Molecular Stratification Research Articles

PATH-10. MULTI-OMICS PROFILING AND MACHINE LEARNING PROPOSE A REFINED MOLECULAR CLASSIFICATION SYSTEM FOR GLIOMA

Abstract Accurate molecular stratification of glioma patients is key to an optimal design of therapeutic strategy to maximize patient survival. Here we leveraged multi-omics analysis of glioma and detailed clinical follow-up to build a refined classification system for glioma patients using support vector machines. The model input included the number of non-synonymous mutations in cancer driver genes, the number of non-synonymous mutations in cancer related genes, the transcriptomic grouping information, the immune infiltrations predicted by RNA-seq dataset, the site of tumor occurrence, as well as other well-known markers including IDH mutation status and 1p19q co-deletion status. We validated key model predictions using TCGA and CGGA datasets. Our refined classification system outperforms current state-of-the-art framework used in clinic. Taken together, we propose a refined molecular classification for glioma combining multi-omics profiling and machine learning approaches.

Hybrid Cross-Discipline, Interactive Curriculum to Nurture the Training Experience for Hematology-Oncology Trainees

Introduction:Hematologic malignancy is a complex science that requires the integration of numerous advanced pathology techniques, including flow cytometry, genomic analysis, and molecular diagnostics, for diagnosis and risk stratification to guide management plans and optimize patient care.Understanding the methodology and proper utilization of new laboratory test methodologies relevant to patient care are required competencies for graduating hematology/oncology trainees, put forth by the Accreditation Council for Graduate Medical Education (ACGME). Therefore, these competencies are heavily tested on specialty board certification exams.We aimed at familiarizing our trainees with distinct laboratory test methodologies, and classifications of hematologic neoplasms from a hematopathologist's perspective. Simplifying such a complex science is a potential way to help trainees conceptualize the proper uses of several diagnostic tests. A shared understanding of clinical and pathologic approaches to hematologic malignancies will lead to improved advanced knowledge in the field, test-taking capabilities and reflect on patient care.We hypothesized that delivering cross-discipline training will improve the level of knowledge for our trainees, and reflect on the hematology in-training-exam scores and subsequently improve the American board of hematology participation and pass rates.Method:Curriculum Description:We developed a cross-discipline curriculum, three-month experience that included rigorous training in advanced hematopathology focused on hematologic malignancies. The curriculum included two hours per week, hybrid style interactive sessions –online/in-person classes–. A self-directed component included pre-class readings and pre- and post-weekly quizzes. The in-person sessions included interactive, case-based seminars guided by cross-discipline faculty members. Instructors for the curriculum included a malignant hematologist and a hematopathologist.The enrollment to the described curriculum made available for all hematology-oncology fellows, internal medicine residents, and advanced practice providers (APPs). This project was accomplished as part of the ASH Medical Educator Institute.Evaluation plan:Trainees were given pre- and post-intervention case-based exams as well as pre- and post-quizzes every week, to assess their knowledge and level of progression. For hematology fellows, trainee's performance on in-training exams (ITEs) was also compared to a historical control group of trainees from the same program.Results:The training included twenty-six participants, eight hematology-oncology fellows, five medical residents, six APPs, and seven faculty. Faculty participants were excluded from the performance evaluation to avoid bias introduction. Pre-class surveys and quizzes were collected to measure baseline knowledge of different hematology subjects and to guide the focus of the training based on common weaknesses amongst a majority of participants.Eighty-six percent of participants elected to attend the training to improve their clinical practice experience and exam scores, the rest intended to network academically. Before each session, participants finished the pre-session quizzes that was compared to the post-session quizzes. We report the persistent positive impact of the sessions on the trainees' weekly performances. We measured the overall impact of the training, comparing the pre-intervention exam with midterm and final exam scores, which also significantly increased compared to pre-intervention scores. (Figures 1 & 2)For hematology Oncology trainees, we also measured the impact of this training on their in-training-exam scores, compared to historical controls from the same fellowship program. For the hematology in-training exam scores, we noticed a significant improvement after the intervention for the year 2021 compared to the year 2020. An increase in the program means score, which reflected on the program overall performance with an increase in our percentile rank by approximately 14 points.Conclusion:Developing a cross-discipline interactive training curriculum is an innovative method to enhance the hematology-oncology trainees' experience. It promoted their level of knowledge and improved exam skills, which is reflected in the annual in-training exam scores. [Display omitted] DisclosuresEllis: Rafael Pharmaceuticals: Consultancy.

