Somatic Mutation Patterns Research Articles

Molecular Spectra and Frequency Patterns of Somatic Mutations in Arab Women with Breast Cancer.

The role of somatic mutations in breast cancer prognosis and management continues to be recognized. However, data on the molecular profiles of Arab women are limited. This was a cross-sectional study based on medical chart review of all Arab women diagnosed with breast cancer at a single institution between 2010 and 2018 who underwent next-generation sequencing with Ampliseq 46-Gene or 50-Gene. A total of 78 Arab women were identified, with a median age at diagnosis of 52.3 years (range: 37-82 years; 38.5% ≤50 years). The majority of patients had stage III or IV disease (74.4%). Next-generation sequencing revealed the following somatic mutation rates: TP53, 23.1%; ATM, 2.6%; IDH1, 2.6%; IDH2, 3.8%; PTEN, 7.7%; PIK3CA, 15.4%; APC, 7.7%; NPM1, 2.5%; MPL, 1.3%; JAK2, 2.5%; KIT, 7.7%; KRAS, 3.8%; and NRAS, 3.8%. Our study illustrates frequencies of somatic mutations in Arab women with breast cancer and suggests potential variations from estimates reported in the Western population. These data calls for larger epidemiologic studies considering the evolving role of such mutations in prognostication and personalized management.

Significance and limitations of the use of next-generation sequencing technologies for detecting mutational signatures

Next generation sequencing technologies (NGS) have been critical in characterizing the genomic landscape and untangling the genetic heterogeneity of human cancer. Since its advent, NGS has played a pivotal role in identifying the patterns of somatic mutations imprinted on cancer genomes and in deciphering the signatures of the mutational processes that have generated these patterns. Mutational signatures serve as phenotypic molecular footprints of exposures to environmental factors as well as deficiency and infidelity of DNA replication and repair pathways. Since the first roadmap of mutational signatures in human cancer was generated from whole-genome and whole-exome sequencing data, there has been a growing interest to extract mutational signatures from other NGS technologies such as targeted panel sequencing, RNA sequencing, single-cell sequencing, duplex sequencing, reduced representation sequencing, and long-read sequencing. Many of these technologies have their inherent sequencing biases and produce technical artifacts that can confound the extraction of reliable and interpretable mutational signatures. In this review, we highlight the relevance, limitations, and prospects of using different NGS technologies for examining mutational patterns and for deciphering mutational signatures.

Interaction with the CCT chaperonin complex limits APOBEC3A cytidine deaminase cytotoxicity.

The APOBEC3 cytidine deaminases are implicated as the cause of a prevalent somatic mutation pattern found in cancer genomes. The APOBEC3 enzymes act as viral restriction factors by mutating viral genomes. Mutation of the cellular genome is presumed to be an off-target activity of the enzymes, although the regulatory measures for APOBEC3 expression and activity remain undefined. It is therefore difficult to predict circumstances that enable APOBEC3 interaction with cellular DNA that leads to mutagenesis. The APOBEC3A (A3A) enzyme is the most potent deaminase of the family. Using proteomics, we evaluate protein interactors of A3A to identify potential regulators. We find that A3A interacts with the chaperonin-containing TCP-1 (CCT) complex, a cellular machine that assists in protein folding and function. Importantly, depletion of CCT results in A3A-induced DNA damage and cytotoxicity. Evaluation of cancer genomes demonstrates an enrichment of A3A mutational signatures in cancers with silencing mutations in CCT subunit genes. Together, these data suggest that the CCT complex interacts with A3A, and that disruption of CCT function results in increased A3A mutational activity.

Somatic mutations of DNA damage repair (DDR) genes in patients with epithelial ovarian cancer

Objectives: Gene mutations are proved to be associated in epithelial ovarian cancer. The majority of researches focus on BRCA1/2 in ovarian serous carcinoma. The incidence of ovarian clear cell carcinoma and endometrioid carcinoma are estimated to be 15% respectively in East Asia, especially in Japan and Taiwan, which is far more prevalent than in the Western countries. However, the somatic gene mutations of DNA damage repair genes in ovarian clear cell carcinoma and endometrioid carcinoma is unclear. Methods: We investigated the somatic mutations of epithelial ovarian cancer patients using a panel containing DNA damage repair genes by next generation sequencing method. Totally 172 epithelial ovarian carcinoma patients, including 69 serous carcinoma, 39 endometrioid carcinoma and 64 clear cell carcinoma, were enrolled. Results: Totally 78 patients with DDR somatic gene mutations were noted, including 48 (69.6%) in serous carcinoma, 13 (33.3%) in endometrioid carcinoma and 17 (26.6%) in clear cell carcinoma. In 69 serous carcinoma patients, gene mutations were 39 TP53 (56.5%), 4 BRCA2 (5.8%), 4 RAD51C (5.8%), 3 MUTYH (4.3%), 3 ERCC8 (4.3%), 1 BRCA1 (1.4%), 1 BRIP1 (1.4%), 1 FANCG (1.4%), 1 RAD51D (1.4%), 1 MLH3 (1.4%), 1 MSH6 (1.4%), 1 OGG1 (1.4%), 1 XRCC6 (1.4%) and 1 ATM (1.4%). In 39 endometrioid carcinoma, gene mutations were 6 TP53 (15.4%), 5 ATM (12.8%), 3 MSH2 (7.7%), 2 MUTYH (5.1%), 2 MLH3 (5.1%), 2 RAD50 (5.1%), 1 BRCA2 (2.6%), 1 MSH6 (2.6%), 1 FANCC (2.6%), 1 FANCM (2.6%), 1 MRE11 (2.6%), 1 MLH1 (2.6%) and 1 MSH3 (2.6%). In 64 clear cell carcinoma, gene mutations were 6 MUTYH (9.4%), 3 TP53 (4.7%), 2 BRCA2 (3.1%), 2 ERCC8 (3.1%), 1 BRCA1 (1.6%), 1 FANCI (1.6%), 1 RAD50 (1.6%), 1 MLH1 (1.6%), 1 MLH3 (1.6%), 1 MSH6 (1.6%), 1 XRCC4 (1.6%), 1 POLD1 (1.6%), 1 CHEK2 (1.6%) and 1 BARD1 (1.6%). In homologous recombination repair genes, the percentage of somatic mutations was 15.9%, 7.7% and 6.3% for serous, endometrioid and clear cell carcinoma (p=0.154, chi-square test). In mismatch repair genes, the percentage of somatic mutations was 2.9%, 15.4% and 4.7% for serous, endometrioid and clear cell carcinoma respectively (p=0.003, chi-square test). In double strand break repair genes, the percentage of somatic mutations was 17.4%, 7.7% and 6.3% for serous, endometrioid and clear cell carcinoma (p=0.092, chi-square test). In single strand break repair genes, the percentage of somatic mutations was 13.0%, 20.5% and 15.6% for serous, endometrioid and clear cell carcinoma (p=0.591, chi-square test). In cell cycle regulation genes, the percentage of somatic mutations was 58.0%, 23.1% and 6.3% for serous, endometrioid and clear cell carcinoma (p Conclusions: The pattern of somatic gene mutations of DNA damage repair genes differs in the serous, endometrioid and clear cell carcinoma patients. Our findings could provide the basis of precision medicine strategy for ovarian cancer treatment.

