Gene Copy Number Alterations Research Articles

FISH Panel for Leukemic Cutaneous T-Cell Lymphoma: Extended Patient Cohort Correlation with Blood Involvement and Clinical Outcomes

The genomic basis of cutaneous T-cell lymphoma has been characterized by gene copy number alterations and genomic sequencing, but there are few clinical tests that are being widely used to inform the diagnosis and prognosis of leukemic cutaneous T-cell lymphoma that may arise as a progression from mycosis fungoides or de novo as Sézary syndrome. An 11-gene FISH panel of TP53, RB1, DNMT3A, FAS, ZEB1, ARID1A, ATM, and CDKN2A deletions and MYC, signal transducer and activator of transcription gene (STAT)3/5B, and CARD11 amplifications was previously found to encapsulate >95% of gene copy number variations in leukemic cutaneous T-cell lymphoma. Through a retrospective analysis of patients with leukemic cutaneous T-cell lymphoma seen at the Yale Cancer Center from 2014 to 2020, we gathered the relevant genes as they became available and correlated them to factors with prognostic relevance as a proof of concept to show the potential utility in further developing a limited gene panel for prognosis. In this study, we show that the abnormal FISH results show an association with clinically relevant factors (blood stage, CD4:8 ratio, and percentage blood involvement) and have a nonsignificant statistical trend (>90%) toward correlation with overall survival. In addition, the previous cost-effective panels were signal transducer and activator of transcription (STAT)3/5B, MYC, TP53, and ARID1A. We now suggest adding RB1 and ZEB1 on the basis of our findings.

The value of molecular testing in the evaluation and management of patients with pancreatic cysts.

Molecular testing aids in the work up and management of patients with pancreatic cysts. This study reports on the value of PancreaSeq® in the evaluation of pancreatic cyst aspirates. PancreaSeq® testing at our institution was implemented June 1, 2022. Over a 7-month period (June 1, 2022 through December 31, 2022) 50 cyst aspirates of which 26 (52%) were non-diagnostic 4 (8%) negative 1 (2%) atypical, 17 (34%) suspicious for a mucinous cystic neoplasm (MCN) and 2 (4%) positive for a MCN on cytology were sent for testing. KRAS/GNAS gene mutations were present in 15 non-diagnostic cases and 5 cases suspicious for an MCN. The type of cyst was interpreted as mucinous (IPMN) and the risk of progression to high grade dysplasia/adenocarcinoma as low. KRAS mutations were present in 8 non-diagnostic cases, 1 atypical case, 8 cases suspicious for a MCN and one case positive for an MCN; findings interpreted as a mucinous cyst (IPMN/MCN) with a low risk of progression. BRAF mutations were present in 2 cases; one suspicious and the second positive for an MCN; both interpreted as a mucinous cyst (IPMN) with a low risk of progression. One non-diagnostic case was positive for several gene mutations and copy number alterations; findings interpreted as a mucinous (IPMN) cyst with an elevated risk of progression. VHL mutations were present in 2 negative cases interpreted as serous cystadenomas. Two non-diagnostic, 2 negative and 2 cases suspicious for a MCN were negative for gene mutations. Implementation of PancreaSeq® has led to improvements in clinical management of patients with pancreatic cysts.

Creation of EGD-Derived Gastric Cancer Organoids to Predict Treatment Responses.

Gastric adenocarcinoma (GAd) is the third leading cause of cancer-related deaths worldwide. Most patients require perioperative chemotherapy, yet methods to accurately predict responses to therapy are lacking. Thus, patients may be unnecessarily exposed to considerable toxicities. Here, we present a novel methodology using patient-derived organoids (PDOs) that rapidly and accurately predicts the chemotherapy efficacy for GAd patients. Methods:Endoscopic GAd biopsies were obtained from 19 patients, shipped overnight, and PDOs were developed within 24 h. Drug sensitivity testing was performed on PDO single-cells with current standard-of-care systemic GAd regimens and cell viability was measured. Whole exome sequencing was used to confirm the consistency of tumor-related gene mutations and copy number alterations between primary tumors, PDOs, and PDO single-cells. Results:Overall, 15 of 19 biopsies (79%) were appropriate for PDO creation and single-cell expansion within 24 h of specimen collection and overnight shipment. With our PDO single-cell technique, PDOs (53%) were successfully developed. Subsequently, two PDO lines were subjected to drug sensitivity testing within 12 days from initial biopsy procurement. Drug sensitivity assays revealed unique treatment response profiles for combination drug regimens in both of the two unique PDOs, which corresponded with the clinical response. Conclusions:The successful creation of PDOs within 24 h of endoscopic biopsy and rapid drug testing within 2 weeks demonstrate the feasibility of our novel approach for future applications in clinical decision making. This proof of concept sets the foundation for future clinical trials using PDOs to predict clinical responses to GAd therapies.

