Molecular Classification Of Tumors Research Articles

Abstract 6911: Expanding reported molecular characteristics for the NCI Patient-Derived Models Repository

Abstract The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), in vitro patient-derived tumor cell cultures (PDCs) and cancer associated fibroblasts (CAFs) as well as patient-derived organoids (PDOrg). These PDMs are clinically annotated with molecular information available in an easily accessible database for the extramural community. To ensure the data and models remains pertinent to current translational efforts, NCI actively reviews and adds new molecular features to the public database for researchers to use. While these data could be obtained through analysis of the available NextGen sequencing files in the PDMR database, many laboratories do not have the bioinformatics support to run these assessments for models that are of research interest. Therefore, new pipelines for an array of additional model and molecular characteristics present in PDX, PDOrg, and PDC models have been validated and are reported in the public database in a searchable format. Current model characteristics include addition of OncoTree Codes as a second histologic classifier, use of the PDXNet Consortium’s inferred ancestry caller to better represent Native/Latin American populations, human leukocyte antigen (HLA) typing, molecular classification of tumors (e.g. CMS subtyping of colorectal adenocarcinoma, PAM50 signature based subtyping of breast carcinoma), microsatellite instability (MSI) assessment, and identification of clinically relevant fusions. SOPs for the pipelines used are available on the public website to allow for independent validation and use by other laboratories. Funded by NCI Contract No. HHSN261200800001E Citation Format: Cindy R. Timme, Yvonne A. Evrard, Biswajit Das, Ting-Chia Chang, Alice Chen, Li Chen, Michelle A. Crespo-Eugeni, Shahanawaz Jiwani, Chris A. Karlovich, Rini Pauly, Peter I-Fan Wu, Dianne L. Newton, P. Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. Expanding reported molecular characteristics for the NCI Patient-Derived Models Repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6911.

Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance

BackgroundProstate cancer (PCA) is the fifth leading cause of cancer-related deaths worldwide, with limited treatment options in the advanced stages. The immunosuppressive tumor microenvironment (TME) of PCA results in lower sensitivity to immunotherapy. Although molecular subtyping is expected to offer important clues for precision treatment of PCA, there is currently a shortage of dependable and effective molecular typing methods available for clinical practice. Therefore, we aim to propose a novel stemness-based classification approach to guide personalized clinical treatments, including immunotherapy.MethodsAn integrative multi-omics analysis of PCA was performed to evaluate stemness-level heterogeneities. Unsupervised hierarchical clustering was used to classify PCAs based on stemness signature genes. To make stemness-based patient classification more clinically applicable, a stemness subtype predictor was jointly developed by using four PCA datasets and 76 machine learning algorithms.ResultsWe identified stemness signatures of PCA comprising 18 signaling pathways, by which we classified PCA samples into three stemness subtypes via unsupervised hierarchical clustering: low stemness (LS), medium stemness (MS), and high stemness (HS) subtypes. HS patients are sensitive to androgen deprivation therapy, taxanes, and immunotherapy and have the highest stemness, malignancy, tumor mutation load (TMB) levels, worst prognosis, and immunosuppression. LS patients are sensitive to platinum-based chemotherapy but resistant to immunotherapy and have the lowest stemness, malignancy, and TMB levels, best prognosis, and the highest immune infiltration. MS patients represent an intermediate status of stemness, malignancy, and TMB levels with a moderate prognosis. We further demonstrated that these three stemness subtypes are conserved across pan-tumor. Additionally, the 9-gene stemness subtype predictor we developed has a comparable capability to 18 signaling pathways to make tumor diagnosis and to predict tumor recurrence, metastasis, progression, prognosis, and efficacy of different treatments.ConclusionsThe three stemness subtypes we identified have the potential to be a powerful tool for clinical tumor molecular classification in PCA and pan-cancer, and to guide the selection of immunotherapy or other sensitive treatments for tumor patients.

Canine Mammary Cancer: State of the Art and Future Perspectives.