Hepatic IFNL4 Gene Activation in Hepatocellular Carcinoma Patients with Regard to Etiology.

Hepatocellular carcinoma (HCC) is a malignancy with a leading lethality. The etiology is quite diverse, ranging from viral infections to metabolic disorders or intoxications, and associates with specific somatic mutational patterns and specific host immunological phenotypes. Particularly, hepatitis C virus (HCV)-infected liver is featured by an activation of interferon (IFN)-stimulated genes (ISGs; IFN signature), which we suppose is driven by type III IFNL4. Taking advantage of the TCGA collection of HCC patients of various different etiologies, this study aimed at validating our previous findings on hepatic IFNL4 gene activation in HCV infection in an independent and larger cohort of patients with advanced liver disease. In a cohort of n = 377 cases, the entirety of the sequencing data was used to assess the IFNL genotypes, and the cases were stratified for etiology. The number of IFNL4 transcripts within nonmalignant and malignant tissues was found to be more abundant in patients with HCV or HCV/HBV infections when compared to other risk factors. Moreover, in patients with HCV infection as a risk factor, a close, positive relationship was found between ISG activation and the number of functional IFNL4 transcripts. Data on this independent TCGA sample support the concept of an IFNL4-dependent HCV-driven activation of hepatic ISGs. In addition to that, they add to the understanding of etiology-related host immunological phenotypes in HCC.

Classification of High-Grade Serous Ovarian Carcinoma by Epithelial-to-Mesenchymal Transition Signature and Homologous Recombination Repair Genes.

High-grade serous ovarian cancer (HGSOC) is one of the deadliest cancers that can occur in women. This study aimed to investigate the molecular characteristics of HGSOC through integrative analysis of multi-omics data. We used fresh-frozen, chemotherapy-naïve primary ovarian cancer tissues and matched blood samples of HGSOC patients and conducted next-generation whole-exome sequencing (WES) and RNA sequencing (RNA-seq). Genomic and transcriptomic profiles were comprehensively compared between patients with germline BRCA1/2 mutations and others with wild-type BRCA1/2. HGSOC samples initially divided into two groups by the presence of germline BRCA1/2 mutations showed mutually exclusive somatic mutation patterns, yet the implementation of high-dimensional analysis of RNA-seq and application of epithelial-to-mesenchymal (EMT) index onto the HGSOC samples revealed that they can be divided into two subtypes; homologous recombination repair (HRR)-activated type and mesenchymal type. Patients with mesenchymal HGSOC, characterized by the activation of the EMT transcriptional program, low genomic alteration and diverse cell-type compositions, exhibited significantly worse overall survival than did those with HRR-activated HGSOC (p = 0.002). In validation with The Cancer Genome Atlas (TCGA) HGSOC data, patients with a high EMT index (≥the median) showed significantly worse overall survival than did those with a low EMT index (<the median) (p = 0.030). In conclusion, through a comprehensive multi-omics approach towards our HGSOC cohorts, two distinctive types of HGSOC (HRR-activated and mesenchymal) were identified. Our novel EMT index seems to be a potential prognostic biomarker for HGSOC.

Progression to AML Is Predictable and Distinct from Age Related Clonal Hematopoiesis

Introduction: Despite marked improvements in our understanding of the biology and genetic basis of acute myeloid leukemia (AML) gained in the past 4 decades, the overall survival of AML has only improved slightly. The strategy for targeting AML once the disease is diagnosed remains grim due to subclonal genetic diversity and the stemness properties of relapse originating cell types. As studies in solid tumors have shown, strategies focused on targeting the cancer at earlier stages hold considerable promise, however no predictive tests are available for AML. The existence of clonally expanded pre-leukemic hematopoietic stem and progenitor cells (preL-HSPC) within the diagnostic blood sample of AML patients provides strong evidence that the disease must evolve over long time periods prior to diagnosis. However, with the discovery that age related clonal hematopoiesis (ARCH) is exceedingly common during normal aging; a refined search for the factors that distinguish ARCH from those rare individuals who will actually develop AML had to be taken.Methods: We hypothesized that the basis for clonal expansion in ARCH was different than in the clonal expansion leading to AML. To investigate genetic differences, we developed sensitive and accurate error correction sequencing method to study blood samples of healthy individuals from the EPIC cohort before AML diagnosis. These 96 pre-AML cases donated their blood on average 6 years before eventually being diagnosed with AML; a set of 420 matched controls were sequenced in the same way. Furthermore, 3.2 million electronic health records (EHR) from the Clalit database were inspected to identify non-genetic AML-risk prediction parameters.Results: The overall variant allele frequency (VAF) distribution of the identified mutations was significantly different between cases and controls. Specifically, a greater proportion of cases carried somatic mutations with intermediate-high VAF (70.8% versus 36.6% in the controls). The median number of all somatic mutations was significantly higher in the cases as compared with the controls (7 and 5 respectively) and was correlated with aging in both groups. Interestingly, the pre-AML group had a higher rate of mutation accumulation compared to controls, resulting in significantly greater numbers of mutations occurring after the age of 55. Recurrent AML mutations were more prevalent in cases compared to controls (Age>=55: OR, 7.571; 95% CI, 4.055-14.387). Specifically, highly recurrent splicing factors mutations (e.g. SRSF2 P95H, U2AF1 Q84P, and SF3B1 K700E) were found solely in the pre-AML group suggesting that specific mutations that rewire the splicing machinery inevitably leads to AML when acquired in HSPC. The VAF of recurrent AML mutations was significantly higher in the cases compared to controls. Furthermore we observed a higher proportion of individuals with more than one recurrent AML mutation in the pre-AML group compared to controls (OR, 14.316; 95% CI, 6.318-34.933). Incorporating these factors, we construct a computational model for predicting progression toward AML. The AML risk prediction model predicted progression on average 7 years before actual diagnosis (HR, 20.1, 95% CI 8.59-46.8). EHR data was found to be highly valuable for the identification of high-risk population. Compared to controls, AML patients (N=982) showed aberrant blood counts up to 6 months prior diagnosis (relative risk, 22.2).Conclusions: These results reveal that the clonal expansion occurring during normal aging is highly distinct from pre-AML clonal expansion, which has a highly predictable evolutionary trajectory. Our study provides clear proof of concept for the feasibility of early AML prediction based on somatic mutation patterns, yet, since ARCH is common, the real-world feasibility of applying our AML risk prediction model will require identifying higher-risk individuals through routine clinical testing. We have shown that information obtained from EHR is useful for that purpose. Future studies of independent population cohorts with access to serial viable blood and leukemia samples will allow for incorporation of information such as the specific identity of the mutated cells and clone expansion kinetics. Such studies will aid in developing better understanding of which individuals should be selected for future clinical trials to study the potential benefits of early interventions in this deadly disease. DisclosuresNo relevant conflicts of interest to declare.