Integrative genomic and transcriptomic analysis reveals genetic alterations associated with the early progression of follicular lymphoma

Introduction: Follicular lymphoma (FL), the most common indolent lymphoma, is a clinically and genetically heterogeneous disease. Progression of disease within 24 months (POD24) is strongly associated with poor outcome. Therefore, prediction of POD24 at diagnosis is essential to support the precision medicine treatment strategies making in clinical practice. However, risk factors associated with POD24 remain uncertain in FL patients. In addition, the prognostic value of driver gene mutations and copy number alterations has not been systematically assessed in FL. Method: We analysed clinical-biological features of 415 FL patients to identify variables associated with POD24. In addition, we integrated whole exome sequencing (WES) and transcriptomic analysis of 102 these patients with FL to identify genetic alterations associated with early progression. Result: POD24 occurred in 21% of evaluable FL patients, with a 5-year OS rate of 82.9% compared with 96.2% for those without POD24 (HR, 5.03; 95% CI, 2.15–11.72; P < 0.01). Patients with B symptoms, elevated lactate dehydrogenase and β2-microglobulin levels, unfavourable baseline haemoglobin levels, advanced stage, and high-risk FL International Prognostic Index (FLIPI) scores had an increased risk of POD24, with FLIPI being the most important factor in logistic regression. Among all the somatically occurring non-silent mutations, twenty-three genes were considered cancer drivers. HIST1H1D, known as a driver mutation, was significantly correlated with POD24. Gains of 6q22.2 (HIST1H1D) and 18q21.33 (BCL2) and loss of 1p36.13 (NBPF1) predicted POD24 independent of FLIPI. Integration of the four variants led to the identification of 76% of POD24 patients. Gene expression profiling (GEP) of 41 FL samples showed that the POD24 cohort was significantly enriched in the inflammatory response (mediated by interferon and tumour necrosis factor) and cell cycle regulation (transcription, replication and proliferation) sets. Keywords: Diagnostic and Prognostic Biomarkers, Genomics, Epigenomics, and Other -Omics, Indolent non-Hodgkin lymphoma No conflicts of interests pertinent to the abstract.

Molecular Profiles of Noninvasive, Minimally Invasive, and Invasive Follicular Patterned Thyroid Neoplasms with Papillary Nuclear Features.

Background: An increasing amount of data is being published, which risk-stratify thyroid tumors according to genetic signatures and histological morphology. Typically, follicular patterned lesions have been shown to harbor RAS-like mutations with more indolent behaviors. Our study aims to examine the extent of similarity among three groups of follicular patterned lesions with papillary nuclear features-noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), encapsulated follicular variant of papillary thyroid carcinoma (EFVPTC) with capsular invasion and/or angioinvasion, and infiltrative follicular variant of papillary thyroid carcinoma (iFVPTC)-to help clarify whether NIFTP and EFVPTC represent a histological continuum and the degree to which the genomic landscape further separates higher risk follicular patterned tumors such as iFVPTC from more indolent ones (EFVPTC and NIFTP). Methods: ThyroSeq test results were compared for cases with histological NIFTP, EFVPTC, and iFVPTC in this retrospective study. Genetic drivers were subcategorized by level of aggressiveness. Gene expression alterations (GEAs) and copy number alterations (CNAs) were compared among the three histological groups. Results: NIFTP and EFVPTC cases displayed predominantly RAS-like alterations (100% and 75%, respectively) and RAS-like GEAs (55.2% and 47.2%, respectively), and many showed CNAs with 22q-loss. Despite a predominance of RAS-like alterations, EFVPTC cases showed molecular heterogeneity with significantly more intermediate and aggressive drivers (22.3% of cases) than NIFTP (0%) (p = 0.0068). iFVPTC cases displayed molecular profiles in between that of traditional follicular patterned lesions and classical papillary thyroid carcinoma, predominantly displaying intermediate and aggressive drivers (61.6%), which was significantly higher than that of EFVPTC (22.3%, p = 0.0158) and NIFTP (0%, p < 0.0001), illustrating the higher MAP kinase activity of iFVPTC. There was no significant difference, however, in comparing GEAs among the three histological groups. Conclusions: While follicular patterned lesions with papillary nuclear features overall tend to display RAS-like alterations, EFVPTC cases, followed by iFVPTC in this series, showed increasing proportions of more aggressive drivers. EFVPTC and NIFTP show much molecular overlap, with predominance of RAS-like alterations, suggesting that these tumors are part of a genetic continuum, while still ranked differentially. Preoperative molecular testing can potentially distinguish EFVPTC and iFVTPC from NIFTP based on a particular molecular signature, optimizing patient management.