Mammary cancer is the most frequently diagnosed neoplasia in women and non-spayed female dogs and is one of the leading causes of death in both species. Canines develop spontaneous mammary tumors that share a significant number of biological, clinical, pathological and molecular characteristics with human breast cancers. This review provides a detailed description of the histological, molecular and clinical aspects of mammary cancer in canines; it discusses risk factors and currently available diagnostic and treatment options, as well as remaining challenges and unanswered questions. The incidence of mammary tumors is highly variable and is impacted by biological, pathological, cultural and socioeconomic factors, including hormonal status, breed, advanced age, obesity and diet. Diagnosis is mainly based on histopathology, although several efforts have been made to establish a molecular classification of canine mammary tumors to widen the spectrum of treatment options, which today rely heavily on surgical removal of tumors. Lastly, standardization of clinical study protocols, development of canine-specific biological tools, establishment of adequate dog-specific disease biomarkers and identification of targets for the development of new therapies that could improve survival and have less adverse effects than chemotherapy are among the remaining challenges.

P13.15.B ULTRA-FAST DEEP-LEARNED CNS TUMOR CLASSIFICATION DURING SURGERY

Abstract BACKGROUND Central nervous system (CNS) tumors are the most lethal category of tumors, particularly among children. Most commonly, the first line treatment of CNS tumors is neurosurgical resection of the tumor. During this procedure a delicate balance must be struck between extent of resection and risk of comorbidity. Ideally, the surgical plan is based on a detailed classification of the tumor. However this classification is often unknown at the start of the surgery. Current practice consists of preoperative imaging and intraoperative diagnosis achieved by rapid histological assessment of frozen tumor sections. However, these tests do not always result in a clear diagnosis, and are sometimes even revised based on postoperative tissue-based diagnostics. As a result, some patients require a second surgery, while others could in hindsight have been operated less radically. MATERIAL AND METHODS Nanopore sequencing enables direct detection of DNA methylation status in real time, making it ideally suited for intraoperative sequencing and molecular tumor classification. The major challenge of this approach is that the classification must be performed on very few randomly distributed sequence reads. To this end we developed Sturgeon, a neural-network training approach that delivers classification models capable of classifying 81 different CNS tumor subtypes based on sparse methylation data. Sturgeon leverages illumina 450K DNA methylation profiles to simulate millions of nanopore sequencing experiments, which are then used to train and validate classifier models. The resulting models are portable, work across patients and sequence depths and require less than a minute of computation on a laptop CPU. RESULTS We demonstrate our method to be fast enough to provide a correct diagnosis with as little as 20 to 40 minutes of sequencing in 45 out of 50 retrospective pediatric brain tumor samples. We applied Sturgeon in an intraoperative setting in 25 cases, where we consistently achieve a turnaround time of 60-90 minutes from biopsy to result with a correct molecular subclassification in 18 cases and an inconclusive result in 7 cases. CONCLUSION Sturgeon classification can be used in parallel with intraoperative frozen section histology. In cases where it agrees with the pathologist, Sturgeon offers a valuable independent confirmation, and a more detailed molecular subclassification. In the rare cases where Sturgeon disagrees with the histology diagnosis, or where the histology is inconclusive, it has the potential to prevent misdiagnoses that would result in unnecessary risk of comorbidity, or the requirement for a second surgery.

A 10-Year Survival-Trend Analysis of Low-Grade Glioma and Treatment Patterns from an LMIC.

Objectives The 2021 WHO Classification of Central Nervous System Tumors taxonomy laid further stress on molecular classification and prognostication of glial tumors in comparison to histopathological grading. Research shows that low-grade gliomas (LGGs) can go through malignant differentiation and lead to severe disability and death. Data from various populations will be necessary to ascertain the exact interplay between genotypic predictors of LGG and outcomes. Materials and Methods To assess the molecular pathology for glial tumors in the Pakistani population, the Shaukat Khanum Memorial Cancer Hospital carried out a retrospective chart review of electronic health records from 2008 to 2018, with immunohistochemistry analysis findings from 2010 to 2018. Patients with a pathological diagnosis of a glioma were included. Statistical Analysis Analysis was performed using IBM SPSS Statistics Version 23 and STATA Version 16. A p -value of less than 0.05 was considered statistically significant with 95% confidence intervals reported. Results In all, 281 operable tumors were recorded. The most common procedure was a subtotal resection, and astrocytomas (64.77%) were the most common tumors. Radiation therapy and PCV (procarbazine, CCNU, and vincristine) was received by 85 patients, while radiation therapy and temozolomide were administered to 15 patients. Conclusions Isocitrate dehydrogenase (IDH) wild-type LGG had a lower survival time, while improved survival times were seen for alpha-thalassemia X-linked intellectual disability syndrome (ATRX) retained and 1p19q co-deleted LGGs. Further studies are required to gain a better understanding of lower-grade glial tumor treatment and survival in Pakistan.