Differential Prognostic Impact of IDH1 and IDH2 Mutations in Chronic Myelomonocytic Leukemia

Introduction: Mutations involving isocitrate dehydrogenase 1/2 (IDH) are known oncogenic drivers in hematological malignancies, conferring neomorphic enzymatic activity to IDH 1/2, resulting in the oncometabolite, 2-hydroxyglutarae (2-HG). 2-HG in turn suppresses TET activity, making IDH and TET2 mutations synthetically lethal and almost mutually exclusive. The frequency of IDH mutations in CMML is <10% and their prognostic impact remains unclear. We carried out this study in a large database of molecularly annotated CMML patients to better define the clinical profile and prognostic impact of these mutations.Methods: After IRB approval, CMML patients from the Mayo Clinic, Minnesota and the Moffitt Cancer Center (MCC), Tampa, Florida, were included in the study. All patients had bone marrow (BM) biopsies with cytogenetics and molecular genetics done either at diagnosis, or at first referral. Clinical and mutational data were abstracted and retrospectively analyzed. Overall survival (OS) was calculated from date of CMML diagnosis to date of death/last follow, while AML-free survival (AML-FS) was calculated from date of CMML diagnosis to date of leukemic transformation (LT). Patients that had undergone allogeneic HCT were excluded from the study (n=3). Statistical analysis was carried out using the Blue Sky software.Results: Six hundred and forty four patients were included in the study (Mayo Clinic-357, MCC- 287), median age 71 years (range, 20-95 years), 67.8% being male. Forty-three (6.7%) patients had IDH mutations, 35 (82%) IDH2 and 8 (18%) IDH1; of which, 34 (97%) involved the IDH2R140 hotspot and 5 (62.5%) involved the IDH1R132 hotspot, respectively. The median variant allele fractions (VAF) for IDH1 mutations was 41% (range, 8-46%) and for IDH2 mutations was 46% (range, 7-70%). There were no significant demographic or clinical differences between IDH mutant and wild type CMML patients, with the exception that IDH mutant CMML patients were less likely to be thrombocytopenic (p=0.006), were less likely to have TET2 co-mutations (14% vs 53.2%; p<0.001) and were more likely to have SRSF2 co-mutations (69.8% VS 40.3%; p<0.001). Importantly there were no differences in proliferative or dysplastic subtypes (p=0.3), cytogenetic (p=0.12) and molecular risk stratifications (p=045). There were also no significant demographic or clinical differences between IDH1 vs IDH2 mutant CMML patients. Six (14%) IDH mutant CMML patients had TET2 co-mutations; 5 (83%) with IDH2R140Q (median VAF-28%;all male) and 1 (17%) with IDH1R132H (VAF-44%;female) (Figure 1). Five (11%) IDH2 mutant patients were treated with enasidenib (IDH2 inhibitor), none with a durable response, while none of the IDH1 mutant patients received targeted therapy.At last follow up (median 18 months), 337 (52%) deaths and 119 (18.5%) LT have been documented, with IDH mutant patients having a higher LT rate (30.2% vs 17.6%, p=0.04) compared to wildtype patients. The median OS of the entire cohort was 35 months, with no difference in OS between IDH mutant and wild type patients (34.5 vs 35 months, p=0.12), with IDH1 mutant patients having a shorter OS in comparison to IDH2 mutant patients (31 vs 37 months; p=0.005- Figure 1). IDH mutant CMML patients also had a shorter AML-FS in comparison to wild type patients (36.6 vs 210 months, p=0.005), with there being no differential impact on AML-FS of IDH1 vs IDH2 mutations (p=0.26, Figure 1).Conclusions: IDH mutations are infrequent in CMML (7%), with IDH2 mutations being more common than IDH1 mutations (80 vs 20%). IDH mutations co-occur very infrequently with TET2 mutations (14%), with IDH mutant patients being less likely to have thrombocytopenia and more likely to have SRSF2 co-mutations. IDH mutations negatively impacting AML-FS without a significant impact on OS. Prospective clinical trials testing the safety and efficacy of IDH1/2 inhibitors in CMML are much needed. [Display omitted] DisclosuresKomrokji: AbbVie: Consultancy; PharmaEssentia: Membership on an entity's Board of Directors or advisory committees; Taiho Oncology: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Jazz: Consultancy, Speakers Bureau; Acceleron: Consultancy; BMSCelgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Geron: Consultancy. Al-Kali: Novartis: Research Funding; Astex: Other: Research support to institution. Padron: BMS: Research Funding; Stemline: Honoraria; Taiho: Honoraria; Kura: Research Funding; Incyte: Research Funding; Blueprint: Honoraria. Patnaik: StemLine: Research Funding; Kura Oncology: Research Funding.