CVAM: CNA Profile Inference of the Spatial Transcriptome Based on the VGAE and HMM.

Tumors are often polyclonal due to copy number alteration (CNA) events. Through the CNA profile, we can understand the tumor heterogeneity and consistency. CNA information is usually obtained through DNA sequencing. However, many existing studies have shown a positive correlation between the gene expression and gene copy number identified from DNA sequencing. With the development of spatial transcriptome technologies, it is urgent to develop new tools to identify genomic variation from the spatial transcriptome. Therefore, in this study, we developed CVAM, a tool to infer the CNA profile from spatial transcriptome data. Compared with existing tools, CVAM integrates the spatial information with the spot's gene expression information together and the spatial information is indirectly introduced into the CNA inference. By applying CVAM to simulated and real spatial transcriptome data, we found that CVAM performed better in identifying CNA events. In addition, we analyzed the potential co-occurrence and mutual exclusion between CNA events in tumor clusters, which is helpful to analyze the potential interaction between genes in mutation. Last but not least, Ripley's K-function is also applied to CNA multi-distance spatial pattern analysis so that we can figure out the differences of different gene CNA events in spatial distribution, which is helpful for tumor analysis and implementing more effective treatment measures based on spatial characteristics of genes.

Prognostic Values of Gene Copy Number Alterations in Prostate Cancer

Whilst risk prediction for individual prostate cancer (PCa) cases is of a high priority, the current risk stratification indices for PCa management have severe limitations. This study aimed to identify gene copy number alterations (CNAs) with prognostic values and to determine if any combination of gene CNAs could have risk stratification potentials. Clinical and genomic data of 500 PCa cases from the Cancer Genome Atlas stable were retrieved from the Genomic Data Commons and cBioPortal databases. The CNA statuses of a total of 52 genetic markers, including 21 novel markers and 31 previously identified potential prognostic markers, were tested for prognostic significance. The CNA statuses of a total of 51/52 genetic markers were significantly associated with advanced disease at an odds ratio threshold of ≥1.5 or ≤0.667. Moreover, a Kaplan-Meier test identified 27/52 marker CNAs which correlated with disease progression. A Cox Regression analysis showed that the amplification of MIR602 and deletions of MIR602, ZNF267, MROH1, PARP8, and HCN1 correlated with a progression-free survival independent of the disease stage and Gleason prognostic group grade. Furthermore, a binary logistic regression analysis identified twenty-two panels of markers with risk stratification potentials. The best model of 7/52 genetic CNAs, which included the SPOP alteration, SPP1 alteration, CCND1 amplification, PTEN deletion, CDKN1B deletion, PARP8 deletion, and NKX3.1 deletion, stratified the PCa cases into a localised and advanced disease with an accuracy of 70.0%, sensitivity of 85.4%, specificity of 44.9%, positive predictive value of 71.67%, and negative predictive value of 65.35%. This study validated prognostic gene level CNAs identified in previous studies, as well as identified new genetic markers with CNAs that could potentially impact risk stratification in PCa.

Abstract 2508: Clinical significance of PARP7 (TIPARP) gene copy number alterations in human non-small cell and head &amp; neck carcinomas

Abstract Introduction: PARP7, encoded by the TIPARP gene, is a monoART involved in cellular stress responses and with immunomodulatory functions in cancer. The PARP7 gene is amplified in a subset of squamous cell carcinomas and ongoing clinical studies are assessing its role as anti-cancer therapeutic target (NCT04053673, NCT05127590) Here, we analyzed the frequency of PARP7 copy number alterations and its association with tumor immune microenvironment (TIME) features and outcomes in non-small cell lung cancer (NSCLC) and head &amp; neck squamous-cell carcinoma (HNSCC) cohorts. Methods: The PARP7 gene copy number and amplification was analyzed using a dual probe fluorescence in situ hybridization (FISH) assay in two retrospective cohorts of NSCLC (Cohort #1, n=124) and HNSCC (Cohort #2, n=83) represented in tissue microarray format. In a subset of cases, the PARP7 copy number was also studied using whole exome DNA sequencing. The TIME was assessed on consecutive tumor sections using a multiplexed quantitative immunofluorescence panel including the markers DAPI, cytokeratin, CD4, CD8 and PD-L1 coupled to computational pathology analysis. The association between the markers, with clinicopathologic variables and survival was studied. Results: Increased PARP7 copy number (&amp;gt;2 copies/cell) was identified in 55% of NSCLCs (85% of them of squamous-cell histology) and 76% of HNSCCs. A high copy number (&amp;gt;3 copies/cell) was identified in 22% cases from both tumor type cohorts. After adjustment of the PARP7 gene copy number by the chromosome 3 centromeric probe (CEN3) signal, PARP7 amplification (&amp;gt;1.5 PARP7/CEN3 signal) was detected in 22% of NSCLC cases and 34% of HNSCC. A higher number of cases with PARP7 copy number gains were identified using FISH than with whole exome DNA sequencing. No significant associations between the PARP7 gains/losses and major clinicopathologic variables were found. However, higher PARP7 copy number was associated with reduced CD8+ or CD4+ tumor infiltrating lymphocytes (TILs) and a numerically lower tumor PD-L1 protein levels in HNSCC. Elevated PARP7 copy number was associated with shorter overall survival in both studied tumor types. Conclusion: Elevated PARP7 gene copy number identifies a subset of lung and head &amp; neck squamous-cell carcinomas with unfavorable TIME features and adverse prognosis. Detection of PARP7 gene abnormalities using FISH in tumor biopsy samples is sensitive and has potential as a predictive biomarker. Citation Format: Viviana A. Ahumada, Kristen McEachern, Kristy Kuplast-Barr, Kurt Alex Schalper. Clinical significance of PARP7 (TIPARP) gene copy number alterations in human non-small cell and head &amp; neck carcinomas [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 2508.