EUSICA/COST IMMUNO-model workshop fostering collaboration to advance sinonasal cancer research: A meeting report

Sinonasal cancer is a clinically and histologically heterogeneous group of rare tumors with generally poor clinical outcomes. Their low incidence hampers the advancement of clinical management as well as translational research, and calls for multicenter and multinational collaboration between physicians and researchers. This report describes the proceedings of a two-day conference organized by the European Network for Sinonasal Cancer Research (EUSICA) and COST Action ‘IMMUNO-model’, fostering such collaboration and focusing on preclinical tumor and immuno models, surgical and radio-oncological treatments, core facilities for genetic characterization and molecular tumor classification, and cancer registry.

Expert consensus on standardized management of tumor gene sequencing for cancer patients

AbstractBackgroundTumour gene detection by next‐generation sequencing (NGS) can comprehensively analyze the molecular characteristics of tumors, and predict drug efficacy and tumor resistance mechanisms through tumour cell models, thereby realizing individualized and precise treatment. Therefore, the whole process of standardized management is required. This consensus aims to refine the standardized management of tumor gene sequencing for cancer patients based on the NGS platform, hoping to provide help for the personalized treatment of cancer patients, and further promoting the development of precision medicine.Methods and resultsStandardized management for tumour gene detection of cancer patients includes patient management before gene testing, during gene testing, and after gene testing. Tumour patients should select appropriate test samples and test content before receiving genetic testing. There should be a clear informed consent statement during the test, a detailed report should be provided after the test, and counseling and monitoring follow‐up should be provided. The management of genetic testing of tumour patients should cover early screening and early diagnosis of tumors, molecular classification and companion diagnosis of tumours, and monitoring of tumour recurrence.ConclusionEffective management and standardized procedures for gene detection of cancer patients, covering the whole process before, during and after detection, will benefit the majority of patients from early screening, personalized diagnosis and treatment, prognosis evaluation and other aspects of cancer, and promote the healthy development of the precision medicine industry.

Outlier Expression of Isoforms by Targeted or Total RNA Sequencing Identifies Clinically Significant Genomic Variants in Hematolymphoid Tumors

Recognition of aberrant gene isoforms due to DNA events can impact risk stratification and molecular classification of hematolymphoid tumors. In myelodysplastic syndromes, KMT2A partial tandem duplication (PTD) was one of the top adverse predictors in the International Prognostic Scoring System-Molecular study. In B-cell acute lymphoblastic leukemia (B-ALL), ERG isoforms have been proposed as markers of favorable-risk DUX4 rearrangements, whereas deletion-mediated IKZF1 isoforms are associated with adverse prognosis and have been extended to the high-risk IKZF1plus signature defined by codeletions, including PAX5. In this limited study, outlier expression of isoforms as markers of IKZF1 intragenic or 3' deletions, DUX4 rearrangements, or PAX5 intragenic deletions were 92.3% (48/52), 90% (9/10), or 100% (9/9) sensitive, respectively, and 98.7% (368/373), 100% (35/35), or 97.1% (102/105) specific, respectively, by targeted RNA sequencing, and 84.0% (21/25), 85.7% (6/7), or 81.8% (9/11) sensitive, respectively, and 98.2% (109/111), 98.4% (127/129), or 98.7% (78/79) specific, respectively, by total RNA sequencing. Comprehensive split-read analysis identified expressed DNA breakpoints, cryptic splice sites associated with IKZF1 3' deletions, PTD of IKZF1 exon 5 spanning N159Y in B-ALL with mutated IKZF1 N159Y, and truncated KMT2A-PTD isoforms. Outlier isoforms were also effective targeted RNA markers for PAX5 intragenic amplifications (B-ALL), KMT2A-PTD (myeloid malignant cancers), and rare NOTCH1 intragenic deletions (T-cell acute lymphoblastic leukemia). These findings support the use of outlier isoform analysis as a robust strategy for detecting clinically significant DNA events.