Chemotherapy and Radiation Results in Distinct Patterns of Somatic Mutations in Subsequent Myeloid Disease

Approximately 10% of myeloid neoplasia (MN) may be attributed to extrinsic factors. While environmental exposures are difficult to assess in their impact, iatrogenic causes of MDS, such as previous treatment (tx) with chemotherapy (ctx) or radiation (rtx), are easier to obtain from a patient's history. However, the distinction of a therapy-related MN (tMN) from germline-mediated and spontaneous second MN, e.g ., due to aging, may be problematic. Distinct etiologies may imply specific molecular defects; for instance, tMN types include topoisomerase II inhibitor-induced translocations of 11q23 and 21q22. We hypothesize that tMN is driven by a specific subset of somatic hits.Among 1058 patients (pts) seen at Cleveland Clinic between July 2002 and July 2017 (68% MDS, 24% AML, 8% MDS/MPN); 266 had tMN, with clearly-defined tx history with ctx, rtx, or a combination of ctx and rtx (both) for their primary malignancy (PM) and 109 pts had a history of PM without tx using ctx or rtx (second MN or sMN). Median age at diagnosis (dx) was 64 (9-88), 68 (20-92) and 74 (47-95) years (y) in pMN, tMN and sMN, respectively (p<.0001). Average latency for tMN vs. sMN was 8.6y vs . 10y (p=0.5). Higher-risk MDS/AML was found in 13%, 26% and 22% of pMN, sMN, and tMN, respectively.For tMN and sMN, prostate (20%, 32%), breast (30.5%, 16%), and colorectal cancers (7%, 16%) were the most common PM. Hematologic neoplasia as PM was more common in tMN than sMN (25% vs . 3.7%, p<.0001). Family history of malignancy was enriched in pts with pMN vs. sMN and tMN (OR 1.7, p=0.001, OR 1.6, p=0.057). Del7/7q was most common in tMN vs. pMN (OR 2.8, p<.0001) and sMN (OR 3.6, p=0.0004). Complex karyotype was enriched in tMN vs. sMN and pMN (30%, 13% 16%, p<.0001). NGS for somatic mutations (60-gene panel) was available for 145 tMN, 65 sMN, and the remaining 683 pts with no history of PM prior to MN dx (primary MN or pMN). To determine differences in patterns of somatic driver lesions in each group, we compared frequency of all mutations (MUT) as well as ancestral hits, as assessed by recapitulation of clonal hierarchy using variant allele frequency and zygosity.General somatic patterns of acquisition were similar in frequency and ancestral hits in tMN, pMN and sMN and featured TET2, DNMT3A, and SRSF2MUTS. However, there were significant differences. TP53 (13.1%), EZH2 (7.6%), WT1 (2.8%), and KITMUTS (3.5%) were overrepresented in tMN vs. pMN (OR 2.6, p=0.002 ; OR 1.9, p=0.083 ; OR 3.2; p=0.08 ; OR 6.1, p=0.01) and sMN (OR 2.3, p=0.15; OR 1.3, p= 0.78 ; OR 1.8, p=1 ; OR Infinity, p=0.186). TP53 and EZH2MUTS were also more common ancestral hits in tMN (11%, 4.8%) vs. pMN (3.5%, 2%) (p=0.0004, p=0 .07). TP53MUTpersisted in being associated with tx as an ancestral hit when sMN (3.1%) was used as a control (p=0.06) . In tMN, IDH1, SRSF2, CUX1, and PHF6MUTS (0.7%, 10.3%, 3.5%, 4.1%) were underrepresented relative to sMN (7.7%, 20%, 7.7%, 9.2%) (p=0.011, p=0.077, p=0.29, p=0.19). Indeed, these were more frequent in sMN than pMN (OR 3.07, p=0.042 ; OR 1.99, p=0.044 ; OR 3, p=0.042 ; OR 4.85, p=0.005) and were ancestral events in 4.6%, 12.3%, 1.5%, 1.5% sMN cases.Specific tx modalities have been associated with molecular lesions. We analyzed whether or not rtx and ctx had the same impact on the profile of somatic lesions. TP53MUT correlated primarily with ctx vs rtx (OR 7.2 , p=0.06). However, it was highest when both were used vs. rtx (OR 11.5, p=0.01). Notably, TP53MUT tMN cases were associated with complex karyotype relative to TP53WT tMN cases (OR 20, p<0.0001). ETV6 and EZH2MUTS were found only in pts with rtx or both, never ctx alone (p=0.05, p=0.004, respectively). In addition to increasing mutational frequency, rtx also increased the propensity for EZH2MUT to become the ancestral hit relative to pMN (OR 2.4, p=0.07) and sMN (OR 1.5, p=0.7), albeit less significantly. EZH2MUT had no influence on complex cytogenetics.In conclusion, our study demonstrates that tMN are molecularly diverse with increased frequency of specific hits including TP53, EZH2, WT1, and KITMUT. The tMN entity may be contaminated by cases with sMN with a hereditary component or spontaneous sMN, in whom molecular patterns may be distinct. However, we were unable to establish an entirely distinct molecular signature related to cytotoxic therapy. DisclosuresAdvani:Pfizer: Consultancy; Takeda/ Millenium: Research Funding. Gerds:Incyte: Consultancy; CTI BioPharma: Consultancy. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees.