Abstract 130: Distinct mutational drivers and evolutionary pathways in stage IA non-myoinvasive endometrioid endometrial cancer

Abstract Background: Endometrioid endometrial cancer (EC), the most common histologic type of EC, is underpinned by somatic genetic alterations of genes in the PI3K and MAPK pathways, and ARID1A. Here we sought to evaluate the genomic landscape of stage IA, low-volume, non-myometrial invasive ECs to define the earliest drivers and tumor evolution of endometrioid EC. Methods: Early-stage, non-myoinvasive EC of patients who underwent surgery at our institution and were subjected to clinical tumor-normal targeted sequencing of up to 505 cancer-related genes. Tumor volume was determined based on the gross and histologic measurements, and the tumors were dichotomized into low- and high- volume disease using a cutoff of 1 cm3. Genomic data was extracted and cancer cell fractions (CCF) of the somatic mutations were determined using ABSOLUTE integrating the mutational variant allele frequency and copy number alterations. Results: A total of 160 non-invasive, stage I ECs were identified, of which the majority (n=128; 80%) were FIGO grade 1 (15.6% grade 2, 3.1% grade 3). The median calculated volume of disease was 1.3 cm3, and 18 cases did not have gross disease with only microscopic disease identified on pathologic evaluation. The tumors on average had 6.7 somatic mutations affecting known EC cancer-related genes, including PTEN (n=127; 79%), ARID1A (n=84; 52.5%), PIK3CA (n=81; 50.6%), CTNNB1 (n=61; 38.1%), PIK3R1 (n=59; 36.8%) and KRAS (n=48; 30%). None of the alterations showed a significant correlation with tumor volume. Analysis of the CCF revealed that in 43% of ECs (69/160)[WB1] , PTEN mutations were clonal and had the highest CCF, indicating that PTEN mutation is most likely the initiating carcinogenic event. In other subsets of the early-stage ECs studied, the highest CCFs were mutations affecting PIK3CA/PIK3R1 (n=26), ARID1A (n=17), and KRAS (n=16). We also found that 109 (68%) ECs harbored activating mutations involving at least two genes in the PI3K/AKT/mTOR pathway, with the most common combination being PTEN/PIK3CA or PTEN/PIK3R1. AKT1 mutations occurred in absence of other PI3K/AKT/mTOR pathway alterations. Unsupervised Louvain clustering based on somatic mutations and gene copy number alterations revealed 5 distinct clusters of ECs with unique mutational drivers. Conclusion: Stage IA non-myoinvasive ECs show considerable genomic heterogeneity suggestive of multiple evolutionary pathways. Further studies are warranted to define whether this heterogeneity is a sign of early genomic drift (i.e. neutral tumor evolution) or whether the various evolutionary pathways all confer similar selective advantages. Citation Format: Sara Moufarrij, Carol Aghajanian, Nadeem Abu Rustum, Lora Ellenson, Britta Weigelt, Amir Momeni. Distinct mutational drivers and evolutionary pathways in stage IA non-myoinvasive endometrioid endometrial 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 130.