Deep learning generates synthetic cancer histology for explainability and education

Artificial intelligence methods including deep neural networks (DNN) can provide rapid molecular classification of tumors from routine histology with accuracy that matches or exceeds human pathologists. Discerning how neural networks make their predictions remains a significant challenge, but explainability tools help provide insights into what models have learned when corresponding histologic features are poorly defined. Here, we present a method for improving explainability of DNN models using synthetic histology generated by a conditional generative adversarial network (cGAN). We show that cGANs generate high-quality synthetic histology images that can be leveraged for explaining DNN models trained to classify molecularly-subtyped tumors, exposing histologic features associated with molecular state. Fine-tuning synthetic histology through class and layer blending illustrates nuanced morphologic differences between tumor subtypes. Finally, we demonstrate the use of synthetic histology for augmenting pathologist-in-training education, showing that these intuitive visualizations can reinforce and improve understanding of histologic manifestations of tumor biology.

Evolving Diagnostic and Treatment Strategies for Pediatric CNS Tumors: The Impact of Lipid Metabolism.

Pediatric neurological tumors are a heterogeneous group of cancers, many of which carry a poor prognosis and lack a "standard of care" therapy. While they have similar anatomic locations, pediatric neurological tumors harbor specific molecular signatures that distinguish them from adult brain and other neurological cancers. Recent advances through the application of genetics and imaging tools have reshaped the molecular classification and treatment of pediatric neurological tumors, specifically considering the molecular alterations involved. A multidisciplinary effort is ongoing to develop new therapeutic strategies for these tumors, employing innovative and established approaches. Strikingly, there is increasing evidence that lipid metabolism is altered during the development of these types of tumors. Thus, in addition to targeted therapies focusing on classical oncogenes, new treatments are being developed based on a broad spectrum of strategies, ranging from vaccines to viral vectors, and melitherapy. This work reviews the current therapeutic landscape for pediatric brain tumors, considering new emerging treatments and ongoing clinical trials. In addition, the role of lipid metabolism in these neoplasms and its relevance for the development of novel therapies are discussed.

Clinical Exome Gene Panel Analysis of a Cohort of Urothelial Bladder Cancer Patients from Sri Lanka.

Bladder cancer has a high rate of recurrence and high mortality rates in those who progress to muscle invasive disease. Biomarkers and molecular sub classification of tumours beyond standard histopathology has been proposed to address therapeutic dilemmas. The Cancer Genome Atlas project and other studies have contributed to the enhanced knowledge base of the mutational landscape of urothelial bladder cancer. Once again, these are mostly from Caucasian and Chinese patients, with data from the rest of Asia and Sri Lanka being sparse. The objective of this study was to assess the genomic variations of a cohort of urothelial bladder cancer patients in Sri Lanka. The molecular genetic study was conducted on formalin fixed paraffin embedded tumour samples of 24 patients, prospectively enrolled from 2013 to 2017. The samples were sequenced and variant distribution performed based on a 70-gene panel. Total number of filtered mutations in the 24 patients was 10453. Median mutations per patient were 450 (range 22-987). The predominant mutational change was C>T and G>A. The top 5 mutated genes in our cohort were SYNE1, SYNE2, KMT2C, LRP2, and ANK2. The genes were clustered into 3 groups dependent on the number of mutations per patient per gene. The genes of cluster 1 and 2 mapped to Chromatin modifying enzymes and Generic Transcription Pathway. The chromatin remodelling pathway accounted for the largest proportion (22%) of mutations. Clinical exome sequencing utilising a gene panel yielded a high mutation rate in our patients. The predominant mutational change was C>T and G>A. Three clusters of genes were identified. SYNE1 was the gene with the most mutations. The mutations comprised predominantly of genes of the chromatin remodelling pathway.

