Biomarker Profiling of Upper Tract Urothelial Carcinoma Only and with Synchronous or Metachronous Bladder Cancer.

BACKGROUND: Molecular profiling in upper tract urothelial carcinoma (UTUC) with synchronous or metachronous urothelial bladder cancer (UBC) is scarce. We intended to assess immunohistochemical (IHC) and genetic differences between UTUC-only and UTUC with synchronous or metachronous UBC (UTUC + UBC) and evaluate the effect of subsequent UBC on the outcome of UTUC patients stratified by luminal-basal subtypes. METHODS: A retrospective cohort of UTUC was divided into UTUC-only (n = 71) and UTUC + UBC (n = 43). IHC expression of cytokeratin 5/6 (CK5/6), CK20, GATA3, and p53 was evaluated to assess relevant subtypes. Genetic characterization comprised TERTp, FGFR3, RAS, and TP53 status. Kaplan-Meier and Cox regression analyses estimated the effect of clinicopathological variables and molecular profiles on progression-free survival (PFS) and overall survival (OS) of UTUC patients. RESULTS: No meaningful differences were detected among both subgroups according to luminal-basal stratification and genetic analysis. UTUC + UBC was independently associated with a worse PFS when stratified by luminal-basal phenotype (HR 3.570, CI 95% 1.508-8.453, p = 0.004) but with no impact in OS (HR 1.279, CI 95% 0.513-3.190, p = 0.597). CONCLUSIONS: This study reveals that both subgroups exhibited equivalent genomic features and luminal-basal subtypes. The involvement of the bladder relates to shorter PFS but does not seem to influence the survival outcome of UTUC, independently of the IHC phenotype.

A paradigm shift in understanding vulvovaginal melanoma as a distinct tumor type compared with cutaneous melanoma.

OBJECTIVE: Our goal was to compare molecular and immune profiles of vulvovaginal melanoma (VVM) with cutaneous melanoma (CM) and explore the significance of immune checkpoint inhibitor (ICI) agents on survival. METHODS: Samples from VVM and CM tumors underwent comprehensive molecular and immune profiling. Treatment and survival data were extracted from insurance claims data and OS was calculated from time of ICI treatment to last contact. Statistical significance was determined using chi-square and Wilcoxon rank sum test and adjusted for multiple comparisons. RESULTS: Molecular analysis was performed on 142 VVM and 3823 CM tumors. VVM demonstrated significantly (q < 0·01) less frequent BRAF and more frequent KIT, ATRX, and SF3B1 mutations. Alterations in pathways involving DNA damage and mRNA splicing were more common in VVM, while alterations in cell cycle and chromatin remodeling were less common. Immunogenicity of VVM was lower than CM, with an absence of high TMB (0% vs 46.9%) and lower PD-L1 positivity (18·0% vs 29·5%). Median immune checkpoint gene expression was lower in VVM, as were cell fractions for type I macrophages and CD8+ T-cells(q < 0·01). Myeloid dendritic cells were increased in VVM(q < 0·01). Median OS was shorter for VVM than for CM patients treated with ICIs (17·6 versus 37·9 months, HR:1·65 (95% CI 1·02-2·67) p = 0·04). CONCLUSIONS: VVM has a distinct molecular and immune profile compared to CM, which may contribute to the worse survival in VVM compared to CM patients treated with ICI therapy. Though ICIs have been a mainstay of treatment in recent years, our findings suggest that new therapeutic strategies are needed.

Comparative analysis of the tumor microbiome, molecular profiles, and immune cell abundances by HPV status in mucosal head and neck cancers and their impact on survival.

