS and sporadic MMRd in patients with EC. Targeted sequencing of five LS susceptibility genes (MLH1, MSH2, MSH6, PMS2, and EPCAM) was carried out in 443 patients with EC who were pathologically diagnosed with EC at the National Cancer Center Hospital between 2011 and 2018. Pathogenic variants in these genes were detected in 16 patients (3.7%). Immunohistochemistry for MMR proteins was undertaken in 337 of the 433 (77.9%) EC patients, and 91 patients (27.0%) showed absent expression of at least one MMR protein. The 13 cases of LS with MMR protein loss (93.8%) showed a favorable prognosis with a 5-year overall survival (OS) rate of 100%, although there was no statistically significant difference between this group and the sporadic MMRd group (p = 0.27). In the MMRd without LS group, the 5-year OS rate was significantly worse in seven patients with an aberrant p53 expression pattern than in those with p53 WT (53.6% vs. 93.9%, log-rank test; p = 0.0016). These results suggest that p53 abnormalities and pathogenic germline variants in MMR genes could be potential biomarkers for the molecular classification of EC with MMRd.

Advances in cancer DNA methylation analysis with methPLIER: use of non-negative matrix factorization and knowledge-based constraints to enhance biological interpretability.

DNA methylation is an epigenetic modification that results in dynamic changes during ontogenesis and cell differentiation. DNA methylation patterns regulate gene expression and have been widely researched. While tools for DNA methylation analysis have been developed, most of them have focused on intergroup comparative analysis within a dataset; therefore, it is difficult to conduct cross-dataset studies, such as rare disease studies or cross-institutional studies. This study describes a novel method for DNA methylation analysis, namely, methPLIER, which enables interdataset comparative analyses. methPLIER combines Pathway Level Information Extractor (PLIER), which is a non-negative matrix factorization (NMF) method, with regularization by a knowledge matrix and transfer learning. methPLIER can be used to perform intersample and interdataset comparative analysis based on latent feature matrices, which are obtained via matrix factorization of large-scale data, and factor-loading matrices, which are obtained through matrix factorization of the data to be analyzed. We used methPLIER to analyze a lung cancer dataset and confirmed that the data decomposition reflected sample characteristics for recurrence-free survival. Moreover, methPLIER can analyze data obtained via different preprocessing methods, thereby reducing distributional bias among datasets due to preprocessing. Furthermore, methPLIER can be employed for comparative analyses of methylation data obtained from different platforms, thereby reducing bias in data distribution due to platform differences. methPLIER is expected to facilitate cross-sectional DNA methylation data analysis and enhance DNA methylation data resources.

Passive Smoking-Induced Mutagenesis as a Promoter of Lung Carcinogenesis.

INTRODUCTION: The International Agency for Research on Cancer has classified passive smoking (PS) or secondhand smoke exposure as a group 1 carcinogen linked to lung cancer. However, in contrast to active smoking, the mutagenic properties of PS remain unclear. METHODS: A consecutive cohort of 564 lung adenocarcinoma samples from female never-smokers, who provided detailed information about their exposure to PS during adolescence and in their thirties through a questionnaire, was prepared. Of these, all 291 cases for whom frozen tumor tissues were available were subjected to whole exome sequencing to estimate tumor mutational burden, and the top 84 cases who were exposed daily, or not, to PS during adolescence, in their thirties or in both periods, were further subjected to whole genome sequencing. RESULTS: A modest yet statistically significant increase in tumor mutational burden was observed in the group exposed to PS compared with the group not exposed to PS (median values = 1.44 versus 1.29 per megabase, respectively; p = 0.020). Instead of inducing driver oncogene mutations, PS-induced substantial subclonal mutations exhibiting APOBEC-type signatures, including SMAD4 and ADGRG6 hotspot mutations. A polymorphic APOBEC3A/3B allele-specific to the Asian population that leads to up-regulated expression of APOBEC3A accentuated the mutational load in individuals exposed daily to PS during adolescence. CONCLUSIONS: This study reveals that PS-induced mutagenesis can promote lung carcinogenesis. The APOBEC3A/3B polymorphism may serve as a biomarker for identifying passive nonsmoking individuals at high risk of developing lung cancer.