Multimodal adversarial representation learning for breast cancer prognosis prediction

With the increasing incidence of breast cancer, accurate prognosis prediction of breast cancer patients is a key issue in current cancer research, and it is also of great significance for patients’ psychological rehabilitation and assisting clinical decision-making. Many studies that integrate data from different heterogeneous modalities such as gene expression profile, clinical data, and copy number alteration, have achieved greater success than those with only one modality in prognostic prediction. However, many of these approaches that exist fail to dramatically reduce the modality gap by aligning multimodal distributions. Therefore, it is crucial to develop a method that fully considers a modality-invariant embedding space to effectively integrate multimodal data. In this study, to reduce the modality gap, we propose a multimodal data adversarial representation framework (MDAR) to reduce the modal heterogeneity by translating source modalities into distributions for the target modality. Additionally, we apply reconstruction and classification losses to embedding space to further constrain it. Then, we design a multi-scale bilinear convolutional neural network (MS-B-CNN) for uni-modality to improve the feature expression ability. In addition, the embedding space generates predictions as stacked feature inputs to the extremely randomized trees classifier. With 10-fold cross-validation, our results show that the proposed adversarial representation learning improves prognostic performance. A comparative study of this method and other existing methods on the METABRIC (1980 patients) dataset showed that Matthews correlation coefficient (Mcc) was significantly enhanced by 7.4% in the prognosis prediction of breast cancer patients.

Abstract P3-08-04: Discovery of cancer genes and pathways operative in PI3K-activated mammary cancer reveals clinically relevant genotype-phenotype correlations

Abstract Human breast cancer (BRCA) shows tremendous genomic, gene expression, clinical, and phenotypic heterogeneity. Known driver gene alterations can only explain a portion of this heterogeneity, some of which likely arise from variation in the target cell for transformation, in addition to incompletely understood gene copy number and epigenetic alterations. These factors are difficult to identify with certainty using human patient samples due to widely varying germline genetic backgrounds, thousands of gene copy and epigenetic changes per sample, and, unknown target cell transformation. Activating mutations in the p110α catalytic subunit of PI3K are one of the most common genetic alterations in human BRCA. Here, we report results from two Sleeping Beauty (SB) transposon-accelerated mouse models of Pik3ca-mutant mammary cancer showing how genotype-phenotype correlations can be drawn providing strong candidates for mediating tumor phenotypes, including estrogen-receptor (ER)-dependent gene expression, high cell cycle activity, and immune cell exclusion. We used SB transposon mutagenesis in mice on a Pik3caH1047R activated mutant background to model mammary cancer development in two different mammary epithelial compartments. Both the target cell for mutagenesis and the specific transposon-induced mutations correlated with specific tumor phenotypes, including whether the tumors were ER positive or negative. RNA sequencing of tumors revealed novel genotype-phenotype correlations implicating specific transposon-altered gene drivers of high cell cycle activity, ER-dependent gene expression, and white blood cell exclusion from the tumor. Many transposon-implicated genes are altered at the gene copy number or epigenetic/methylation level in human BRCA, and several were functionally validated. These models provide a source of genetically heterogenous mouse mammary tumors with a uniform initiating mutation, Pik3caH1047R, useful for identifying cooperating pathways and drivers of specific tumor phenotypes. Citation Format: Morito Kurata, Emiily Pope, Jingmin Shu, Wenlin Yuan, Wendy Hudson, Mark Sokolowski, Setareh Bagherzadeh, Zora Modrusan, Eric Stawiski, Steffen Durinck, Sekar Seshigiri, Aaron Sarver, Nuri Temiz, David Largaespada. Discovery of cancer genes and pathways operative in PI3K-activated mammary cancer reveals clinically relevant genotype-phenotype correlations. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-08-04.

Multi-omics-based analysis of high grade serous ovarian cancer subtypes reveals distinct molecular processes linked to patient prognosis.

Despite advancements in treatment, high-grade serous ovarian cancer (HGSOC) is still characterized by poor patient outcomes. To understand the molecular heterogeneity of this disease, which underlies the challenge in selecting optimal treatments for HGSOC patients, we have integrated genomic, transcriptomic, and epigenetic information to identify seven new HGSOC subtypes using a multiscale clustering method. These subtypes not only have significantly distinct overall survival, but also exhibit unique patterns of gene expression, microRNA expression, DNA methylation, and copy number alterations. As determined by our analysis, patients with similar clinical outcomes have distinct profiles of activated or repressed cellular processes, including cell cycle, epithelial-to-mesenchymal transition, immune activation, interferon response, and cilium organization. Furthermore, we performed a multiscale gene co-expression network analysis to identify subtype-specific key regulators and predicted optimal targeted therapies based on subtype-specific gene expression. In summary, this study provides new insights into the cellular heterogeneity of the HGSOC genomic, epigenetic, and transcriptomic landscapes and provides a basis for future studies into precision medicine for HGSOC patients.

Characterization of ctDNA findings at the end of life in patients with prostate cancer.