Head and Neck Squamous Cell Carcinoma (HNSCC) comprises a diverse group of tumors with variable treatment response and prognosis. The tumor microenvironment (TME), which includes microbiome and immune cells, can impact outcomes. Here, we sought to relate the presence of specific microbes, gene expression, and tumor immune infiltration using tumor transcriptomics from The Cancer Genome Atlas (TCGA) and associate these with overall survival (OS). RNA sequencing (RNAseq) from HNSCC tumors in TCGA was processed through the exogenous sequences in tumors and immune cells (exotic) pipeline to identify and quantify low-abundance microbes. The detection of the Papillomaviridae family of viruses assessed HPV status. All statistical analyses were performed using R. A total of 499 RNAseq samples from TCGA were analyzed. HPV was detected in 111 samples (22%), most commonly Alphapapillomavirus 9 (90.1%). The presence of Alphapapillomavirus 9 was associated with improved OS [HR = 0.60 (95%CI: 0.40-0.89, p = .01)]. Among other microbes, Yersinia pseudotuberculosis was associated with the worst survival (HR = 3.88; p = .008), while Pseudomonas viridiflava had the best survival (HR = 0.05; p = .036). Microbial species found more abundant in HPV- tumors included several gram-negative anaerobes. HPV- tumors had a significantly higher abundance of M0 (p < .001) and M2 macrophages (p = .035), while HPV+ tumors had more T regulatory cells (p < .001) and CD8+ T-cells (p < .001). We identified microbes in HNSCC tumor samples significantly associated with survival. A greater abundance of certain anaerobic microbes was seen in HPV tumors and pro-tumorigenic macrophages. These findings suggest that TME can be used to predict patient outcomes and may help identify mechanisms of resistance to systemic therapies.

Mutually exclusive driver mutations identifies 2 separate primaries in a collision tumor initially interpreted as a solitary lung adenocarcinoma with tumor heterogeneity.

Distinction of histologically heterogenous, single primary tumor from two or more collision tumors with different primaries could represent a challenge to practicing pathologists. Histologic variations including differences in degree of differentiating within a tumor, are typically interpreted as tumor heterogeneity in a contiguous small size tumor biopsy. The authors report a case of adult former smoker female who presented with lung mass and a metastatic lytic lesion of acetabulum. A needle biopsy of a lung mass revealed an adenocarcinoma with well and moderately differentiated components. Next generation sequencing studies proved 2 different primaries in this small needle biopsy.

Plasmablastic lymphoma: current knowledge and future directions.

Plasmablastic lymphoma (PBL) is an aggressive non-Hodgkin lymphoma associated with HIV infection and immunodeficiency. However, PBL can also be seen immunocompetent individuals in recent studies. PBL was characterized by distinct clinical and pathological features, such as plasmablastic morphology and universal expression of plasma cell markers. The clinicopathologic features were different between HIV-negative and HIV-positive patients. Gene expression analysis identified the unique molecular feature in PBL, including frequent c-MYC rearrangement and downregulation of BCR signaling pathway. Despite the recent advances in the treatment of PBL, the prognosis of PBL patients remains dismal. The objectives of this review are to summarize the current knowledge on the epidemiology, molecular profiles, clinical and pathological features, differential diagnosis, treatment strategies, prognostic factors, and potential novel therapeutic approaches in PBL patients.

FT-ICR-MS reveals the molecular imprints of the brewing process.

The study of fermentation and brewing has a long history of pioneering discoveries that continue to influence modern industrial food production. Since then, numerous research endeavors have yielded conventional criteria that guide contemporary brewing practices. However, the intricate open challenges faced today necessitate a more exhaustive understanding of the process at the molecular scale. We have developed an ultra-high-resolution mass spectrometric analysis (FT-ICR-MS) of the brewing process that can rapidly and comprehensively resolve thousands of molecules. This approach allows us to track molecular fluctuation during brewing at the level of chemical compositions. Employing biological triplicates, our investigation of two brewing lines that are otherwise identical except for the malt used revealed over 8,000 molecular descriptors of the brewing process. Metabolite imprints of both the similarities and differences arising from deviating malting temperatures were visualized. Additionally, we translated traditional brewing attributes such as the EBC-value, free amino nitrogen, pH-value, and concentration curves of specific molecules, into highly correlative molecular patterns consisting of hundreds of metabolites. These in-depth molecular imprints provide a better understanding of the molecular circumstances leading to various changes throughout the brewing process. Such chemical maps go beyond the observation of traditional brewing attributes and are of great significance in the investigation strategies of current open challenges in brewing research. The molecular base of knowledge, along with advancements in technological and data integration schemes, can facilitate the efficient monitoring of brewing and other productions processes.