Histone methyltransferase SUV420H1/KMT5B contributes to poor prognosis in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) has a high rate of recurrence and poor prognosis, even after curative surgery. Multikinase inhibitors have been applied for HCC patients, but their effect has been restricted. This study aims to clarify the clinical impact of SUV420H1/KMT5B, one of the methyltransferases for histone H4 at lysine 20, and elucidate the novel mechanisms of HCC progression. We retrospectively investigated SUV420H1 expression using HCC clinical tissue samples employing immunohistochemical analysis (n = 350). We then performed loss-of-function analysis of SUV420H1 with cell cycle analysis, migration assay, invasion assay and RNA sequence for Gene Ontology (GO) pathway analysis in vitro, and animal experiments with xenograft mice in vivo. The SUV420H1-high-score group (n = 154) had significantly poorer prognosis for both 5-year overall and 2-year/5-year disease-free survival than the SUV420H1-low-score group (n = 196) (p < 0.001 and p < 0.05, respectively). The SUV420H1-high-score group had pathologically larger tumor size, more tumors, poorer differentiation, and more positive vascular invasion than the SUV420H1-low-score group. Multivariate analysis demonstrated that SUV420H1 high score was the poorest independent factor for overall survival. SUV420H1 knockdown could suppress cell cycle from G1 to S phase and cell invasion. GO pathway analysis showed that SUV420H1 contributed to cell proliferation, cell invasion, and/or metastasis. Overexpression of SUV420H1 clinically contributed to poor prognosis in HCC, and the inhibition of SUV420H1 could repress tumor progression and invasion both in vitro and in vivo; thus, further analyses of SUV420H1 are necessary for the discovery of future molecularly targeted drugs.

Sketch-based semantic retrieval of medical images.

The volume of medical images stored in hospitals is rapidly increasing; however, the utilization of these accumulated medical images remains limited. Existing content-based medical image retrieval (CBMIR) systems typically require example images, leading to practical limitations, such as the lack of customizable, fine-grained image retrieval, the inability to search without example images, and difficulty in retrieving rare cases. In this paper, we introduce a sketch-based medical image retrieval (SBMIR) system that enables users to find images of interest without the need for example images. The key concept is feature decomposition of medical images, which allows the entire feature of a medical image to be decomposed into and reconstructed from normal and abnormal features. Building on this concept, our SBMIR system provides an easy-to-use two-step graphical user interface: users first select a template image to specify a normal feature and then draw a semantic sketch of the disease on the template image to represent an abnormal feature. The system integrates both types of input to construct a query vector and retrieves reference images. For evaluation, ten healthcare professionals participated in a user test using two datasets. Consequently, our SBMIR system enabled users to overcome previous challenges, including image retrieval based on fine-grained image characteristics, image retrieval without example images, and image retrieval for rare cases. Our SBMIR system provides on-demand, customizable medical image retrieval, thereby expanding the utility of medical image databases.

A discrimination model by machine learning to avoid gastrectomy for early gastric cancer.

Aim: Gastrectomy is recommended for patients with early gastric cancer (EGC) because the possibility of lymph node metastasis (LNM) cannot be completely denied. The aim of this study was to develop a discrimination model to select patients who do not require surgery using machine learning. Methods: Data from 382 patients who received gastrectomy for gastric cancer and who were diagnosed with pT1b were extracted for developing a discrimination model. For the validation of this discrimination model, data from 140 consecutive patients who underwent endoscopic resection followed by gastrectomy, with a diagnosis of pT1b EGC, were extracted. We applied XGBoost to develop a discrimination model for clinical and pathological variables. The performance of the discrimination model was evaluated based on the number of cases classified as true negatives for LNM, with no false negatives for LNM allowed. Results: Lymph node metastasis was observed in 95 patients (25%) in the development cohort and 11 patients (8%) in the validation cohort. The discrimination model was developed to identify 27 (7%) patients with no indications for additional surgery due to the prediction of an LNM-negative status with no false negatives. In the validation cohort, 13 (9%) patients were identified as having no indications for additional surgery and no patients with LNM were classified into this group. Conclusion: The discrimination model using XGBoost algorithms could select patients with no risk of LNM from patients with pT1b EGC. This discrimination model was considered promising for clinical decision-making in relation to patients with EGC.