State-of-the-Art of Monoclonal Antibodies for the Treatment of Gastric Cancer.

Gastric cancer (GC) is a complex and heterogeneous disease with poor prognosis and limited available treatment options. During recent years, several molecular stratifications have been proposed to optimize the overall treatment strategy for GC patients. Breakthroughs in cancer biology and in molecular profiling through DNA and RNA sequencing are now opening novel landscapes, leading to the personalization of molecular matched therapy. In particular, therapies against HER2, Claudine 18.2, Fibroblast Growth Factor Receptors (FGFR), and other molecular alterations could significantly improve survival outcomes in the advance phase of the disease. Furthermore, immunotherapy with checkpoint inhibitors also represents a promising option in a selected population. Hoping that precision oncology will enter soon in clinical practice, our review describes the state of the art of many novel pathways and the current evidence supporting the use of monoclonal antibodies implicated in GC treatment.

Optimizing autologous hematopoietic stem cell transplantation for acute leukemia.

Autologous hematopoietic stem cell transplantation (ASCT) remains an important postremission treatment for acute leukemia (AL). It is known that some prognostic factors, such as age, cytogenetic and molecular risk stratification, and minimal residual disease (MRD) status, are closely related to clinical outcomes following ASCT. Moreover, there are multiple measurements, including pretransplant treatment, stem cell mobilization and collection, conditioning regimens, and maintenance treatment after transplantation, that can affect prognosis after ASCT. Our clinical practice of ASCT should be better standardized to further improve patient outcomes. This review outlines optimization and quality control measures for ASCT developed at the Institute of Hematology and Blood Diseases Hospital of the Chinese Academy of Medical Sciences, the first established and largest autologous stem cell transplant center in China. These measures will enhance the development of best practices and strategies for AL ASCT therapies, thereby improving patient outcomes.

In This Issue

In This Issue

Machine Learning-Based Prediction of Survival Outcome in Lower Grade Gliomas With Combined Clinical and DNA Methylation Data

Lower grade gliomas (LGG, World Health Organization Grade II and III) are characterized by variable clinical behavior and variable outcomes. While previously identified clinically molecular stratification factors add prognostic insight over histologic classification alone, significant heterogeneity exists with respect to overall outcome among patients. The purpose of this study was to evaluate nine machine learning algorithms on a combined clinical, mutational and methylation data of 293 adult LGGs.293 clinically annotated LGG samples with genome-wide methylation data available in the TCGA atlas were included in the study. Clinically relevant information included age at diagnosis, sex, IDH, TP53, ATRX mutations, 1p/19q status, tumor grade, histology, disease status and overall survival status. Methylation data of 450 genes with the highest variance across all samples were included. We used a total of nine machine learning algorithms in RapidMiner to evaluate the accuracy of each in predicting the overall survival status (deceased/living.) Those included tree-based and neural networks-based algorithms, support vector machine, and linear regression.Gradient boosted trees achieved the greatest predictive accuracy (86.76%, living and deceased class recall of 84.75% and 91.67%, respectively), followed by Decision Tree (84.52%, class recall of 85.25 and 82.61%, respectively). The largest weight in each model was disease-free status. Combined clinical and methylation data achieved greater sensitivity and specificity compared to either methylation or clinical data only: methylation data-based analysis without inclusion of clinical data achieved maximum accuracy of 79.56% with Deep Learning (living and deceased class recall of 95% and 39.13%, respectively), while clinical data-only based analysis showed highest accuracy of 89.16% with Random Forests, with a class recall for living and deceased of 98.36% and 63.64%, respectively.The combination of clinical and methylation data achieves a remarkable accuracy in predicting overall survival outcome in LGG patients, with highest overall class recall. The class recall (true positive rate or sensitivity) for deceased patients of combined data is superior to both clinical data-only and methylation data-only based analysis.