230 Background: Somatic alterations change over time in response to treatment and disease progression in patients with prostate cancer (PCa). We report ctDNA findings of patients who died from PCa within 3 months of a ctDNA assessment to better characterize patients with fatal disease. Methods: A total of 118 patients with PCa specific mortality who had been treated at Tulane Cancer Center and had ctDNA assessments between 2015 and 2022. The ctDNA was assessed by Guardant360 (Guardent Health, Inc) assays to identify alterations, pathogenic mutations and/or copy number alterations (CNAs) in cancer-related genes. Clinical annotation including treatment history, genetics, and staging were also obtained. Statistical analyses included Fischer’s Exact and Wilcoxon tests. Results: Of the 118 patients with PCa specific mortality, 42% (49/118) had a ctDNA assessment &lt;3 months from death. Of 49 CRPC patients tested within 3 months of death, the median number of life extending therapies (LET) at death was 5 (2-9). Patients had a median of 2 (0-6) LET prior to first ctDNA screening and 3 (0-7) LET in between first and last ctDNA assessment. Of the total gene alterations detected on ctDNA analysis, within 3 months of death, the most common alterations detected were 65.3% (32/49) TP53, 44.9% (22/49) AR, 28.6% (14/49) EGFR, 24.5% (12/49) PIK3CA, 22.4% (11/49) MYC, and 20.4% (10/49) CDK6. In a paired analysis(n= 45) of first and last ctDNA screening, AR (OR= 2.35, 95% C.I. (0.99, 5.62), p= 0.05), CDK6 (OR= 4.00, 95% C.I. (1.02, 15.68), p= 0.04), FGFR1 (OR= 9.51, 95% C.I. (1.14, 79.61), p= 0.03), and EGFR (OR= 9.71, 95% C.I. (2.06, 45.83), p= 0.0009) were significantly more likely to be detected in ctDNA screening within 3 months of death. In addition, ctDNA alterations in general were significantly more likely to be detected at the end-of-life (p=&lt; 0.00001). Other ctDNA gene mutations did not have statistically significant increases. Conclusions: An analysis of patients with PCa mortality showed most frequent gene alterations in TP53, AR, EGFR, PIK3CA, MYC, and CDK6. When comparing patients’ first and last ctDNA, alterations were significantly more likely by time of death in AR, CDK6, EGFR, FGFR and there was a significant increase in overall detection of somatic alterations in ctDNA. These analyses are limited to the genes assessed on the ctDNA panel and may or may not reflect all of the functionally relevant alterations. Further the CNAs reported herein may reflect broad genomic changes rather than specific gene alterations.

Impact of gene alterations on clinical outcome in young adults with myelodysplastic syndromes

Young adults with myelodysplastic syndrome (MDS) are rare, and the clinical significance of driver mutations has not yet been analysed. We analysed the gene mutations and copy number alterations (CNAs) in younger MDS patients using next-generation sequencing, targeting 68 genes that were recurrently mutated in myeloid malignancies, to investigate the correlation between their genetic alterations and clinical outcomes. We enrolled 55 patients retrospectively (aged < 50 years). At least one mutation was detected in 56% of the patients. The most frequently mutated genes were ASXL1 and RUNX1, 13% each. We defined higher-risk patients as those with ≥ 2 mutations, except for SF3B1 mutation, and/or CNA. The 3-year overall survival (OS) in patients with a higher-risk was lower than that in those with a lower-risk (50.8% vs. 71.8%, P = 0.024). Among the 44 transplant recipients, patients with higher-risk had a significantly lower OS and tended to have a higher cumulative incidence of relapse (CIR) than those with a lower-risk (3-year OS: 38.0% vs. 64.4%, P = 0.039; 3-year CIR: 44.0% vs. 24.1%, P = 0.076). Our results showed that genetic aberrations can predict clinical outcomes in younger MDS patients, despite the low rate of genetic mutations.

Genomic alterations in neuroendocrine prostate cancer: A systematic review and meta-analysis.

Neuroendocrine prostate cancer (NEPC) is a lethal subtype of prostate cancer. We performed a systematic review and meta-analysis to evaluate the prevalence of genomic alterations in NEPC and better understand its molecular features to potentially inform precision medicine. EMBASE, PubMed, and Cochrane Central Register of Controlled Trials databases were searched for eligible studies until March 2022. Study qualities were assessed using the Q-genie tool. The prevalence of gene mutations and copy number alterations (CNAs) were extracted, and meta-analysis was performed using R Studio with meta package. A total of 14 studies with 449 NEPC patients were included in this meta-analysis. The most frequently mutated gene in NEPC was TP53 (49.8%), and the prevalence of deleterious mutations in ATM/BRCA was 16.8%. Common CNAs in NEPC included RB1 loss (58.3%), TP53 loss (42.8%), PTEN loss (37.0%), AURKA amplification (28.2%), and MYCN amplification (22.9%). RB1/TP53 alterations and concurrent RB1 and TP53 alterations were remarkably common in NEPC, with a prevalence of 83.8% and 43.9%, respectively. Comparative analyses indicated that the prevalence of (concurrent) RB1/TP53 alterations was significantly higher in de novo NEPC than in treatment-emergent NEPC (t-NEPC). This study presents the comprehensive prevalence of common genomic alterations and potentially actionable targets in NEPC and reveals the genomic differences between de novo NEPC and t-NEPC. Our findings highlight the importance of genomic testing in patients for precision medicine and provide insights into future studies exploring different NEPC subtypes.