Integrative analysis reveals early epigenetic alterations in high-grade serous ovarian carcinomas.

High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecological malignancy. To date, the profiles of gene mutations and copy number alterations in HGSOC have been well characterized. However, the patterns of epigenetic alterations and transcription factor dysregulation in HGSOC have not yet been fully elucidated. In this study, we performed integrative omics analyses of a series of stepwise HGSOC model cells originating from human fallopian tube secretory epithelial cells (HFTSECs) to investigate early epigenetic alterations in HGSOC tumorigenesis. Assay for transposase-accessible chromatin using sequencing (ATAC-seq), chromatin immunoprecipitation sequencing (ChIP-seq), and RNA sequencing (RNA-seq) methods were used to analyze HGSOC samples. Additionally, protein expression changes in target genes were confirmed using normal HFTSECs, serous tubal intraepithelial carcinomas (STICs), and HGSOC tissues. Transcription factor motif analysis revealed that the DNA-binding activity of the AP-1 complex and GATA family proteins was dysregulated during early tumorigenesis. The protein expression levels of JUN and FOSL2 were increased, and those of GATA6 and DAB2 were decreased in STIC lesions, which were associated with epithelial-mesenchymal transition (EMT) and proteasome downregulation. The genomic region around the FRA16D site, containing a cadherin cluster region, was epigenetically suppressed by oncogenic signaling. Proteasome inhibition caused the upregulation of chemokine genes, which may facilitate immune evasion during HGSOC tumorigenesis. Importantly, MEK inhibitor treatment reversed these oncogenic alterations, indicating its clinical effectiveness in a subgroup of patients with HGSOC. This result suggests that MEK inhibitor therapy may be an effective treatment option for chemotherapy-resistant HGSOC.

Tumor microenvironment-mediated immune profiles and efficacy of anti-PD-L1 antibody plus chemotherapy stratified by DLL3 expression in small-cell lung cancer.

BACKGROUND: Delta-like ligand 3 (DLL3) is a therapeutic target in small-cell lung cancer (SCLC). However, how DLL3 expression status affects the tumor microenvironment (TME) and clinical outcomes in SCLC remains unclear. METHODS: This retrospective study included patients with postoperative limited-stage (LS)-SCLC and extensive-stage (ES)-SCLC treated with platinum and etoposide (PE) plus anti-programmed cell death ligand 1 (PD-L1) antibody. We investigated the relationship of DLL3 expression with TME, mutation status, tumor neoantigens, and immunochemotherapy. RESULTS: In the LS-SCLC cohort (n = 59), whole-exome sequencing revealed that DLL3High cases had significantly more neoantigens (P = 0.004) and a significantly higher rate of the signature SBS4 associated with smoking (P = 0.02) than DLL3Low cases. Transcriptome analysis in the LS-SCLC cohort revealed that DLL3High cases had significantly suppressed immune-related pathways and dendritic cell (DC) function. SCLC with DLL3High had significantly lower proportions of T cells, macrophages, and DCs than those with DLL3Low. In the ES-SCLC cohort (n = 30), the progression-free survival associated with PE plus anti-PD-L1 antibody was significantly worse in DLL3High cases than in DLL3Low cases (4.7 vs. 7.4 months, P = 0.01). CONCLUSIONS: Although SCLC with DLL3High had a higher neoantigen load, these tumors were resistant to immunochemotherapy due to suppressed tumor immunity by inhibiting antigen-presenting functions.

Rare FGFR fusion genes in cervical cancer and transcriptome-based subgrouping of patients with a poor prognosis.