DNA Methylation Patterns in CD8+ T Cells Discern Psoriasis From Psoriatic Arthritis and Correlate With Cutaneous Disease Activity.

Background: Psoriasis is a T cell-mediated chronic autoimmune/inflammatory disease. While some patients experience disease limited to the skin (skin psoriasis), others develop joint involvement (psoriatic arthritis; PsA). In the absence of disease- and/or outcome-specific biomarkers, and as arthritis can precede skin manifestations, diagnostic and therapeutic delays are common and contribute to disease burden and damage accrual.Objective: Altered epigenetic marks, including DNA methylation, contribute to effector T cell phenotypes and altered cytokine expression in autoimmune/inflammatory diseases. This project aimed at the identification of disease-/outcome-specific DNA methylation signatures in CD8+ T cells from patients with psoriasis and PsA as compared to healthy controls.Method: Peripheral blood CD8+ T cells from nine healthy controls, 10 psoriasis, and seven PsA patients were collected to analyze DNA methylation marks using Illumina Human Methylation EPIC BeadChips (>850,000 CpGs per sample). Bioinformatic analysis was performed using R (minfi, limma, ChAMP, and DMRcate packages).Results: DNA methylation profiles in CD8+ T cells differentiate healthy controls from psoriasis patients [397 Differentially Methylated Positions (DMPs); 9 Differentially Methylated Regions (DMRs) when ≥CpGs per DMR were considered; 2 DMRs for ≥10 CpGs]. Furthermore, patients with skin psoriasis can be discriminated from PsA patients [1,861 DMPs, 20 DMRs (≥5 CpGs per region), 4 DMRs (≥10 CpGs per region)]. Gene ontology (GO) analyses considering genes with ≥1 DMP in their promoter delivered methylation defects in skin psoriasis and PsA primarily affecting the BMP signaling pathway and endopeptidase regulator activity, respectively. GO analysis of genes associated with DMRs between skin psoriasis and PsA demonstrated an enrichment of GABAergic neuron and cortex neuron development pathways. Treatment with cytokine blockers associated with DNA methylation changes [2,372 DMPs; 1,907 DMPs within promoters, 7 DMRs (≥5 CpG per regions)] affecting transforming growth factor beta receptor and transmembrane receptor protein serine/threonine kinase signaling pathways. Lastly, a methylation score including TNF and IL-17 pathway associated DMPs inverse correlates with skin disease activity scores (PASI).Conclusion: Patients with skin psoriasis exhibit DNA methylation patterns in CD8+ T cells that allow differentiation from PsA patients and healthy individuals, and reflect clinical activity of skin disease. Thus, DNA methylation profiling promises potential as diagnostic and prognostic tool to be used for molecular patient stratification toward individualized treatment.

Molecular Stratification of CKD

Molecular Stratification of CKD

Molecular Stratification of Childhood Ependymomas as a Basis for Personalized Diagnostics and Treatment.

Simple SummaryThe current trend in neuropathology directs to the integrated histo-molecular approach. The traditional concept of histological grade should be complemented by comprehensive diagnostics with the mandatory use of molecular genetic markers. As a consequence, basic types of CNS tumors fall into multiple nosological entities that can be morphologically similar while having fundamentally different pathogenesis and clinical presentation. This trend is particularly evident for ependymal tumors, which harbor molecular markers of decisive importance for the prognosis. This minireview emphasizes recent achievements in ependymoma biology research closely connected with state-of-the-art diagnostics.Ependymomas are among the most enigmatic tumors of the central nervous system, posing enormous challenges for pathologists and clinicians. Despite the efforts made, the treatment options are still limited to surgical resection and radiation therapy, while none of conventional chemotherapies is beneficial. While being histologically similar, ependymomas show considerable clinical and molecular diversity. Their histopathological evaluation alone is not sufficient for reliable diagnostics, prognosis, and choice of treatment strategy. The importance of integrated diagnosis for ependymomas is underscored in the recommendations of Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy. These updated recommendations were adopted and implemented by WHO experts. This minireview highlights recent advances in comprehensive molecular-genetic characterization of ependymomas. Strong emphasis is made on the use of molecular approaches for verification and specification of histological diagnoses, as well as identification of prognostic markers for ependymomas in children.