Somatic PRPF8 Mutations in Myeloid Neoplasia

Somaticmutations in genes of the RNA-splicing machinery are recurrent in myeloid neoplasia. PRPF8 has a central role in the spliceosome assembly and it is required in all tissues. Somatic mutations in PRPF8 have been described in patients with MDS. We previously showed that PRPF8 mutations (PRPF8MT) are associated with presence of ring sideroblasts (RS) and a distinct myeloid phenotype. However, to date, no comprehensive analysis has been conducted to unravel the clonal architecture of PRPF8MTpatients.We took advantage of a large database of patients with bone marrow failure syndromes (BMFS) annotated for molecular and clinical characteristics (n=1700; median follow up 1.0 year, range 1-5 years), median age was 71 years (range, 13-93). Whole exome sequencing and targeted deep sequencing of a panel of 65 genes was applied. Our analyses included somatic mutational patterns, clonal hierarchy, and cross-sectional correlation in the cohort of PRPF8MT and PRPF8 wild type.PRPF8 mutations were found in 4% (65/1700) of patients. The mutations were mainly missense but nonsense, frameshift, and splice mutations were also seen. No specific hotspot was identified, although we noted that mutations at D1958 were detected in 7 patients, F1099 in 4 patients and C1594 and V1015 mutations were detected in 3 patients each. 6 mutations (-17/17p-) were consistent with hemizygous configuration of PRPF8MT.A total of 368 mutations in the 65 gene panel were detected. Median number of mutations/ patient was 3 (range 1-26). PRPF8MT cases had a median overall survival (OS) of 26 months (mo) (range 8-110). 48/65 samples were tested for the presence of RS, showing 31% of samples with RS (RS+) and 69% of samples without RS (RS-). PRPF8MT/RS+ were mainly MDS (47%) and MDS/MPN (27%) while PRPF8MT/RS- were distributed in MDS (27%), BMFS (AA, PRCA, PNH; 27%), and AML (24%). We found that PRPF8MT/RS+ had a higher neutrophil counts vs. PRPF8MT/RS- (3.2±2.2 vs. 1.7±0.02) as well as platelets counts (158±197 vs. 91±150; P=.06) and a mild decreased number of lymphocytes (1.0±0.6 vs. 1.8±2.3, P=.03) perhaps due to a higher proportion of patients with BMFS. PRPF8MT were mostly normal karyotype (45%) with a low percentage of complex karyotypes (16%)We dissected the clonal hierarchy of PRPF8MT and found that 38% (25/65) were ancestral while 62% (40/65) were secondary hits. The most commonly ancestral mutations besides PRPF8 were TET2 (n=3) and SF3B1 (n=3). The most common secondary mutations after PRPF8 were TET2 (n=14) and ASXL1 (n=14). In MDS and AML, PRPF8MT were either ancestral or secondary, while in MDS/MPN and BMFS, PRPF8MT was mostly a secondary mutation (71% and 75%, P=.05 and P=.04).We further analyzed the mutational spectrum of PRPF8MT patients. Cross-sectional analysis identified that the top mutated genes in PRPF8MT clustered in epigenetic regulation and histone modification (19%; TET2, DNMT3A, IDH1/2, EZH2, ASXL1, KDM6A), followed by transcriptional regulation (13%; RUNX1, BCOR/L1, PHF6, ETV6, TP53), RNA-splicing (12%; SRSF2, SF3B1, LUC7L2, U2AF1, ZRSR2, DDX41, DHX29), and DNA-repair (7%; CUX1). Unlike other splicing mutations PRPF8 coexisted with other splicing lesions: SF3B1 (12%), SRSF2 (6%), LUC7L2 (9%), U2AF1 (8%), and ZRSR2 (6%). Of note, we found rare cases with triple splicing factor mutations (n=6). When we assessed the impact of the clonal architecture, ancestral PRPF8MT had a shorter OS than those with secondary mutations (35mo vs. 59mo; P=.04).In sum,clonal architecture analyses showed that PRPF8MT are frequently secondary rather than ancestral mutations but when are ancestral hits, they lead to dismal prognosis. Unlike the more common spliceosomal factor mutations (SF3B1, U2AF1, SRSF2) that rarely co-occur, PRPF8MT often co-occur with other spliceosomal mutations. This may be due to the fact that PRPF8MT are mostly secondary mutations. DisclosuresSekeres:Celgene: Membership on an entity's Board of Directors or advisory committees.

Mutational Signatures Associated with Intensity and Duration of Smoking in Myelodysplastic Syndromes (MDS)