Abstract 4863: PMCA inhibition induces cytotoxic calcium stress and suppression of Wnt signaling in refractory molecular subtype of gastric cancer

Abstract Background: Gastric cancer (GC) is the fourth leading cause of cancer-related deaths worldwide, but its genetic heterogeneity retards the development of novel therapeutics. Recently, tumor molecular classification identified clinically refractory SEM (i.e., Stem-like, EMT and Mesenchymal) subtype GC which exhibited over-expression of the plasma membrane Ca2+ ATPase (PMCA) whose role is circumventing calcium overload causing ER stress and apoptosis. Here, we showed that PMCA4 is associated with Wnt signaling activity by regulating Secreted Frizzled-Related Protein 2 (SFRP2) expression and demonstrated that PMCA4 inhibition might achieve dual mechanism-specific anti-cancer effect by inducing calcium-mediated apoptosis and restraining oncogenic Wnt activity in SEM subtype GC. Materials and Methods: GC cell lines and patient-derived organoids (PDOs) were categorized either SEM-subtype (SNU484, SNU668, SK4, MKN1; GA077T, GA265T, GA333T, GA352T) or non-SEM subtype (MKN45, NCIN87, SNU16, SNU601; GA200T, GA247T, GA215T) based on transcriptome signatures or subtype-specific biomarker genes. PMCA4 expression was confirmed using western blot and its calcium clearance function was examined using Fluo-4 AM fluorescent Ca2+ dye. Biological and molecular characteristics of GC cell lines and PDOs upon PMCA4 inhibition were investigated using RT-qPCR, western blot, and TOPflash/FOPflash reporter assay. The target engagement of novel PMCA inhibitor PM058 (bis-indole maleimide derivative) was evaluated by cellular thermal shift assay (CETSA), and the efficacy was determined by CCK8 cell viability assay for cell lines and by Cell Titer-Glo for PDOs.Results: PMCA4 was highly expressed in SEM subtype GC cell lines and PDOs. The siRNA-mediated PMCA4 knockdown (KD) or pharmaceutical inhibition of PMCA4 suppressed the calcium clearance, the cell viability, and decreased cell invasion/migration. TCF/LEF-responsive reporter assay revealed that pharmaceutical inhibition of PMCA4 suppressed Wnt/beta-catenin signaling activity, proven by decrease in beta-catenin and Wnt target gene expression. PMCA inhibition was mechanistically associated with the increased expression of SFRP2, a Wnt antagonist. Importantly, PM058, a PMCA inhibitor, treatment resulted in highly efficacious anti-cancer effect in PDOs at nano molar range, which correlated with PMCA4 protein expression.Discussion and Conclusion: Our results provide the proof of concept that PMCA4 can be a promising therapeutic target for refractory subtype cancer. The proposed mechanism of PMCA4 inhibition is calcium overload - induced apoptosis and interfering with Wnt signaling activity via SFRP2 in GC. Importantly, we demonstrated a novel potent inhibitor PM058 that blocks PMCA function in clinically intractable SEM subtype GC cancer. Citation Format: Saeli Ban, Jungmin Kim, Jonghwan Bae, Ki Cheong Park, Suji Lee, Moon Hwan Kim, Jae-Ho Cheong. PMCA inhibition induces cytotoxic calcium stress and suppression of Wnt signaling in refractory molecular subtype of gastric cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4863.

Using AI to improve the molecular classification of brain tumors.

Using AI to improve the molecular classification of brain tumors.

Updates in gynecologic care for individuals with lynch syndrome.