Comprehensive Analysis of TP53 and KEAP1 Mutations and Their Impact on Survival in Localized- and Advanced-Stage NSCLC

IntroductionTP53 and KEAP1 are frequently mutated in NSCLC, but their prognostic value is ambiguous, particularly in localized stage tumors. MethodsThis retrospective cohort study included a total of 6297 patients with NSCLC who were diagnosed between November 1998 and February 2020. The primary end point was overall survival. Patients were diagnosed in a central pathology laboratory as part of the Network Genomic Medicine collaboration, encompassing more than 300 lung cancer-treating oncology centers in Germany. All patients underwent molecular testing, including targeted next-generation panel sequencing and in situ hybridization. ResultsA total of 6297 patients with NSCLC were analyzed. In 1518 surgically treated patients (Union for International Cancer Control [UICC] I–IIIA), truncating TP53 mutations and KEAP1 mutations were independent negative prognostic markers in multivariable analysis (hazard ratio [HR]TP53truncating = 1.43, 95% confidence interval [CI]: 1.07–1.91, p = 0.015; HRKEAP1mut = 1.68, 95% CI:1.24–2.26, p = 0.001). Consistently, these mutations were associated with shorter disease-free survival. In 4779 patients with advanced-stage (UICC IIIB–IV) tumors, TP53 mutations did not predict outcome in univariable analysis. In contrast, KEAP1 mutations remained a negative prognostic factor (HRKEAP1mut = 1.40, 95% CI: 1.23–1.61, p < 0.001) in patients with advanced-stage tumors. Furthermore, those with KEAP1-mutant tumors with co-occurring TP53 missense mutations had longer overall survival than those with KEAP1-mutant tumors with wild-type or truncating TP53 mutations. ConclusionsThis study found that TP53 and KEAP1 mutations were prognostic for localized and advanced-stage NSCLC. The increased relative hazard of harboring TP53 or KEAP1 mutations was comparable to an increase in one UICC stage. Our data suggest that molecular stratification on the basis of TP53 and KEAP1 mutation status should be implemented for localized and advanced-stage NSCLC to optimize and modify clinical decision-making.

Association between delay in intensive care unit admission and the host response in patients with community-acquired pneumonia

BackgroundA delay in admission to the intensive care unit (ICU) of patients with community-acquired pneumonia (CAP) has been associated with an increased mortality. Decisions regarding interventions and eligibility for immune modulatory therapy are often made at the time of admission to the ICU. The primary aim of this study was to compare the host immune response measured upon ICU admission in CAP patients admitted immediately from the emergency department (direct ICU admission) with those who were transferred within 72 h after admission to the general ward (delayed ICU admission).MethodsSixteen host response biomarkers providing insight in pathophysiological mechanisms implicated in sepsis and blood leukocyte transcriptomes were analysed in patients with CAP upon ICU admission in two tertiary hospitals in the Netherlands.ResultsOf 530 ICU admissions with CAP, 387 (73.0%) were directly admitted and 143 (27.0%) had a delayed admission. Patients with a delayed ICU admission were more often immunocompromised (35.0 versus 21.2%, P = .002) and had more malignancies (23.1 versus 13.4%, P = .011). Shock was more present in patients who were admitted to the ICU directly (46.6 versus 33.6%, P = .010). Delayed ICU admission was not associated with an increased hospital mortality risk (hazard ratio 1.25, 95% CI 0.89–1.78, P = .20). The plasma levels of biomarkers (n = 297) reflecting systemic inflammation, endothelial cell activation and coagulation activation were largely similar between groups, with exception of C-reactive protein, soluble intercellular adhesion molecule-1 and angiopoietin-1, which were more aberrant in delayed admissions compared to direct ICU admissions. Blood leukocyte transcriptomes (n = 132) of patients with a delayed ICU admission showed blunted innate and adaptive immune response signalling when compared with direct ICU admissions, as well as decreased gene expression associated with tissue repair and extracellular matrix remodelling pathways.ConclusionsBlood leukocytes of CAP patients with delayed ICU admission show evidence of a more immune suppressive phenotype upon ICU admission when compared with blood leukocytes from patients directly transferred to the ICU.Trial registration: Molecular Diagnosis and Risk Stratification of Sepsis (MARS) project, ClinicalTrials.gov identifier NCT01905033.