Background:MDS pathogenesis is a multi-step molecular process resulting from somatic mutations acquired over time. Smoking is a known risk factor for MDS which may accelerate this process. To further investigate the contribution of tobacco use in MDS development, we studied the association between smoking and specific genomic alterations in MDS patients (pts).Methods: MDS and CMML pts diagnosed between 1996 and 2016 with both smoking histories and sequencing data were included. The Center for Disease Control definition defined current, ex- and never smokers, the latter defined as pts with zero smoking duration/packs per day (PPD). Next generation targeted sequencing was performed for a panel of 60 genes known to be commonly mutated in myeloid malignancies. Fisher's exact test and Wilcoxon's test compared proportions and medians, respectively. Poisson regression modeled total numbers of mutations per pt. The probability of a mutation in a particular gene was modeled using conditional logistic regression. Adjustment was done for both sex and age, fits were stratified using age cut points of 0, 40, 50, 60, 65, 70, 75, 80, 85 and 90 years (y). Odds ratios (OR) were found as exponentials of gene status coefficients of such fits.Results: In 672 pts, the median age at diagnosis was 68y (range, 20-103), for pt characteristics, see Table 1. Median OS 34 mo (95% CI 30-39) and median follow-up time was 21.5 mo (IQR, 10-45). Median tobacco exposures were 30 pack-years (py) in current smokers (range, 6-80) and 25 in ex-smokers (range, 0.3-175), P=.2. More men than women ever smoked (74% v 45%; P <.0001). Longer duration of smoking associated with higher IPSS-R categories (P=.012) and cytogenetic risk scores, P=.037. Most pts (502, 75%) had at least one mutation; 23% had a single gene mutation, 19% had 2, 15% had 3, and 18% had >3. The most frequently mutated genes were TET2 17%, ASXL1 16%, SRSF2 14%, SF3B1 12%, DNMT3A 10%, RUNX1 9%, STAG2 9%, and TP53 7%.Poisson regression analysis was used to assess the impact of smoking duration (y) or PPD on mutation acquisition. A positive correlation of greater smoking intensity (> 2 PPD v <0.5, relative increase (RI) =1.46, P=.011) and longer duration of smoking (>40y v <10, RI = 1.31, P=.011) was seen with increased number of mutations [Figure 1].Impact of duration of smoking was evaluated using logistic regression. Duration of smoking >40y v <1 was significantly associated with the following molecular abnormalities: FLT3 (P= .036), EZH2/ del7 (P=.038) and NRAS (P=.046). Comparing 20-40y v <1 yielded SETBP1 (P=.005), DNMT3A (P=.010) and EZH2 /del7 (P=.036). Comparing 10-20y v <1 yielded STAG2 (P=.039) and NOTCH1 (P=.046). Finally, comparing durations of 1-10y v <1 yielded PHF6 (P=.016). OR per mutation, see Table 2.Focusing on intensity of smoking, >2 PPD v <0.5 was significantly associated with higher rates of mutations in FLT3 (P=.013), EZH2 /del7 (P=.024), IDH1 (P=.041), and NPM1 (P=.044). Even low intensity smoking, comparing 0.5-1 PPD v <0.5, was significantly associated with mutations in SETBP1 (P=.002), DDX54 (P=.042) and DNMT3A (P=.046). For the combination of smoking duration and intensity, >40py v <10 was associated with IDH1 mutation (P=.046), while 20-30 py v <10 significantly associated with RAD21 (P=. 016), DDX54 (P=.018), SRSF2 (P=.041), del7/ EZH2 (P=.042), and NF1 (P=.045) mutations. Comparing 1-10py v <1, significant associations were found for IDH1 (P=.004), PRPF8 (P=.011), SETBP1 (P=.022), ETV6 (P= .040) and TET2 (P=. 047)mutations [Table 2]. Analyses were repeated after excluding CMML and MDS/MPN pts to control for the common genomic phenotype seen in these disorders, with identical results.Conclusions: Tobacco smoking predisposes to either acquisition or selection of distinct somatic mutational patterns from those seen in “spontaneous/non-tobacco exposed” MDS. EZH2/ del7 abnormalitiesassociated with longer durations and heavier smoking patterns, while SETBP1 mutation associated with lighter smoking for prolonged durations. Lesions associated with light smoking for years may be related to chronic inflammatory changes, whereas those associated with higher intensity may reflect direct DNA damage. Validation of these findings warrants earlier sequencing in pts with pre-MDS conditions such as clonal hematopoiesis of indeterminate potential to better identify the onset of somatic mutations and their role in MDS pathogenesis. [Display omitted] DisclosuresAdvani:Takeda/ Millenium: Research Funding; Pfizer: Consultancy. Gerds:CTI BioPharma: Consultancy; Incyte: Consultancy. Maciejewski:Alexion Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Speaker Fees; Apellis Pharmaceuticals: Consultancy; Ra Pharma: Consultancy. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees.

Whole Genome Sequencing in Hairy Cell Leukemia-Variant (HCL-v) and Splenic Marginal Zone Lymphoma (SMZL)

Background: The WHO 2016 classification defines a variety of lymphomas. Among the mature B-cell neoplasms different types of splenic lymphomas are separated from each other. In particular, hairy cell leukemia-variant (HCL-v) and splenic marginal zone lymphoma (SMZL) are defined as distinct entities, however, while they are readily separated from hairy cell leukemia based on cytomorphology, immunophenotype and lack of BRAF V600E mutation, HCL-v and SMZL feature partial overlaps of findings in cytomorphology and immunophenotype. Cytogenetic changes are rare and nonspecific. Thus, a comprehensive molecular work up may provide insight into shared and differentiating mutation.Aims: Molecular characterization of HCL-v and SMZL through whole genome sequencing (WGS) to provide a more distinct disease category.Patient cohort and methods: Diagnostic peripheral blood or bone marrow samples of 14 patients (7 HCL-v and 7 SMZL, median age 82, range 59-94; 8 female, 6 males) were selected for WGS with 90x coverage. Infiltration by mature B-lymphatic population ranged from 6%-72% (median 52%) by immunophenotyping. HCL-v cases were negative for BRAF . Library preparation was performed using Truseq DNA PCR-Free HT sample preparation kit (Illumina, San Diego, CA) according to manufacturer's protocol using fresh/frozen samples and sequenced on NovaSeq sequencing instruments. Tumor-only data was aligned by BaseSpace (BS) WGS app with default parameters and (structural) variant calling was performed with Tumor/Normal app using an unmatched reference DNA (Promega, Fitchburg, WI). Data was subsequently loaded into BS Variant Interpreter to filter and prioritize variants of interest. For the structural variants we looked at all high confidence variant calls passing filters with at least 5 paired reads and 3 split reads with a somatic QScore of >30. In addition, all calls were eliminated with a population frequency of >1% according to the DGV (Database of Genomic variants). For mutation analysis we filtered down the passed variant list to the coding regions of the CancerGeneCensus genes, with a variant read frequency of >0.2, ExAC population frequency of <1% and a damaging/deleterious mutation prediction score with PolyPhen-2 and SIFT. We performed mutation signature analysis by looking at the distribution of base substitutions across the sample with a 3mer context to decompose somatic mutation patterns and compared the results to the COSMIC signature database.Results: We observed a heterogeneous structural variation pattern with no obvious recurrent aberrations across both cohorts. The high diversity in molecular pattern was further confirmed on variant level. Mutation analysis yielded 164 mutations with a median of 12.5 (range 3-18) mutations per sample involving 122 of the 600 investigated genes. 19 genes were mutated in both entities, 44 were exclusive to HCL-v and 59 exclusive to SMZL. Recurrent mutations (n=3/14) were observed in the following genes: ASXL1, ATM, KMT2C, PCSK7, SMO, SPEN, TP53, TRIP11, WRN . PCSK7 is a transcriptional regulator and has been described to be associated with B-cell lymphoma. WRN is a helicase enzyme involved in DNA repair and associated with AML. Strikingly 3/7 (42%) of SMZL cases were mutated in these two genes. SPEN is known to block the differentiation of precursor B-cells into marginal zone B-cells. Additional exclusive recurrent mutations (n=2) were observed in ABL2, ARID1B, CREBBP for HCL-v, and BCL11A, NACA, NSD1, SF3B1 for SMZL. ABL2 is a tyrosine kinase and thus may provide a treatable target. Pathway analysis revealed that 30% of genes mutated (n=36) are involved in the MAPK/ERK pathway. We subsequently conducted a context-sensitive mutation signature analysis with the SNV data, using 96 substitution patterns rather than 6 to increase the complexity. In all instances we found a highly similar pattern across all 14 samples with a strong bias towards C>T substitutions.Conclusion: HCL-v and SMZL are highly diverse on the molecular level. Mutation signature analysis creates patterns associated with cancer and age. More data and further refinement of mutational entity specific signatures are needed to increase the granularity of these signatures. We identified several putative genes to be involved in HCL-v and SMZL, which were not associated with the two entities before. In two instances tyrosine kinase proteins were involved revealing a target for drugs. DisclosuresHaferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Comprehensive Analysis of Mixed Phenotype Acute Leukemia (MPAL) By Whole Genome Sequencing