Copy Number Alterations in CDKN2A/2B and MTAP Genes Are Associated With Low MEF2C Expression in T-cell Acute Lymphoblastic Leukemia.

The molecular heterogeneity of T-cell acute lymphoblastic leukemia (T-ALL) makes this disease complex. Early T-cell precursor ALL (ETP-ALL) is a recognized subtype of T-ALL associated with a high probability of induction failure with conventional therapy. Higher expression of myocyte enhancer factor 2C (MEF2C) and the absence of a biallelic deletion (ABD) are the designated markers for the ETP-ALL. Co-deletion of the contiguous genes cyclin-dependent kinase inhibitor 2A/2B (CDKN2A/2B) and the methylthioadenosine phosphorylase (MTAP) cluster, located at 9p21.3, is another common alteration in T-ALL and confers poor response to treatment. We used real-time polymerase chain reaction (PCR) analysis to assess MEF2C mRNA expression and ABD status. Copy number alterations (CNAs) in key genes previously reported to be altered in T-ALL were assessed using multiple ligation probe amplification (MLPA). We observed that CNAs in this co-deletion cluster of CDKN2A/B and MTAP genes exhibited low MEF2C expression while ABD was associated with CNA in the Abelson murine leukemia 1 (ABL1) gene. Assessment of MEF2C expression based on immunophenotype revealed that its association with CDKN2A/2B alteration is present in non-immature immunophenotype. Additionally, ABD was associated with copy number alterations of T-cell acute lymphocytic leukemia protein 1 (TAL1), myeloblastosis (MYB), and LIM domain only 2 (LMO2) genes in immature immunophenotypes. Further, STIL::TAL1fusion was associated with low expression ofMEF2C. These associations may help explain the difficulties in assessing disease heterogeneity and the prognostic importance of 9p21.3 alterations in T-ALL.

Ecological stoichiometry drives the evolution of soil nematode life history traits

Ecological stoichiometry is a useful theoretical framework for understanding the sources and controls on nutrient availability that structure the composition and diversity of biotic communities. One such relationship is that organismal development rate is positively linked to cellular Phosphorus (P). We hypothesized that P availability, relative to other nutrients, e.g., nitrogen and carbon, would drive the evolution of traits associated with organismal growth and development. We examined the effects of P availability both in situ and in vitro, on free-living soil nematodes. We found that P-deficient environments produce predictable changes in the ecology and evolution of important life history traits. Our results identify altered rRNA gene copy number and subsequent changes in gene expression and protein synthesis as mechanisms by which P-deficiency influences these traits. These findings have important implications for explaining soil ecological and evolutionary patterns across multiple levels of organization, including the structure and functioning of organisms, populations, communities, and ecosystems.

FGFR2-amplified tumor clones are markedly heterogeneously distributed in carcinomas of the upper gastrointestinal tract

BackgroundFGFR2 is a therapy-relevant target in tumors of the upper gastrointestinal tract (GIT), and clinical trials are currently underway to test the efficacy of FGFR2 inhibitors. Tumor heterogeneity is one of the relevant causes of treatment failure. Almost nothing is known about the heterogeneous distribution of FGFR2-amplified clones in adenocarcinomas of the upper GIT.Patients and methodsTo assess FGFR2 gene copy number alteration and intratumoral heterogeneity of upper GIT adenocarcinomas, we analyzed 893 patient-derived formalin-fixed paraffin-embedded tumor specimens, including primary operated and neoadjuvant-treated tumors (462 gastric carcinomas and 429 esophageal adenocarcinomas) as well as complementary lymph node and distant metastasis by fluorescence in situ hybridization.ResultsTwenty-six gastric tumors (5.6%) and 21 esophageal adenocarcinomas (4.9%) showed FGFR2 amplification. Overall, 93% of gastric carcinomas and 83% of esophageal carcinomas showed heterogeneous amplification. FGFR2 amplification was found in different histological growth patterns, including intestinal and diffuse type according to the Lauren classification. In the primary gastric carcinoma group, FGFR2 amplification was associated with poor prognosis (p = 0.005).ConclusionHomogeneous FGFR2 amplification in tumors of the upper GIT is the exception. This has highly relevant implications in the nature of FGFR2 diagnostics (sufficient tumor cell number, determination of amplification at metastasis versus primary tumor, etc.) and on the response probability of appropriate inhibitors. It is relevant that the often poorly treatable and aggressive subtype of diffuse carcinomas (poorly cohesive carcinomas) also shows FGFR2 amplification and that an individualized therapy option with FGFR2 inhibitors could be an option in this group.