Lynch syndrome is an autosomal dominant hereditary cancer syndrome caused by germline pathogenic variants (PVs) in DNA mismatch repair genes (MLH1, MSH2, PMS2, MSH6) or the EPCAM gene. It is estimated to affect 1 in 300 individuals and confers a lifetime risk of cancer of 10-90%, depending on the specific variant and type of cancer. Lynch syndrome is the most common cause of inherited colorectal cancer, but for women, endometrial cancer is more likely to be the sentinel cancer. There is also evidence that certain PVs causing Lynch syndrome confer an increased risk of ovarian cancer, while the risk of ovarian cancer in others is not well defined. Given this, it is essential for the practicing gynecologist and gynecologic oncologist to remain up to date on the latest techniques in identification and diagnosis of individuals with Lynch syndrome as well as evidence-based screening and risk reduction recommendations for those impacted. Furthermore, as the landscape of gynecologic cancer treatment shifts towards treatment based on molecular classification of tumors, knowledge of targeted therapies well-suited for mismatch repair deficient Lynch tumors will be crucial. The objective of this review is to highlight recent updates in the literature regarding identification and management of individuals with Lynch syndrome as it pertains to endometrial and ovarian cancers to allow gynecologic providers the opportunity to both prevent and identify Lynch-associated cancers earlier, thereby reducing the morbidity and mortality of the syndrome.

Entering a new era of molecular classification of brain tumors: An update of 2021 World Health Organization classification in adult gliomas

Abstract Glioma is the most common primary central nervous system tumor. The World Health Organization (WHO) 2021 classification of gliomas extended from WHO 2016 in the integration of molecular and histological classifications. WHO 2021 aims to establish a specific diagnosis that could reflect the biological and clinical features of the tumors, and further transform into more specific clinical studies or trials and therapeutics. Major updates of WHO 2021 classification focusing on glioma were reviewed in this article.

Syngeneic model of carcinogen-induced tumor mimics basal/squamous, stromal-rich, and neuroendocrine molecular and immunological features of muscle-invasive bladder cancer.

Bladder cancer is a heterogenous disease and the emerging knowledge on molecular classification of bladder tumors may impact treatment decisions based on molecular subtype. Pre-clinical models representing each subtype are needed to test novel therapies. Carcinogen-induced bladder cancer models represent heterogeneous, immune-competent, pre-clinical testing options with many features found in the human disease. Invasive bladder tumors were induced in C57BL/6 mice when continuously exposed to N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN) in the drinking water. Tumors were excised and serially passed by subcutaneous implantation into sex-matched syngeneic C57BL/6 hosts. Eight lines were named BBN-induced Urothelium Roswell Park (BURP) tumor lines. BURP lines were characterized by applying consensus molecular classification to RNA expression, histopathology, and immune profiles by CIBERSORT. Two lines were further characterized for cisplatin response. Eight BURP tumor lines were established with 3 male and 3 female BURP tumor lines, having the basal/squamous (BaSq) molecular phenotype and morphology. BURP-16SR was established from a male mouse and has a stromal-rich (SR) molecular phenotype and a sarcomatoid carcinoma morphology. BURP-19NE was established from a male mouse and has a neuroendocrine (NE)-like molecular phenotype and poorly differentiated morphology. The established BURP tumor lines have unique immune profiles with fewer immune infiltrates compared to their originating BBN-induced tumors. The immune profiles of the BURP tumor lines capture some of the features observed in the molecular classifications of human bladder cancer. BURP-16SR growth was inhibited by cisplatin treatment, while BURP-24BaSq did not respond to cisplatin. The BURP lines represent several molecular classifications, including basal/squamous, stroma-rich, and NE-like. The stroma-rich (BURP-16SR) and NE-like (BURP-19NE) represent unique immunocompetent models that can be used to test novel treatments in these less common bladder cancer subtypes. Six basal/squamous tumor lines were established from both male and female mice. Overall, the BURP tumor lines have less heterogeneity than the carcinogen-induced tumors and can be used to evaluate treatment response without the confounding mixed response often observed in heterogeneous tumors. Additionally, basal/squamous tumor lines were established and maintained in both male and female mice, thereby allowing these tumor lines to be used to compare differential treatment responses between sexes.

Clinical outcome following surgical resection and radiotherapy in adult patients with pleomorphic xanthoastrocytoma as defined by DNA methylation profiling.