Background: Mixed phenotype acute leukemias (MPAL) comprise a rare subgroup of acute leukemias with significant expression of lineage-specific antigens of more than one cell lineage not allowing assignment to a single cell lineage. While two MPAL subgroups are genetically defined according to the WHO 2016 classification, i.e. MPAL with BCR-ABL1 and MPAL with KMT2A rearrangement, the majority of cases are grouped as MPAL, B/myeloid, NOS or MPAL, T/myeloid, NOS and lack any specific or characteristic genetics so far.Aims: Molecular characterization of MPAL by whole genome sequencing (WGS).Patient cohort and methods: Diagnostic peripheral blood or bone marrow samples of 12 MPAL patients (median age 64 years, range 38-96; 5 male, 7 female) were selected for WGS with 90x coverage. One had MPAL with BCR-ABL1, 5 had MPAL, B/myeloid, NOS and 6 had MPAL, T/myeloid, NOS. Library preparation was performed using Truseq DNA PCR-Free HT sample preparation kit (Illumina, San Diego, CA). Sequencing was performed on NovaSeq instruments (Illumina). Tumor-only data was aligned by BaseSpace (BS) WGS app with default parameters and (structural) variant calling was performed with the Tumor/Normal app using an unmatched reference DNA (Promega, Fitchburg, WI). Data was subsequently loaded into BS Variant Interpreter to filter and prioritize variants of interest. For the structural variants we looked at all high confidence variant calls passing filters with at least 5 paired reads and 3 split reads with a somatic QScore of >30. In addition, all calls were eliminated with a population frequency of >1% according to the DGV (Database of Genomic variants). We performed mutation signature analysis by looking at the distribution of base substitutions across the sample with a 3mer context (including the base before and after the substitution) to decompose somatic mutation patterns and compared the results to the COSMIC signature database. For mutation analysis variants with a read frequency of >0.2% and ExAC population frequency of <1% were considered. For the first set of analysis we filtered down the variant list to the coding region of 65 genes described mutated in hematologic malignancies. For the second set of analysis we considered also genes beyond these 65 genes but required that variants had an entry in the COSMIC database and were classified with a “damaging” score by PolyPhen-2 and SIFT data bases.Results: Regarding the first set of analysis we found a median of 6 (range 2-7) mutations per patient, 63 overall, involving 35 of the 65 investigated genes. The majority were missense mutations (n=31), frameshift mutations (n=14) and splice-site mutations (n=13). The genes listed in table 1 were found most frequently mutated. Except for RUNX1 none of the frequently encountered mutations affected the case with MPAL with BCR-ABL1 while there was no restriction of mutations to either of the two other MPAL subgroups. 11 of these 63 mutations had been previously analyzed by routine diagnostics applying next generation sequencing (NGS) yielding identical results.Regarding the second set of analysis without limitation on the above mentioned 65 genes we found a median of 83 (range 63-129) mutations per patient, 1079 overall, involving 736 genes. Specifically, four candidate genes were found mutated in at least five patients (table 2). NBPF1 has been described as tumor suppressor, PRAMEF2 belongs to the PRAME family of genes associated with various malignancies and as a prognostic factor in B-ALL, MUC12 is a highly polymorphous gene involved in a variety of cancer types and described to be epigenetically regulated and thus a marker for early cancer detection, ARSD has been described overexpressed and prognostic in CLL. Again, mutations were not restricted to one MPAL subgroup.We subsequently conducted a context-sensitive mutation signature analysis with the SNV data, using 96 substitution patterns rather than only 6 to increase the complexity. In all instances we found a highly similar pattern across all 12 samples with a strong bias towards C>T substitutions (figure 1).Conclusion: WGS is capable of reproducing routine NGS diagnostics and of identifying mutations not yet described for MPAL which might be used to better understand and categorize this disease. [Display omitted] DisclosuresKern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Walter:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

The somatic mutation landscape of germline CHEK2-altered prostate cancer.