TERT promoter mutations and gene amplification in endometrial cancer.

OBJECTIVE: To assess the clinicopathologic, molecular profiles, and survival outcomes of patients with endometrial carcinomas (ECs) harboring telomerase reverse transcriptase (TERT) hotspot mutations or gene amplification. METHODS: ECs harboring somatic TERT promoter hotspot mutations or gene amplification (TERT-altered) were identified from 1944 ECs that underwent clinical tumor-normal sequencing from 08/2016-12/2021. Clinicopathologic variables, somatic mutation profiles, and survival outcomes of TERT-alt and TERT-wild-type EC were assessed. RESULTS: We identified 66 TERT-altered ECs (43 TERT-mutated and 23 TERT-amplified), representing 3% of the unselected ECs across histologic subtypes. Most TERT-altered ECs were of copy number (CN)-high/TP53abn molecular subtype (n = 40, 60%), followed by microsatellite-unstable (MSI-H) or CN-low/no specific molecular profile (NSMP)(n = 13, 20% each). TERT-amplified and TERT-mutated ECs were molecularly distinct, with TERT-amplified ECs being more genomically instable and more frequently harboring TP53 and PPP2R1A alterations (q < 0.1). Compared to TERT-wild-type ECs, TERT-altered ECs were more commonly of CN-H/TP53abn molecular subtype (31% vs 57%, p = 0.001), serous histology (10% vs 26%, p = 0.004), and were significantly enriched for TP53, CDKN2A/B, and DROSHA somatic genetic alterations (q < 0.1). Median progression-free survival was 18.7 months (95% CI 11.8-not estimable [NE]) for patients with TERT-altered EC and 80.9 months (65.8-NE) for patients with TERT-wild-type EC (HR 0.33, 95% CI 0.21-0.51, p < 0.001). Similarly, median overall survival was 46.7 months (95% CI 30-NE) for TERT-altered EC patients and not reached for TERT-wild-type EC patients (HR 0.24, 95% CI 0.13-0.44, p < 0.001). CONCLUSION: TERT-altered ECs, although rare, are enriched for CN-high/TP53abn tumors, TP53, CDKN2A/B and DROSHA somatic mutations, and independently predict worse survival outcomes.

Comprehension of rectosigmoid junction cancer molecular features by comparison to the rectum or sigmoid colon cancer.