Plasma Copy Number Alteration-Based Prognostic and Predictive Multi-Gene Risk Score in Metastatic Castration-Resistant Prostate Cancer.

Simple SummaryAt a genomic level metastatic castrate resistant prostate cancer state is highly heterogeneous and no clear genome-based prognostic or predictive biomarkers exist in practice. We evaluated multiple copy number somatic alterations in two castrate resistant patient cohorts to determine if a genome-based risk score at the copy number level can predict clinical outcomes. The first cohort included patients in a prospective clinical-trial in which abiraterone acetate was given and the other comprised of a real-world hospital-registry. We extracted plasma cell free DNA in both cohorts and performed low pass whole genome sequencing. Copy number alterations were identified for 24 candidate genes and a final composite score developed from 11 genes. This risk score was able to predict survival in castrate resistant patients after adjusting for known clinical biomarkers. Additionally, the multi-gene copy number alteration based risk score algorithm also predicted if abiraterone acetate would be effective in castrate resistant patients.: BackgroundA plasma cell-free DNA (cfDNA) multi-gene copy number alteration (CNA)-based risk score was evaluated to predict clinical outcomes in metastatic castrate resistant prostate cancer (mCRPC) patients. Methods: Plasma specimens from two independent mCRPC patient cohorts (N = 88 and N = 92 patients) were used. A treatment-naïve mCRPC cohort (prospective clinical-trial cohort) included plasma samples before treatment with abiraterone acetate/prednisone and serially at 3-months. A separate real-world hospital-registry (RWHR) mCRPC cohort included a single blood sample collected prior to mCRPC treatments in 92 mCRPC patients following ADT failure. Low pass whole genome sequencing was performed on plasma cell-free DNA (cfDNA) and copy number alterations (CNAs) were identified for 24 candidate genes of interest. Associations of individual gene CNAs with 3 month primary resistance to therapy, progression-free survival (PFS) in the prospective trial cohort and overall survival (OS) in both cohorts was evaluated by Cox regression. A multi-gene risk score was determined for significantly associated candidate CNAs for predicting clinical outcomes. Clinical factors were included in the risk model for survival. Statistical significance for all tests was set at 0.05. Results: In the prospective trial cohort, patients responding to treatment were observed to have a significant copy number decrease in AR (p = 0.001) and COL22A1 (p = 0.037) at 3 months, while the non-responder group showed a significant CNA decrease in NKX3.1 (p = 0.027), ZBTB16 (p = 0.025) and CNA increases in PIK3CB (p = 0.006). Based on the significance level of each gene, CNAs in 11 of the 24 genes (AR, COL22A1, MYC, NCOR1, NKX3.1, NOTCH1, PIK3CA, PIK3CB, TMPRSS2, TP53, ZBTB16) were selected to develop a Cox-regression coefficient-based weighted multi-gene risk score for predicting mCRPC outcomes in both cohorts. A higher multi-gene risk score was observed to have poor OS in mCRPC patients in the prospective trial cohort (p = 0.00019) and for the RWHR cohort, (p < 0.0001). A higher risk score was also associated with poor PFS in the prospective cohort (p = 0.0043). Conclusions: A multi-gene CNAs-based risk score derived from plasma cfDNA may predict treatment response and prognosticate survival in mCRPC and warrants prospective validation of risk-based algorithms.

A comprehensive genomic and transcriptomic dataset of triple-negative breast cancers

Molecular subtyping of triple-negative breast cancer (TNBC) is essential for understanding the mechanisms and discovering actionable targets of this highly heterogeneous type of breast cancer. We previously performed a large single-center and multiomics study consisting of genomics, transcriptomics, and clinical information from 465 patients with primary TNBC. To facilitate reusing this unique dataset, we provided a detailed description of the dataset with special attention to data quality in this study. The multiomics data were generally of high quality, but a few sequencing data had quality issues and should be noted in subsequent data reuse. Furthermore, we reconduct data analyses with updated pipelines and the updated version of the human reference genome from hg19 to hg38. The updated profiles were in good concordance with those previously published in terms of gene quantification, variant calling, and copy number alteration. Additionally, we developed a user-friendly web-based database for convenient access and interactive exploration of the dataset. Our work will facilitate reusing the dataset, maximize the values of data and further accelerate cancer research.