Pre-treatment risk assessment of women with endometrial cancer: differences in outcomes of molecular and clinical classifications in the Slovenian patient cohort.

BackgroundThe aim of this study was to evaluate changes in prognostic risk profiles of women with endometrial cancer by comparing the clinical risk assessment with the integrated molecular risk assessment profiling.Patients and methodsThis prospective study recruited patients with biopsy proven endometrial cancer treated at the University Medical Centre Maribor between January 2020 to February 2021. Patient clinical data was assessed and categorized according to the currently valid European Society of Gynaecological Oncology, European SocieTy for Radiotherapy and Oncology, and European Society of Pathology (ESGO/ESTRO/ESP) guidelines on endometrial cancer. Molecular tumour characterization included determination of exonuclease domain of DNA polymerase-epsilon (POLE) mutational status by Sanger sequencing and imunohistochemical specimen evaluation on the presence of mismatch repair deficiencies (MMRd) and p53 abnormalities (p53abn).ResultsFourty-five women were included in the study. Twenty-two tumours were of non-specific mutational profile (NSMP) (56.4%), 13 were classified as MMRd (33.3%), 3 were classified as p53abn (7.7%) and 1 was classified as POLE mutated (2.6%). Six tumours (15.4%) had multiple molecular classifiers, these were studied separately and were not included in the risk assessment. The clinical risk-assessment classified 21 women (53.8%) as low-risk, 5 women (12.8%) as intermediate risk, 2 women as high-intermediate risk (5.1%), 10 women (25.6%) as high risk and 1 patient as advanced metastatic (2.6%). The integrated molecular classification changed risk for 4 women (10.3%).ConclusionsIntegrated molecular risk improves personalized risk assessment in endometrial cancer and could potentially improve therapeutic precision. Further molecular stratification with biomarkers is especially needed in the NSMP group to improve personalized risk-assessment.

Highlights from Recent Cancer Literature

Highlights from Recent Cancer Literature

Differential impact of clinicopathological risk factors within the 2 largest ProMisE molecular subgroups of endometrial carcinoma.

ObjectiveTo assess whether the prognostic impact of conventional risk factors and ancillary biomarkers differs across the 2 largest ProMisE molecular subgroups of endometrial carcinoma (EC).MethodsDirect sequencing of POLE exonuclease domain hot spots and immunohistochemistry for MLH1, PMS2, MSH2, MSH6 and p53 were performed on 745 unselected endometrioid ECs to identify mismatch repair deficient (MMR-D, n = 264) and no specific molecular profile (NSMP, n = 206) ECs. Molecular group-specific survival analyses and interaction analyses were performed to determine the prognostic relevance of clinicopathological factors and various biomarkers (L1 cell adhesion molecule, estrogen and progesterone receptor, beta-catenin, p16, E-cadherin, KRAS) within the subgroups.ResultsMolecular subgroup did not have an independent effect on disease-specific survival after adjustment for conventional risk factors (P = 0.101). High grade (G3) and p16 hyperexpression remained significant predictors of survival in NSMP. Stage II-IV, ≥50% myometrial invasion, lymphovascular space invasion and loss of E-cadherin were independent predictors in the MMR-D group. In the interaction analysis, molecular subclass significantly modified the prognostic effect of high grade and p16 hyperexpression, which showed a stronger negative effect on survival in NSMP as compared to MMR-D (P for interaction = 0.016 for grade and 0.033 for p16).ConclusionsGrade of differentiation and p16 hyperexpression appear to have a stronger prognostic impact in NSMP as compared to MMR-D EC. While these results need to be confirmed in a larger study population, they indicate that differential impact of risk factors needs to be taken into account when developing new molecular class-integrated risk stratification algorithms for EC.

TCR Clonality and Genomic Instability Signatures as Prognostic Biomarkers in High Grade Serous Ovarian Cancer.