Background: Colorectal cancer (CRC) is a heterogeneous cancer. Its treatment depends on its anatomical site and molecular features. Carcinomas of the rectosigmoid junction are frequent; however, specific data on these tumors are sparse, as they are frequently assigned to either the colon or rectum. This study sought to identify the molecular features of rectosigmoid junction cancer to determine whether there should be any difference between the therapeutic management of rectosigmoid junction cancer and that of sigmoid colon or rectum cancer. Methods: The data of 96 CRC patients with carcinomas in the sigmoid colon, rectosigmoid junction, and rectum were retrospectively summarized. The next-generation sequencing (NGS) data of the patients were analyzed to study the molecular characteristics of the carcinomas in different locations of the bowel. Results: In total, there was no difference in the clinicopathologic characteristics of the three groups. TP53, APC, and KRAS genes were the top 3 alteration genes in sigmoid colon, rectosigmoid junction, and rectum cancer. The rates of the KRAS, NRAS, and PIK3CA increased as the location moved distally, while the rates of APC and BRAF decreased. Almost no significant molecular differences were found among the three groups. The prevalence of the FLT3, fms-related tyrosine kinase 1 (FLT1), and phosphoenolpyruvate carboxykinase 1 (PCK1) mutation was lower in the rectosigmoid junction group than the sigmoid colon and rectum groups (P>0.05). The proportion of the transforming growth factor beta pathway was higher in the rectosigmoid junction and rectum groups than the sigmoid colon group (39.3% vs. 34.3% vs. 18.2%, respectively, P=0.121, P=0.067, P=0.682); a higher proportion of MYC pathway was also observed in the rectosigmoid junction than that in rectum and sigmoid colon (28.6% vs. 15.2% vs. 17.1%, P=0.278, P=0.202, P=0.171). Regardless of the clustering method employed, the patients were divided into two clusters, and the composition of clusters revealed no significant differences in terms of the different locations. Conclusions: Rectosigmoid junction cancer has a distinctive molecular profile compared to the molecular profiles of the adjacent bowel segment cancers.

Molecular profile and clinical features of patients with gliomas using a broad targeted next generation-sequencing panel.

Gliomas are the most common malignant primary brain tumors characterized by poor prognosis. The genotyping of tumors using next generation sequencing (NGS) platforms enables the identification of genetic alterations that constitute diagnostic, prognostic and predictive biomarkers. The present study investigated the molecular profile of 32 tumor samples from 32 patients with high-grade gliomas by implementing a broad 80-gene targeted NGS panel while reporting their clinicopathological characteristics and outcomes. Subsequently, 14 of 32 tumor specimens were also genotyped using a 55-gene NGS panel to validate the diagnostic accuracy and clinical utility of the extended panel. The median follow-up was 19.2 months. In total, 129 genetic alterations including 33 structural variants were identified in 38 distinct genes. Among 96 variants (single nucleotide variants and insertions and deletions), 38 were pathogenic and 58 variants of unknown clinical significance. TP53 was the most frequently mutated gene, followed by PTEN and IDH1 genes. Glioma patients with IDH1 mutant tumors were younger and had significantly longer overall survival compared to patients with wild-type IDH1 tumors. Similarly, tumors with TP53 mutations were more likely observed in younger patients with glioma. Subsequently, a comparison of mutational profiles of samples analyzed by both panels was also performed. Implementation of the comprehensive pan-cancer and the MOL panels resulted in the identification of 37 and 15 variants, respectively. Of those, 13 were common. Comprehensive pan-cancer panel identified 24 additional variants, 22 of which were located in regions that were not targeted by the MOL panel. By contrast, the MOL panel identified two additional variants. Overall, the present study demonstrated that using an extended tumor profile assay instead of a glioma-specific tumor profile panel identified additional genetic changes that may be taken into consideration as potential therapeutic targets for glioma diagnosis and molecular classification.

Time-Series Transcriptomic Analysis Reveals the Molecular Profiles of Diapause Termination Induced by Long Photoperiods and High Temperature in Chilo suppressalis.

Survival and adaptation to seasonal changes are challenging for insects. Many temperate insects such as the rice stem borer (Chilo suppressalis) overcome the adverse situation by entering diapause, wherein development changes dynamically occur and metabolic activity is suppressed. The photoperiod and temperature act as major environmental stimuli of diapause. However, the physiological and molecular mechanisms that interpret the ecologically relevant environmental cues in ontogenetic development during diapause termination are poorly understood. Here, we used genome-wide high-throughput RNA-sequencing to examine the patterns of gene expression during diapause termination in C. suppressalis. Major shifts in biological processes and pathways including metabolism, environmental information transmission, and endocrine signalling were observed across diapause termination based on over-representation analysis, short time-series expression miner, and gene set enrichment analysis. Many new pathways were identified in diapause termination including circadian rhythm, MAPK signalling, Wnt signalling, and Ras signalling, together with previously reported pathways including ecdysteroid, juvenile hormone, and insulin/insulin-like signalling. Our results show that convergent biological processes and molecular pathways of diapause termination were shared across different insect species and provided a comprehensive roadmap to better understand diapause termination in C. suppressalis.