Molecular brain tumor classification using DNA methylation profiling has revealed that the methylation-class of pleomorphic xanthoastrocytoma (mcPXA) comprised a substantial portion of divergent initial diagnoses, which had been established based on histology alone. This study aimed to characterize the survival outcome in patients with mcPXAs-in light of the diverse selected treatment regimes. A retrospective cohort of adult mcPXAs were analyzed in regard to their progression-free survival following surgical resection and postoperative radiotherapy. Radiotherapy treatment plans were correlated with follow-up images to characterize the pattern of relapse. Treatment toxicities and molecular tumor characteristics were further analyzed. Divergent initial histological diagnoses were encountered in 40.7%. There was no significant difference in local progression-free (PFS) and overall survival (OS) following gross total or subtotal resection. Postoperative radiotherapy was completed in 81% (22/27) following surgical intervention. Local PFS was 54.4% (95% CI: 35.3-84.0%) and OS was 81.3% (95% CI: 63.8-100%) after 3 years following postoperative radiotherapy. Initial relapses post-radiotherapy were primarily located in the previous tumor location and/or the planning target volume (PTV) (12/13). All patients in our cohort demonstrated the prognostically favorable pTERT-wildtype mcPXA. Our study demonstrated that adult patients with mcPXAs display a worse progression-free survival compared to the reported WHO grade 2 PXAs. Future matched-pair analyses are required with a non-irradiated cohort to elucidate the benefit of postoperative radiotherapy in adult patients with mcPXAs.

Events in CNS Tumor Pathology Post-2016 WHO CNS: cIMPACT-NOW Updates and Other Advancements: A Comprehensive Review Plus a Summary of the Salient Features of 2021 WHO CNS 5.

The 2016 World Health Organization Classification (WHO) of Tumors of the Central Nervous System (CNS) represented a major change. It recommended an "integrated diagnosis" comprising histologic and molecular information facilitating a more precise diagnosis of specific CNS tumors. Its goal was to provide greater diagnostic precision and reproducibility resulting in more clinical relevance and predictive value, ultimately leading to better patient care. Advances in molecular classification, mostly resulting from DNA methylation array profiling of CNS tumors, were occurring at a very rapid pace and required more rapid integration into clinical practice. cIMPACT-NOW updates and other recent papers plus salient features of 2021 WHO CNS5 in this comprehensive write-up were reviewed. CNS tumor classification needs to be updated at a rapid pace and mechanisms put into place to guide diagnosticians and clinicians in the interim period if major changes in the classification of tumor types came to light. Recognizing the need to integrate these into clinical practice more rapidly and without inordinate delay, the International Society of Neuropathology (ISN) 2016 sponsored an initiative called cIMPACT-NOW. Goal of cIMPACT-NOW was to provide clarification regarding contentious issues arising in the wake of the 2016 WHO CNS update as well as report new advancements in molecular classification of CNS tumors and new tumor entities emerging as a result of these advancements. cIMPACT-NOW updates: It thus laid the foundation for the 5th edition of the WHO Classification of CNS tumors (2021 WHO CNS 5). We have discussed cIMPACT updates in detail in this review. In addition, molecular diagnostics including DNA methylation-based classification of CNS tumors and the practical use of molecular classification in the prognostication and treatment of CNS tumors is discussed. Finally, the salient features of the new CNS tumor classification are summarized.

Abstract C034: Bioinformatical identification of cancer-associated-fibroblasts with tumor cells pro-migratory crosstalks depending on activin