BACKGROUND: Although cervical cancer is often characterized as preventable, its incidence continues to increase in low- and middle-income countries, underscoring the need to develop novel therapeutics for this disease.This study assessed the distribution of fusion genes across cancer types and used an RNA-based classification to divide cervical cancer patients with a poor prognosis into subgroups. MATERIAL AND METHODS: RNA sequencing of 116 patients with cervical cancer was conducted. Fusion genes were extracted using StarFusion program. To identify a high-risk group for recurrence, 65 patients who received postoperative adjuvant therapy were subjected to non-negative matrix factorization to identify differentially expressed genes between recurrent and nonrecurrent groups. RESULTS: We identified three cases with FGFR3-TACC3 and one with GOPC-ROS1 fusion genes as potential targets. A search of publicly available data from cBioPortal (21,789 cases) and the Center for Cancer Genomics and Advanced Therapeutics (32,608 cases) showed that the FGFR3 fusion is present in 1.5% and 0.6% of patients with cervical cancer, respectively. The frequency of the FGFR3 fusion gene was higher in cervical cancer than in other cancers, regardless of ethnicity. Non-negative matrix factorization identified that the patients were classified into four Basis groups. Pathway enrichment analysis identified more extracellular matrix kinetics dysregulation in Basis 3 and more immune system dysregulation in Basis 4 than in the good prognosis group. CIBERSORT analysis showed that the fraction of M1 macrophages was lower in the poor prognosis group than in the good prognosis group. CONCLUSIONS: The distribution of FGFR fusion genes in patients with cervical cancer was determined by RNA-based analysis and used to classify patients into clinically relevant subgroups.

A comprehensive appraisal of HER2 heterogeneity in HER2-amplified and HER2-low colorectal cancer.

BACKGROUND: This study aimed to elucidate the clinicopathological and molecular features of HER2-amplified and HER2-low colorectal cancers (CRCs). We also characterised HER2 expression statuses in CRCs focusing on their intratumoral heterogeneity and alterations in metastatic lesions to establish practical HER2 status assessment. METHODS: We evaluated 1009 CRCs for HER2 expression and HER2 amplification by immunohistochemistry and FISH, respectively, and correlated the results to clinicopathological and molecular data. For HER2-positive tumours, HER2 expression in metastatic lesions was also assessed. RESULTS: Twenty-five HER2-amplified (2.5%) and 46 HER2-low tumours (4.6%) were identified. HER2-amplified tumours consistently lacked a mucinous component and HER2-low tumours tended to be in the right colon, but no other clinicopathological features were noted. KRAS, NRAS or BRAF mutations were detected in only two HER2-amplified tumours (8%), whereas 23 HER2-low tumours (50%) had one of these mutations. Most HER2-amplified and HER2-low tumours showed a homogeneous or mosaic HER2 expression pattern and a clustered heterogeneous expression pattern was rather rare. HER2 expression was maintained in most metastatic lesions in both HER2-amplified (93%) and HER2-low tumours (81%). CONCLUSIONS: These results suggest that biopsy-based assessment of primary lesions is appropriate for the identification of CRC patients eligible for systemic HER2-targeted therapy.

An ATR-PrimPol pathway confers tolerance to oncogenic KRAS-induced and heterochromatin-associated replication stress.

Activation of the KRAS oncogene is a source of replication stress, but how this stress is generated and how it is tolerated by cancer cells remain poorly understood. Here we show that induction of KRASG12V expression in untransformed cells triggers H3K27me3 and HP1-associated chromatin compaction in an RNA transcription dependent manner, resulting in replication fork slowing and cell death. Furthermore, elevated ATR expression is necessary and sufficient for tolerance of KRASG12V-induced replication stress to expand replication stress-tolerant cells (RSTCs). PrimPol is phosphorylated at Ser255, a potential Chk1 substrate site, under KRASG12V-induced replication stress and promotes repriming to maintain fork progression and cell survival in an ATR/Chk1-dependent manner. However, ssDNA gaps are generated at heterochromatin by PrimPol-dependent repriming, leading to genomic instability. These results reveal a role of ATR-PrimPol in enabling precancerous cells to survive KRAS-induced replication stress and expand clonally with accumulation of genomic instability.

PROX1 induction by autolysosomal activity stabilizes persister-like state of colon cancer via feedback repression of the NOX1-mTORC1 pathway.