Identifying Actionable Variants in Cancer - The Dual Web and Batch Processing Tool MTB-Report.

Next-generation sequencing methods continuously provide clinicians and researchers in precision oncology with growing numbers of genomic variants found in cancer. However, manually interpreting the list of variants to identify reliable targets is an inefficient and cumbersome process that does not scale with the increasing number of cases. Support by computer systems is needed for the analysis of large scale experiments and clinical studies to identify new targets and therapies, and user-friendly applications are needed in molecular tumor boards to support clinicians in their decision-making processes. The MTB-Report tool annotates, filters and sorts genetic variants with information from public databases, providing evidence on actionable variants in both scenarios. A web interface supports medical doctors in the tumor board, and a command line mode allows batch processing of large datasets. The MTB-Report tool is available as an R implementation as well as a Docker image to provide a tool that runs out-of-the-box. Moreover, containerization ensures a stable application that delivers reproducible results over time. A public version of the web interface is available at: http://mtb.bioinf.med.uni-goettingen.de/mtb-report.

Identification of Carcinogenesis and Tumor Progression Processes in Pancreatic Ductal Adenocarcinoma Using High-Throughput Proteomics.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with an overall 5-year survival rate of just 5%. A better understanding of the carcinogenesis processes and the mechanisms of the progression of PDAC is mandatory. Fifty-two PDAC patients treated with surgery and adjuvant therapy, with available primary tumors, normal tissue, preneoplastic lesions (PanIN), and/or lymph node metastases, were selected for the study. Proteins were extracted from small punches and analyzed by LC-MS/MS using data-independent acquisition. Proteomics data were analyzed using probabilistic graphical models, allowing functional characterization. Comparisons between groups were made using linear mixed models. Three proteomic tumor subtypes were defined. T1 (32% of patients) was related to adhesion, T2 (34%) had metabolic features, and T3 (34%) presented high splicing and nucleoplasm activity. These proteomics subtypes were validated in the PDAC TCGA cohort. Relevant biological processes related to carcinogenesis and tumor progression were studied in each subtype. Carcinogenesis in the T1 subtype seems to be related to an increase of adhesion and complement activation node activity, whereas tumor progression seems to be related to nucleoplasm and translation nodes. Regarding the T2 subtype, it seems that metabolism and, especially, mitochondria act as the motor of cancer development. T3 analyses point out that nucleoplasm, mitochondria and metabolism, and extracellular matrix nodes could be involved in T3 tumor carcinogenesis. The identified processes were different among proteomics subtypes, suggesting that the molecular motor of the disease is different in each subtype. These differences can have implications for the development of future tailored therapeutic approaches for each PDAC proteomics subtype.

The bioinformatics and experimental analysis of AlkB family for prognosis and immune cell infiltration in hepatocellular carcinoma.