5084 Background: The intersection between germline and somatic genomics is an evolving field in which germline mutations may predispose to unique patterns of subsequent somatic mutations in cancer. Germline mutations in CHEK2, involved in cell cycle regulation and DNA damage response, are associated with an increased risk of prostate cancer (PCa), while somatic-only CHEK2 alterations in PCa are rare. The association of germline CHEK2 (g CHEK2)-altered PCa with somatic mutations is unknown, and may inform hypotheses about the etiology of these cancers. Methods: Germline DNA sequencing of 1,042 consecutive PCa patients (pts) from the public SignalDB database (www.signaldb.org) was analyzed for prevalence of pathogenic g CHEK2 mutations and was compared to individuals from the general population estimated by the ExAC database (containing 53,105 germline exomes). A separate cohort of 33 PCa pts from Johns Hopkins (JH) with known g CHEK2 mutations and available somatic tumor DNA sequencing (from primary prostatic tissue) was used to assess the association of g CHEK2 mutations with somatic mutations in genes that are recurrently altered in PCa ( TP53, RB1, PTEN, ATM, BRCA1/2, and CDK12); the prevalence of these somatic alterations was compared to those in 333 unselected PCa pts from the TCGA cohort. Somatic biallelic inactivation of CHEK2 was analyzed in a subset of pts. After uncovering a potential link between g CHEK2 and somatic CDK12 mutations, we studied a cohort of 69 pts with somatic CDK12 mutations where germline data were also available. Results: 28 of 1,042 (2.7%) PCa pts from SignalDB had a pathogenic g CHEK2 mutation, compared to a population prevalence (in ExAC) of 1.4% (750 of 53,105) (RR 1.9, 95%CI 1.3–2.8, P&lt; 0.001). Strikingly, only 23.8% of pts from SignalDB with g CHEK2 mutations had biallelic inactivation in the tumor . Furthermore, none of the 33 g CHEK2 pts from the JH cohort had evidence of somatic LOH. There were no differences in mutation prevalences involving TP53, RB1, PTEN, ATM, and BRCA1/2 between g CHEK2-altered and non-altered PCa pts. Unexpectedly, 5 of 33 (15%) g CHEK2-altered pts from the JH cohort had a somatic CDK12 mutation, compared to only 3 of 333 CDK12 mutations (1%) in unselected PCa pts from the TCGA cohort (RR 16.8, 95%CI 4.2–67, P&lt; 0.001). Conversely, 11 of 69 (16%) pts with a somatic CDK12 mutation harbored a pathogenic g CHEK2 mutation, compared to 28 of 1,042 (2.7%) unselected PCa pts from SignalDB (RR 5.9, 95%CI 3.1–11.4, P&lt; 0.001). Conclusions: Prostate cancers from g CHEK2-altered pts are infrequently characterized by biallelic CHEK2 inactivation and may be enriched for somatic CDK12 mutations, suggesting a unique mechanism of carcinogenesis that is different from g BRCA2-altered pts. Conversely, somatic CDK12-mutated cancers may be enriched for g CHEK2 mutations. The co-occurrence of CHEK2 and CDK12 mutations suggests a synergistic role in promoting cancer growth.

Abstract No. 21 A multi-institutional investigation of image-guided percutaneous ablation for intrahepatic cholangiocarcinoma: outcomes analysis and impact of molecular profiling

To evaluate characteristics, including tumor molecular profiling, and outcomes of patients with intrahepatic cholangiocarcinoma (ICC) submitted to percutaneous ablation (PA) This is a three-institution retrospective analysis of 46 patients (28 males) with a total of 69 ICCs (local therapy treatment-naïve at target ICC: 53) submitted to PA (Radiofrequency ablation = 25; Microwave ablation = 39; Irreversible electroporation = 5 ICCs) between 2007 and 2019. Indications included unresectable (12 patients; 15 ICCs), post-radiation (5 patients; 5 ICCs), and post-resection recurrence (29 patients, 49 ICCs). Median tumor diameter was 1.6 cm (range, 0.5-5.1 cm). Outcomes evaluated included local tumor progression-free survival (LTPFS), intra-hepatic progression-free survival (IHPFS), overall survival (OS), and major complications. Recent molecular profiling studies indicate a distinct pattern of somatic mutations in ICC; we explored the impact of these mutations on the clinical outcomes from PA. 42 patients with a total of 65 ICCs had imaging follow-up (mean 25.7 months, range 0.7-93.6). Primary technical efficacy was 92%. Three-year LTPFS was 71.5%, mean IHPFS was 15.6 months, and mean OS was 47.1 months for the entire cohort. One major complication (liver abscess) occurred, with no deaths recorded. Somatic mutations were present in 13 (72%) of the 18 patients who received molecular profiling, 6 patients (33%) with a total of 9 ICCs, which possess poor-prognosis mutations (CDKN2A = 3; ARID1A = 2; MSH2 = 1). Three-year LTPFS, mean IHPFS, and mean OS for patients with poor-prognosis mutations were 66.7%, 9.8 months, and 28.8 months, respectively. PA is an effective loco-regional therapy for small-localized ICC. Larger cohort studies are warranted to evaluate the association between mutational profile and efficacy of liver-directed therapies.

MutViz2.0: visual analysis of somatic mutations and the impact of mutational signatures on selected genomic regions.

Patterns of somatic single nucleotide variants observed in human cancers vary widely between different tumor types. They depend not only on the activity of diverse mutational processes, such as exposure to ultraviolet light and the deamination of methylated cytosines, but largely also on the sequence content of different genomic regions on which these processes act. With MutViz (http://gmql.eu/mutviz/), we have presented a user-friendly web tool for the identification of mutation enrichments that offers preloaded mutations from public datasets for a variety of cancer types, well organized within an effective database architecture. Somatic mutation patterns can be visually and statistically analyzed within arbitrary sets of small, user-provided genomic regions, such as promoters or collections of transcription factor binding sites. Here, we present MutViz 2.0, a largely extended and consolidated version of the tool: we took into account the immediate (trinucleotide) sequence context of mutations, improved the representation of clinical annotation of tumor samples and devised a method for signature refitting on limited genomic regions to infer the contribution of individual mutational processes to the mutation patterns observed in these regions. We described both the features of MutViz 2.0, concentrating on the novelties, and the substantial re-engineering of the cloud-based architecture.

Respiratory complex and tissue lineage drive recurrent mutations in tumour mtDNA.

Mitochondrial DNA (mtDNA) encodes protein subunits and translational machinery required for oxidative phosphorylation (OXPHOS). Using repurposed whole-exome sequencing data, in the present study we demonstrate that pathogenic mtDNA mutations arise in tumours at a rate comparable to those in the most common cancer driver genes. We identify OXPHOS complexes as critical determinants shaping somatic mtDNA mutation patterns across tumour lineages. Loss-of-function mutations accumulate at an elevated rate specifically in complex I and often arise at specific homopolymeric hotspots. In contrast, complex V is depleted of all non-synonymous mutations, suggesting that impairment of ATP synthesis and mitochondrial membrane potential dissipation are under negative selection. Common truncating mutations and rarer missense alleles are both associated with a pan-lineage transcriptional programme, even in cancer types where mtDNA mutations are comparatively rare. Pathogenic mutations of mtDNA are associated with substantial increases in overall survival of colorectal cancer patients, demonstrating a clear functional relationship between genotype and phenotype. The mitochondrial genome is therefore frequently and functionally disrupted across many cancers, with major implications for patient stratification, prognosis and therapeutic development.