Cancer chemoresistance is often attributed to slow-cycling persister populations with cancer stem cell (CSC)-like features. However, how persister populations emerge and prevail in cancer remains obscure. We previously demonstrated that while the NOX1-mTORC1 pathway is responsible for proliferation of a fast-cycling CSC population, PROX1 expression is required for chemoresistant persisters in colon cancer. Here, we show that enhanced autolysosomal activity mediated by mTORC1 inhibition induces PROX1 expression and that PROX1 induction in turn inhibits NOX1-mTORC1 activation. CDX2, identified as a transcriptional activator of NOX1, mediates PROX1-dependent NOX1 inhibition. PROX1-positive and CDX2-positive cells are present in distinct populations, and mTOR inhibition triggers conversion of the CDX2-positive population to the PROX1-positive population. Inhibition of autophagy synergizes with mTOR inhibition to block cancer proliferation. Thus, mTORC1 inhibition-mediated induction of PROX1 stabilizes a persister-like state with high autolysosomal activity via a feedback regulation that involves a key cascade of proliferating CSCs.

Identification of inflamed-phenotype of small cell lung cancer leading to the efficacy of anti-PD-L1 antibody and chemotherapy.

BACKGROUND: Platinum etoposide plus anti-programmed cell death ligand-1 (PD-L1) antibody therapy is the standard of care for extensive-stage small cell lung cancer (ES-SCLC). However, patient characteristics associated with the efficacy of the combination therapy in SCLC are unclear. METHODS: We retrospectively reviewed post-surgical limited-stage (LS)-SCLC and ES-SCLC patients treated with atezolizumab plus carboplatin and etoposide (ACE). The association between SCLC subtypes based on transcriptomic data and pathological findings, including CD8-positive tumor-infiltrating lymphocyte (TIL) status, was investigated in the LS-SCLC cohort. The association between the efficacy of ACE therapy, pathological subtypes, and TIL status was evaluated in the ES-SCLC cohort. RESULTS: The LS-SCLC cohort (N = 48) was classified into four SCLC subtypes (ASCL1 + NEUROD1 [SCLC-A + N, N = 17], POU2F3 [SCLC-P, N = 15], YAP1 [SCLC-Y, N = 10], and inflamed [SCLC-I, N = 6]) based on transcriptomic data. SCLC-I showed enriched immune-related pathways, the highest immune score (CD8A expression and T-cell-inflamed gene expression profiles), and epithelial-mesenchymal transition (EMT), in transcriptional subtypes. Immunohistochemical staining (IHC) showed that SCLC-I had the highest density of CD8-positive TILs in transcriptional subtypes. In the ES-SCLC cohort, the efficacy of ACE therapy did not differ according to pathological subtypes. The progression-free survival (PFS) of TILHigh patients was significantly longer than that of TILLow patients (PFS: 7.3 months vs. 4.0 months, p < 0.001). CONCLUSION: Tumors with a high density of TILs, which represent the most immunogenic SCLC subtype (SCLC-I), based on transcriptomic data could benefit from ACE therapy.

Epigenetic regulation of SMAD3 by histone methyltransferase SMYD2 promotes lung cancer metastasis.

Epigenetic alterations, especially histone methylation, are key factors in cell migration and invasion in cancer metastasis. However, in lung cancer metastasis, the mechanism by which histone methylation regulates metastasis has not been fully elucidated. Here, we found that the histone methyltransferase SMYD2 is overexpressed in lung cancer and that knockdown of SMYD2 could reduce the rates of cell migration and invasion in lung cancer cell lines via direct downregulation of SMAD3 via SMYD2-mediated epigenetic regulation. Furthermore, using an in vitro epithelial-mesenchymal transition (EMT) system with a Transwell system, we generated highly invasive H1299 (In-H1299) cell lines and observed the suppression of metastatic features by SMYD2 knockdown. Finally, two types of in vivo studies revealed that the formation of metastatic tumors by shSMYD2 was significantly suppressed. Thus, we suggest that SMYD2 is a potential metastasis regulator and that the development of SMYD2-specific inhibitors may help to increase the efficacy of lung cancer treatment.