Abstract Pancreatic ductal adenocarcinoma (PDAC) aggressiveness results from its high metastatic and chemoresistance potential. Pancreatic cancer cells are immersed in an exuberant tumor microenvironment (or stroma), which represents up to 80% of PDAC tumor volume, and is hijacked by cancer cells for their own survival and metastasis. Additionally, PDAC tumors are heterogeneous, e.g. transcriptomic (RNAseq) analyses of human PDAC tumors have allowed patients to be stratified into two tumor subgroups (basal and classical) with different prognoses. Therefore, we aimed to understand which tumor-stroma crosstalks are critical for PDAC aggressiveness in the context of its heterogeneity, and how they can be pharmacologically targeted, to then propose more effective personalized therapeutic strategies. By performing bioinformatical analysis on RNAseq data from PDX (Patient Derived Xenograft), a hybrid tumor model from which human-derived tumor cell sequences are distinguishable from murine-derived stromal cell sequences, we searched for different stromal behaviors linked to the tumor aggressiveness, to be then validated in published PDAC patient databases. According to NMF (Non-negative matrix factorization) and GSEA (Gene Set Enrichment Analyses), we identified two components, which classify the samples according to a stromal gradient. Interestingly, these components are characterized by distinct functional signatures of aggressiveness and they are highly prognostic (correlated with survival). In addition, these components stratify patients independently on the described molecular tumor (basal or classical) classification. Importantly, we validated those results on other PDAC published databases. Moreover, ligand-receptor bioinformatics analyses identified novel players of the TGFβ superfamily in the most aggressive stromal component. Indeed, we have highlighted the involvement of the ligand activin a member of this large superfamily. Using in situ hybridization coupled with immunofluorescence, we were able to demonstrate that activin is only expressed by stromal cells, and more specifically by cancer associated fibroblasts (CAF), with however a strong heterogeneity (inter and intra-tumor). In vitro, activin strongly increases the migratory capacity of fibroblasts but also of specific cancer cells, this effect being effectively blocked pharmacologically with an activin receptor-targeting drug that is now tested in a pre-clinical PDAC murine model. Therapeutic targeting of the stroma must take into account its functional heterogeneity. We have identified in specific aggressive PDAC tumors novel stromal players involved in the tumor-stroma symbiosis, and which presumably play a critical role in CAFs and cancer cells migration and invasion. Our work should enable to delineate which stroma-targeting drug to co-deliver, in addition to chemotherapies, in stratified patients, to improve PDAC prognosis. Citation Format: Alexia Brunel, Jérôme Raffenne, Remy Nicolle, Ilse Rooman, Elisa Espinet, Marjorie Fanjul, Aurélie Perraud, Muriel Mathonnet, Sophie Vasseur, Nelson Dusetti, Yvan Martineau, Christine Jean, Corinne Bousquet. Bioinformatical identification of cancer-associated-fibroblasts with tumor cells pro-migratory crosstalks depending on activin [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr C034.

BIOM-52. DIAGNOSTIC POTENTIAL OF EXTRACELLULAR VESICLES IN MENINGIOMA PATIENTS

Abstract Standard monitoring after meningioma resection relies on serial MRI examinations, which are time-consuming, expensive and provide no information on molecular alterations that may indicate progression towards a more aggressive tumor. Extracellular vesicles (EVs) secreted by tumor cells play an important role in cell-cell communication, and tumor-derived EVs circulating in patient blood can serve as biomarkers. We investigated the potential role of plasma EVs in meningioma patients for tumor detection and determined whether EVs secreted by meningioma cells reflect epigenetic, genomic and proteomic alterations of original tumors. EV concentrations were quantified in patient plasma (n = 46). Short-term meningioma cultures were established (n = 26) and secreted EVs were isolated. Methylation and copy number profiling was performed using 850k arrays, and mutations were identified by targeted gene panel sequencing. Differential quantitative mass spectrometry was employed for proteomic analysis. We found that the levels of circulating EVs were significantly elevated in meningioma patients compared to healthy individuals, and that plasma EV concentrations correlated with malignancy grade and extent of peritumoral edema. Postoperatively, EV counts dropped to normal levels, and the magnitude of the postoperative decrease was associated with extent of tumor resection (Simpson grade). Methylation profiling of EV-DNA allowed correct tumor classification as meningioma in all investigated cases, and accurate methylation subclass assignment in nearly all cases. Copy number variations present in tumors, as well as tumor-specific mutations were faithfully reflected in meningioma EV-DNA. Proteomic EV profiling did not permit original tumor identification but revealed tumor-associated proteins such as desmoplakin that could potentially be utilized to enrich meningioma EVs from biofluids. In conclusion, elevated EV levels in meningioma patient plasma may aid in tumor diagnosis and assessment of treatment response. Meningioma EV-DNA mirrors genetic and epigenetic tumor alterations and facilitates molecular tumor classification.