Identification of the Prognostic Significance of Somatic Mutation-Derived LncRNA Signatures of Genomic Instability in Lung Adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is a highly heterogeneous tumor with substantial somatic mutations and genome instability, which are emerging hallmarks of cancer. Long non-coding RNAs (lncRNAs) are promising cancer biomarkers that are reportedly involved in genomic instability. However, the identification of genome instability-related lncRNAs (GInLncRNAs) and their clinical significance has not been investigated in LUAD.Methods: We determined GInLncRNAs by combining somatic mutation and transcriptome data of 457 patients with LUAD and probed their potential function using co-expression network and Gene Ontology (GO) enrichment analyses. We then filtered GInLncRNAs by Cox regression and LASSO regression to construct a genome instability-related lncRNA signature (GInLncSig). We subsequently evaluated GInLncSig using correlation analyses with mutations, external validation, model comparisons, independent prognostic significance analyses, and clinical stratification analyses. Finally, we established a nomogram for prognosis prediction in patients with LUAD and validated it in the testing set and the entire TCGA dataset.Results: We identified 161 GInLncRNAs, of which seven were screened to develop a prognostic GInLncSig model (LINC01133, LINC01116, LINC01671, FAM83A-AS1, PLAC4, MIR223HG, and AL590226.1). GInLncSig independently predicted the overall survival of patients with LUAD and displayed an improved performance compared to other similar signatures. Furthermore, GInLncSig was related to somatic mutation patterns, suggesting its ability to reflect genome instability in LUAD. Finally, a nomogram comprising the GInLncSig and tumor stage exhibited improved robustness and clinical practicability for predicting patient prognosis.Conclusion: Our study identified a signature for prognostic prediction in LUAD comprising seven lncRNAs associated with genome instability, which may provide a useful indicator for clinical stratification management and treatment decisions for patients with LUAD.

PALLD mutation in a European family conveys a stromal predisposition for familial pancreatic cancer.

BACKGROUNDPancreatic cancer is one of the deadliest cancers, with low long-term survival rates. Despite recent advances in treatment, it is important to identify and screen high-risk individuals for cancer prevention. Familial pancreatic cancer (FPC) accounts for 4%–10% of pancreatic cancers. Several germline mutations are related to an increased risk and might offer screening and therapy options. In this study, we aimed to identity of a susceptibility gene in a family with FPC.METHODSWhole exome sequencing and PCR confirmation was performed on the surgical specimen and peripheral blood of an index patient and her sister in a family with high incidence of pancreatic cancer, to identify somatic and germline mutations associated with familial pancreatic cancer. Compartment-specific gene expression data and immunohistochemistry were also queried.RESULTSThe identical germline mutation of the PALLD gene (NM_001166108.1:c.G154A:p.D52N) was detected in the index patient with pancreatic cancer and the tumor tissue of her sister. Whole genome sequencing showed similar somatic mutation patterns between the 2 sisters. Apart from the PALLD mutation, commonly mutated genes that characterize pancreatic ductal adenocarcinoma were found in both tumor samples. However, the 2 patients harbored different somatic KRAS mutations (G12D and G12V). Healthy siblings did not have the PALLD mutation, indicating a disease-specific impact. Compartment-specific gene expression data and IHC showed expression in cancer-associated fibroblasts (CAFs).CONCLUSIONWe identified a germline mutation of the palladin (PALLD) gene in 2 siblings in Europe, affected by familial pancreatic cancer, with a significant overexpression in CAFs, suggesting that stromal palladin could play a role in the development, maintenance, and/or progression of pancreatic cancer.FUNDINGDFG SFB 1321

Shaping the BRCAness mutational landscape by alternative double-strand break repair, replication stress and mitotic aberrancies.

Tumours with mutations in the BRCA1/BRCA2 genes have impaired double-stranded DNA break repair, compromised replication fork protection and increased sensitivity to replication blocking agents, a phenotype collectively known as ‘BRCAness’. Tumours with a BRCAness phenotype become dependent on alternative repair pathways that are error-prone and introduce specific patterns of somatic mutations across the genome. The increasing availability of next-generation sequencing data of tumour samples has enabled identification of distinct mutational signatures associated with BRCAness. These signatures reveal that alternative repair pathways, including Polymerase θ-mediated alternative end-joining and RAD52-mediated single strand annealing are active in BRCA1/2-deficient tumours, pointing towards potential therapeutic targets in these tumours. Additionally, insight into the mutations and consequences of unrepaired DNA lesions may also aid in the identification of BRCA-like tumours lacking BRCA1/BRCA2 gene inactivation. This is clinically relevant, as these tumours respond favourably to treatment with DNA-damaging agents, including PARP inhibitors or cisplatin, which have been successfully used to treat patients with BRCA1/2-defective tumours. In this review, we aim to provide insight in the origins of the mutational landscape associated with BRCAness by exploring the molecular biology of alternative DNA repair pathways, which may represent actionable therapeutic targets in in these cells.

The Genotype-Based Morphology of Aldosterone-Producing Adrenocortical Disorders and Their Association with Aging.

Primary aldosteronism (PA) is the most common cause of secondary hypertension, and is associated with an increased incidence of cardiovascular events. PA itself is clinically classified into the following two types: unilateral PA, mostly composed of aldosterone-producing adenoma (APA); and bilateral hyperaldosteronism, consisting of multiple aldosterone-producing micronodules (APMs) and aldosterone-producing diffuse hyperplasia. Histopathologically, those disorders above are all composed of compact and clear cells. The cellular morphology in the above-mentioned aldosterone-producing disorders has been recently reported to be closely correlated with patterns of somatic mutations of ion channels including KCNJ5, CACNA1D, ATP1A1, ATP2B3, and others. In addition, in non-pathological adrenal glands, APMs are frequently detected regardless of the status of the renin-angiotensin-aldosterone system (RAAS). Aldosterone-producing nodules have been also proposed as non-neoplastic nodules that can be identified by hematoxylin and eosin staining. These non-neoplastic CYP11B2-positive nodules could represent possible precursors of APAs possibly due to the presence of somatic mutations. On the other hand, aging itself also plays a pivotal role in the development of aldosterone-producing lesions. For instance, the number of APMs was also reported to increase with aging. Therefore, recent studies indicated the novel classification of PA into normotensive PA (RAAS-independent APM) and clinically overt PA.