Analysis of super-enhancer using machine learning and its application to medical biology.

The analysis of super-enhancers (SEs) has recently attracted attention in elucidating the molecular mechanisms of cancer and other diseases. SEs are genomic structures that strongly induce gene expression and have been reported to contribute to the overexpression of oncogenes. Because the analysis of SEs and integrated analysis with other data are performed using large amounts of genome-wide data, artificial intelligence technology, with machine learning at its core, has recently begun to be utilized. In promoting precision medicine, it is important to consider information from SEs in addition to genomic data; therefore, machine learning technology is expected to be introduced appropriately in terms of building a robust analysis platform with a high generalization performance. In this review, we explain the history and principles of SE, and the results of SE analysis using state-of-the-art machine learning and integrated analysis with other data are presented to provide a comprehensive understanding of the current status of SE analysis in the field of medical biology. Additionally, we compared the accuracy between existing machine learning methods on the benchmark dataset and attempted to explore the kind of data preprocessing and integration work needed to make the existing algorithms work on the benchmark dataset. Furthermore, we discuss the issues and future directions of current SE analysis.

Comparison of clinicopathological and genomic profiles in anal squamous cell carcinoma between Japanese and Caucasian cohorts.

Anal squamous cell carcinoma (ASCC) is a rare tumor of the gastrointestinal tract. We aimed to compare the genetic backgrounds and their effect on clinical outcomes between Japanese and Caucasian patients with ASCC. Forty-one patients diagnosed with ASCC at the National Cancer Center Hospital were enrolled and evaluated for clinicopathological features, human papillomavirus (HPV) infection, HPV genotypes, p16 expression, PD-L1, and association of p16 status with the efficacy of concurrent chemoradiotherapy (CCRT). Target sequencing for hotspot mutations in 50 cancer-related genes was performed using genomic DNA from 30 available samples. Of 41 patients, 34 were HPV-positive (among them, HPV 16 was predominant; 73.2%); 38 patients were p16-positive (92.7%); and 39 patients received CCRT, of whom 36 were p16-positive and three p16-negative. p16-positive patients showed better complete response than p16-negative patients. Among 28 samples, 15 showed mutations in PIK3CA, FBXW7, ABL1, TP53, and PTEN; no difference in mutation profiles between the Japanese and Caucasian cohorts was observed. Actionable mutations were detected in both Japanese and Caucasian patients with ASCC. Genetic backgrounds, such as the HPV 16 genotype and PIK3CA mutations, were common regardless of ethnicity. p16 status may be a prognostic biomarker for CCRT in Japanese patients with ASCC.

Utility of molecular subtypes and genetic alterations for evaluating clinical outcomes in 1029 patients with endometrial cancer.

BACKGROUND: We investigated the utility of a molecular classifier tool and genetic alterations for predicting prognosis in Japanese patients with endometrial cancer. METHODS: A total of 1029 patients with endometrial cancer from two independent cohorts were classified into four molecular subtype groups. The primary and secondary endpoints were relapse-free survival (RFS) and overall survival (OS), respectively. RESULTS: Among the 265 patients who underwent initial surgery, classified according to immunohistochemistry, patients with DNA polymerase epsilon exonuclease domain mutation had an excellent prognosis (RFS and OS), patients with no specific molecular profile (NSMP) and mismatch repair protein deficiency had an intermediate prognosis, and those with protein 53 abnormal expression (p53abn) had the worst prognosis (P < 0.001). In the NSMP group, mutant KRAS and wild-type ARID1A were associated with significantly poorer 5-year RFS (41.2%) than other genomic characteristics (P < 0.001). The distribution of the subtypes differed significantly between patients with recurrence/progression and classified by sequencing (n = 764) and patients who underwent initial surgery (P < 0.001). Among patients with recurrence/progression, 51.4% had the opportunity to receive molecular targeted therapy. CONCLUSIONS: A molecular classifier is a useful tool for determining prognosis and eligibility for molecularly targeted therapy in patients with endometrial cancer.