BACKGROUND: Serving as N6-methyladenosine demethylases, the AlkB family is involved in the tumorigenesis of hepatocellular carcinoma (HCC). However, the molecular profiles and clinical values of the AlkB family in HCC are not well known. METHODS: Several bioinformatics tools and in vitro experiments were used to identify the immune-related profiles and prognostic values of AlkB family in HCC. RESULTS: In this study expression levels of ALKBH1/2/3/4/7 were all remarkably increased in HCC tissues when compared with normal tissues. Quantitative PCR (qPCR) and immunohistochemistry were used to validate the expression of AlkB family members in HCC tissues and normal liver tissues. In addition, high expression levels of ALKBH4 were negatively correlated with overall survival (OS) and disease-free survival (DFS) in patients with HCC. Increased ALKBH4 was also associated with pathological stage in HCC patients. The molecular profiles of AlkB family in HCC were mainly associated with peptidyl-serine modification, peptidyl-tyrosine modification, regulation of metal ion transport, etc. Furthermore, tumor-infiltrating immune cell analysis indicated that ALKBH1/2/3/4/5/6/7/8 and FTO were related to the infiltration of different immune cell, such as CD8+ T cells, macrophages, neutrophils, dendritic cells and CD4+ T cells. We also discovered that the methylation levels of ALKBH1/2/4/5/6/8 and FTO were remarkably reduced in HCC tissues. CONCLUSIONS: Collectively, our findings may deepen the understanding of specific molecular profiles of the AlkB family in HCC pathology. In particular, ALKBH4 could serve as a promising prognostic candidate for treating HCC, and these results might potentiate the development of more reliable therapeutic strategies for patients with HCC.

Histological Heterogeneity of Primary Liver Cancers: Clinical Relevance, Diagnostic Pitfalls and the Pathologist's Role.

Primary liver cancers (PLCs) mainly comprise hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), and cHCC-CCA. Combined HCC-CCA and small duct type iCCA show similar clinical presentations, and their histological features are more complex than seen in HCC. Therefore, while their treatment strategy differs, it is difficult to properly diagnose these tumors. Currently, HCC is the only tumor that can be treated by liver transplantation. In addition, small duct type iCCA harbors IDH1/2 mutations and FGFR2 fusions, which can be used for targeted therapy. Thus, improving diagnostic accuracy is crucial. A further point to note is that PLCs often present as multiple liver tumors, and they can be a combination of different types of PLCs or HCCs. In the case of HCCs, two different scenarios are possible, namely intrahepatic metastasis, or multicentric occurrence. Therefore, it is essential to characterize the type of multiple liver tumors. This review aims to clarify the pathological features of HCC, iCCA and cHCC-CCA, including their diagnostic pitfalls and clinical relevance. It is designed to be of use to clinicians who are dealing with PLCs, to provide a better understanding of the pathology of these tumors, and to enable a more accurate diagnosis and optimal treatment choice.

Identification of magnetic resonance imaging features for the prediction of molecular profiles of newly diagnosed glioblastoma.

PURPOSE: We predicted molecular profiles in newly diagnosed glioblastoma patients using magnetic resonance (MR) imaging features and explored the associations between imaging features and major molecular alterations. METHODS: This retrospective study included patients with newly diagnosed glioblastoma and available next-generation sequencing results. From preoperative MR imaging, Visually AcceSAble Rembrandt Images (VASARI) features, volumetric parameters, and apparent diffusion coefficient (ADC) values were obtained. First, univariate random forest was performed to identify gene abnormalities that could be predicted by imaging features with high accuracy and stability. Next, multivariate random forest was trained to predict the selected genes in the discovery cohort and was validated in the external cohort. Univariable logistic regression was performed to further explore the associations between imaging features and genes. RESULTS: Univariate random forest identified nine genes predicted by imaging features, with high accuracy and stability. The multivariate random forest model showed excellent performance in predicting IDH and PTPN11 mutations in the discovery cohort, which were validated in the external validation cohorts (areas under the receiver operator characteristic curve [AUCs] of 0.855 for IDH and 0.88 for PTPN11). ATRX loss and EGFR mutation were predicted with AUCs of 0.753 and 0.739, respectively, whereas PTEN could not be reliably predicted. Based on univariable logistic regression analyses, IDH, ATRX, and TP53 were clustered according to their shared imaging features, whereas EGFR and CDKN2A/B were clustered in the opposite direction. CONCLUSIONS: MR imaging features are related to specific molecular alterations and can be used to predict molecular profiles in patients with newly diagnosed glioblastoma.

Imaging of brain tumors in children: the basics-a narrative review.