Simple SummaryHigh-grade serous ovarian carcinoma (HGSC) could be analyzed with a molecular stratification defined by different genomic instability signatures associated with specific mutational process and prognostic biomarkers. Immune infiltrate is known to be a robust biomarker in HGSC. We aimed to investigate immune parameters according to genomic instability signatures. We observed that homologous recombination deficiency positive, copy cumber variant signature 7 and TCR (T cells receptor) clonality are good prognostic biomarkers in HGSC. Combining TCR clonality and genomic instability signature or T cell infiltration improved the prognostic value compared to each variable taken alone. We provided a description of immune parameters according to different genomic instability signatures. We identified TCR clonality, alone or combined with genomic instability, as a promising prognostic biomarker in HGSC.Purpose: Immune infiltration is a prognostic factor in high-grade serous ovarian carcinoma (HGSC) but immunotherapy efficacy is disappointing. Genomic instability is now used to guide the therapeutic value of PARP inhibitors. We aimed to investigate exome-derived parameters to assess the tumor microenvironment according to genomic instability profile. Methods: We used the HGSC TCGA (the cancer genome atlas) dataset with genomic characteristics, including homologous recombination deficiency (HRD), copy number variant (CNV) signatures, TCR (T cell receptor) clonality and abundance of tissue-infiltrating immune and stromal cell populations. We then investigated the relationship with survival data. Results: In 578 HGSC patients, HRD status, CNV signature 7 and TCR clonality were associated with longer survival. The combination of high CNV signature 7 expression and HRD status or high CNV signature 3 expression and high TCR clonality was associated with a trend towards longer survival compared to each variable alone. Combining T cell infiltrate and TCR clonality improved the prognostic value compared to T cells infiltration alone. Prognostic value of TCR clonality was confirmed in an independent cohort. Conclusions: TCR clonality is an emerging prognostic biomarker that improves T cell infiltrate information. Analysis of TCR clonality combined with genomic instability could be an interesting prognostic biomarker.

Copy Number Signatures and Clinical Outcomes in Upper Tract Urothelial Carcinoma

Tumor staging of upper tract urothelial carcinomas (UTUCs) is relatively difficult to assert accurately before surgery. Here, we used copy number (CN) signatures as a tool to explore their clinical significance of molecular stratification in UTUC. CN signatures were extracted by non-negative matrix factorization from the whole-genome sequencing (WGS) data of 90 Chinese UTUC primary tumor samples. A validation UTUC cohort (n = 56) and a cohort from urinary cell-free DNA (cfDNA) of urothelial cancer patients (n = 94) and matched primary tumors were also examined. Survival analyses were measured using the Kaplan–Meier, and Cox regression was used for multivariate analysis. Here, we identified six CN signatures (Sig1–6). Patients with a high contribution of Sig6 (Sig6high) were associated with higher microsatellite instability level and papillary architecture and had a favorable outcome. Patients with a low weighted genome integrity index were associated with positive lymph node and showed the worst outcome. Sig6high was identified to be an independently prognostic factor. The predictive significance of CN signature was identified by a validation UTUC cohort. CN signatures retained great concordance between primary tumor and urinary cfDNA. In conclusion, our results reveal that CN signature assessment for risk stratification is feasible and provides a basis for clinical studies that evaluate therapeutic interventions and prognosis.

Molecular Risk Stratification is Independent of EGFR Mutation Status in Identifying Early-Stage Non–Squamous Non–Small Cell Lung Cancer Patients at Risk for Recurrence and Likely to Benefit From Adjuvant Chemotherapy

BackgroundA clinically-certified gene expression profile improved survival in a cohort of stage I-IIA NSCLC patients by identifying those likely to benefit from adjuvant intervention. EGFR mutation status has not provided this type of predictive risk discrimination in stage IA NSCLC, and overtreatment of low-risk stage IB patients may have limited the overall benefit seen recently in the adjuvant application of a third-generation TKI. We compared EGFR mutation data to molecular risk stratification in a prospective, early-stage cohort. Materials and MethodsTwo hundred fifty eligible stage I-IIA non–squamous NSCLC patients underwent prospective molecular risk stratification by the 14-gene prognostic assay. Platinum doublet adjuvant chemotherapy (AC) was recommended for molecular high-risk (MHR). Differences in freedom from recurrence (FFR) and disease-free survival (DFS) were evaluated. ResultsAt 29 months, prospective molecular testing yielded an estimated FFR of 94.6% and 72.4% in low-risk and untreated MHR patients, respectively, and 97.0% among MHR patients receiving AC (P < .001). In contrast, there was no association between EGFR status and recurrence, while molecular risk predicted survival and response to AC within both the EGFR mutation(+) and mutation(-) populations. Sixty-seven percent of EGFR(+) and 49% of EGFR(-) patients were molecular low-risk. ConclusionThis prospective study demonstrates the utility of the 14-gene assay independent of EGFR mutation. Basing adjuvant intervention in early-stage NSCLC on EGFR status alone may undertreat up to 51% of EGFR(-) patients likely to benefit from adjuvant intervention, and overtreat as many as 67% of EGFR(+) patients more likely to be free of residual disease.