Primary pediatric brain tumors comprise a broad group of neoplasm subtypes that can be categorized based on their histological and molecular features according to the 2016 World Health Organization (WHO) classification of central nervous system (CNS) tumors. The majority of the pediatric brain tumors demonstrate a singular preference for this age group and have a unique molecular profile. The separation of certain tumor entities, including different types of embryonal tumors, low-grade gliomas, and high-grade gliomas, may have a significant impact by guiding appropriate treatment for these children and potentially changing their outcomes. Currently, the focus of the imaging diagnostic studies is to follow the molecular updates, searching for potential imaging patterns that translate this information in molecular profile results, therefore helping the final diagnosis. Due to the high impact of accurate diagnosis in this context, the scientific community has presented extensive research on imaging pediatric tumors in recent years. This article summarizes the key characteristics of the imaging features of the most common primary childhood brain tumors, categorizing them according to the recent WHO classification update, which is based on each of their molecular profiles. The purpose of this review article is to familiarize radiologists with their key imaging features and thereby improve diagnostic accuracy.

Molecular characterization of high-grade serous ovarian cancers occurring in younger and older women.

OBJECTIVES: To determine if the mutational landscapes and genomic features of homologous recombination DNA repair defects (HRD) vary between younger and older patients with high-grade serous ovarian cancer (HGSOC). METHODS: Younger and older women were defined as bottom and top age quartiles, respectively. HGSOCs from 15 younger (median 49 years, range 35-53) and 15 older women (median 72 years, range 70-87) were subjected to whole-exome sequencing (WES). For validation, HGSOC WES data were obtained from The Cancer Genome Atlas (TCGA), including 38 younger (median 45 years, range 34-50) and 30 older women (median 74 years, range 68-84). Mutational profiles, BRCA1/2 status, genomic HRD features, and for TCGA cases RNA-sequencing-based HRD transcriptomic signatures were assessed. RESULTS: In the institutional cohort, pathogenic germline BRCA1/2 mutations were more frequent in younger (5/15) than older women (0/15, p = 0.042). No somatic BRCA1/2 mutations were identified. HGSOCs from older patients preferentially displayed aging-related mutational signatures and, in contrast to younger patients, harbored CCNE1 amplifications (3/15, 20%). In the TCGA cohort, pathogenic germline BRCA1 (younger 8/38, older 0/30, p = 0.007) but not BRCA2 mutations (young 3/38, older 4/30, p = 0.691) were more frequent in younger patients. Again, no somatic BRCA1/2 mutations were identified. HGSOCs from younger women more frequently displayed genomic features of HRD (all, p < 0.05), a significant HRD gene-signature enrichment, but less frequently CCNE1 amplification (p = 0.05). Immunoreactive CLOVAR subtypes were more common in HGSOCs from younger women, and proliferative subtypes in HGSOCs from older women (p = 0.041). CONCLUSIONS: HGSOC patients diagnosed at an older age less frequently harbor pathogenic BRCA1 germline mutations and genomic features of HRD than younger women. Individualized treatment options, particularly pertaining to use of PARP inhibitors, in older women may be warranted.

Prediction of Lymph-Node Metastasis in Cancers Using Differentially Expressed mRNA and Non-coding RNA Signatures.

Accurate prediction of lymph-node metastasis in cancers is pivotal for the next targeted clinical interventions that allow favorable prognosis for patients. Different molecular profiles (mRNA and non-coding RNAs) have been widely used to establish classifiers for cancer prediction (e.g., tumor origin, cancerous or non-cancerous state, cancer subtype). However, few studies focus on lymphatic metastasis evaluation using these profiles, and the performance of classifiers based on different profiles has also not been compared. Here, differentially expressed mRNAs, miRNAs, and lncRNAs between lymph-node metastatic and non-metastatic groups were identified as molecular signatures to construct classifiers for lymphatic metastasis prediction in different cancers. With this similar feature selection strategy, support vector machine (SVM) classifiers based on different profiles were systematically compared in their prediction performance. For representative cancers (a total of nine types), these classifiers achieved comparative overall accuracies of 81.00% (67.96-92.19%), 81.97% (70.83-95.24%), and 80.78% (69.61-90.00%) on independent mRNA, miRNA, and lncRNA datasets, with a small set of biomarkers (6, 12, and 4 on average). Therefore, our proposed feature selection strategies are economical and efficient to identify biomarkers that aid in developing competitive classifiers for predicting lymph-node metastasis in cancers. A user-friendly webserver was also deployed to help researchers in metastasis risk determination by submitting their expression profiles of different origins.

PTEN, ATM, IDH1 mutations and MAPK pathway activation as modulators of PFS and OS in patients treated by first line EGFR TKI, an ancillary study of the French Cooperative Thoracic Intergroup (IFCT) Biomarkers France project.

OBJECTIVES: Tumor mutation screening is standard of care for patients with stage IV NSCLC. Since a couple of years, widespread NGS approaches used in routine diagnostics to detect driver mutations such as EGFR, KRAS, BRAF or MET allows the identification of other alterations that could modulated the intensity or duration of response to targeted therapies. The prevalence of co-occurring alterations that could affect response or prognosis as not been largely analyzed in clinical settings and large cohorts of patients. Thanks to the IFCT program "Biomarkers France", a collection of samples and data at a nation-wide level was available to test the impact of co-mutations on first line EGFR TKI in patients with EGFR mutated cancers. MATERIALS AND METHODS: Targeted NGS was assessed on available (n = 208) samples using the Ion AmpliSeq™ Cancer Hotspot Panel v2 to screen for mutations in 50 different cancer genes. RESULTS: This study showed that PTEN inactivating mutations, ATM alterations, IDH1 mutations and complex EGFR mutations were predictors of short PFS in patients with a stage 4 lung adenocarcinoma receiving first line EGFR TKI and that PTEN, ATM, IDH1 and KRAS mutations as well as alterations in the MAPK pathway were related to shorter OS. CONCLUSION: These findings may lead to new treatment options in patients with unfavorable genotypes to optimize first line responses.

Machine learning model to predict oncologic outcomes for drugs in randomized clinical trials.

Predicting oncologic outcome is challenging due to the diversity of cancer histologies and the complex network of underlying biological factors. In this study, we determine whether machine learning (ML) can extract meaningful associations between oncologic outcome and clinical trial, drug-related biomarker and molecular profile information. We analyzed therapeutic clinical trials corresponding to 1102 oncologic outcomes from 104 758 cancer patients with advanced colorectal adenocarcinoma, pancreatic adenocarcinoma, melanoma and nonsmall-cell lung cancer. For each intervention arm, a dataset with the following attributes was curated: line of treatment, the number of cytotoxic chemotherapies, small-molecule inhibitors, or monoclonal antibody agents, drug class, molecular alteration status of the clinical arm's population, cancer type, probability of drug sensitivity (PDS) (integrating the status of genomic, transcriptomic and proteomic biomarkers in the population of interest) and outcome. A total of 467 progression-free survival (PFS) and 369 overall survival (OS) data points were used as training sets to build our ML (random forest) model. Cross-validation sets were used for PFS and OS, obtaining correlation coefficients (r) of 0.82 and 0.70, respectively (outcome vs model's parameters). A total of 156 PFS and 110 OS data points were used as test sets. The Spearman correlation (rs ) between predicted and actual outcomes was statistically significant (PFS: rs = 0.879, OS: rs = 0.878, P < .0001). The better outcome arm was predicted in 81% (PFS: N = 59/73, z = 5.24, P < .0001) and 71% (OS: N = 37/52, z = 2.91, P = .004) of randomized trials. The success of our algorithm to predict clinical outcome may be exploitable as a model to optimize clinical trial design with pharmaceutical agents.