Subgroup and subtype-specific outcomes in adult medulloblastoma.

Medulloblastoma, a common pediatric malignant central nervous system tumour, represent a small proportion of brain tumours in adults. Previously it has been shown that in adults, Sonic Hedgehog (SHH)-activated tumours predominate, with Wingless-type (WNT) and Group 4 being less common, but molecular risk stratification remains a challenge. We performed an integrated analysis consisting of genome-wide methylation profiling, copy number profiling, somatic nucleotide variants and correlation of clinical variables across a cohort of 191 adult medulloblastoma cases identified through the Medulloblastoma Advanced Genomics International Consortium. We identified 30 WNT, 112 SHH, 6 Group 3, and 41 Group 4 tumours. Patients with SHH tumours were significantly older at diagnosis compared to other subgroups (p < 0.0001). Five-year progression-free survival (PFS) for WNT, SHH, Group 3, and Group 4 tumours was 64.4 (48.0-86.5), 61.9% (51.6-74.2), 80.0% (95% CI 51.6-100.0), and 44.9% (95% CI 28.6-70.7), respectively (p = 0.06). None of the clinical variables (age, sex, metastatic status, extent of resection, chemotherapy, radiotherapy) were associated with subgroup-specific PFS. Survival among patients with SHH tumours was significantly worse for cases with chromosome 3p loss (HR 2.9, 95% CI 1.1-7.6; p = 0.02), chromosome 10q loss (HR 4.6, 95% CI 2.3-9.4; p < 0.0001), chromosome 17p loss (HR 2.3, 95% CI 1.1-4.8; p = 0.02), and PTCH1 mutations (HR 2.6, 95% CI 1.1-6.2; p = 0.04). The prognostic significance of 3p loss and 10q loss persisted in multivariable regression models. For Group 4 tumours, chromosome 8 loss was strongly associated with improved survival, which was validated in a non-overlapping cohort (combined cohort HR 0.2, 95% CI 0.1-0.7; p = 0.007). Unlike in pediatric medulloblastoma, whole chromosome 11 loss in Group 4 and chromosome 14q loss in SHH was not associated with improved survival, where MYCN, GLI2 and MYC amplification were rare. In sum, we report unique subgroup-specific cytogenetic features of adult medulloblastoma, which are distinct from those in younger patients, and correlate with survival disparities. Our findings suggest that clinical trials that incorporate new strategies tailored to high-risk adult medulloblastoma patients are urgently needed.

Ductal adenocarcinoma of the pancreas: subtypes and molecular pathology

Ductal adenocarcinoma is the most common tumor of the pancreas. Although relatively rare, it poses one of the greatest oncological challenges because of its poor prognosis, which has so far only slightly improved. Progress has been made in the more precise classification and standardization of the morphological assessment. In the current WHO classification, prognostically relevant subtypes are clearly delimited among themselves and from ductal adenocarcinoma not otherwise specified (NOS). In the recent TNM classification, asize-based T‑category was introduced. Diagnostically, the histological assessment of the resection specimen is relatively easy; on the other hand, assessment of the fine-needle biopsy from the primary tumor or aliver metastasis is still difficult. The molecular stratification of ductal adenocarcinoma and the other pancreatic neoplasms has made great progress. This not only defined the genetics of tumor entities, but also identified the prognosis and biology of tumor groups on the basis of RNA expression patterns. The range of treatment could be expanded by targeted molecular therapies (especially for patients with BRCA1/2 germline mutations, NTRK- or NRG1-fusions, or oncogenic BRAF and PIK3CA mutations as well as tumors with microsatellite instability (MSI)), even if targeted therapies are currently only available for aminority of patients (<10%).