Frequency Of Driver Mutations Research Articles

Abstract 5900: INCB161734: A novel, potent, and orally bioavailable KRAS G12D selective inhibitor demonstrates antitumor activity in KRAS G12D mutant tumors

Abstract KRAS G12D (G12D) is one of the most frequent oncogenic driver mutations, and is especially common in pancreatic (PDAC) and colorectal (CRC) cancers. Patients with G12D-mutated disease experience poor treatment outcomes, representing a significant unmet medical need. G12D mutation results in constitutively active signaling, including hyperactivation of the ERK and PI3K pathways, which drive cell proliferation and survival. Here we describe INCB161734, a novel, potent, selective, and orally bioavailable small molecule G12D inhibitor that demonstrates in vivo efficacy in G12D-bearing tumor models. INCB161734 binds to both the GDP and GTP forms of the G12D mutant at the switch II pocket with picomolar affinity (KD), and exhibits >80-fold selectivity over wildtype (WT) KRAS. INCB161734 potently inhibits SOS1-dependent GDP/GTP exchange activity in cell-free assays (IC50 <3 nM), and exhibits >40-fold selectivity for G12D versus WT KRAS. Additionally, INCB161734 demonstrates high selectivity for G12D over WT in various cellular assays using G12D mutant versus WT cancer derived cell lines. INCB161734 potently inhibits ERK phosphorylation (a correlate for KRAS activity), with a mean IC50 of 14.3 nM (range: 1.9-45.2 nM) across 7 human and 3 mouse G12D cell lines; mean 21.5% inhibition was observed at 1 μM (maximum tested concentration) across 14 WT cell lines. Likewise, INCB161734 inhibits proliferation of G12D mutant cell lines, with a mean IC50 of 154 nM (range: 8.3-318 nM) across the same 7 human G12D cell lines; <30% inhibition (mean 13%) was observed at 1 μM across the same 14 WT cell lines. Treatment with INCB161734 induces caspase 3/7 cleavage in a PDAC cell line (G12D HPAC), with EC50 <100 nM; caspase 3/7 cleavage in a WT cell line (NCI-H838) was not induced at doses as high as 5 μM. In addition, INCB161734 induced cell cycle arrest (S-phase inhibition) in the G12D HPAC cell line, with IC50 12.8 nM; S-phase inhibition in the WT NCI-H838 cell line only occurred at much higher doses (IC50 >3.3 μM). INCB161734 demonstrates excellent oral bioavailability with good absorption, low clearance, and low metabolic turnover. Orally dosed INCB161734 clearly shows target engagement, generating continuous near-maximal KRAS inhibition in G12D HPAC mouse xenograft tumors for almost the entire dosing interval. INCB161734 is efficacious against multiple types of G12D-mutated tumors and xenografts, resulting in significant tumor growth inhibition, growth arrest and/or regression in multiple PDAC (HPAC, Panc0403, and 2838c3) and CRC (CT26, GP2D, and LS513) mouse tumor models. These preclinical results demonstrate that INCB161734 is a potent, selective, and orally bioavailable KRAS G12D inhibitor, strongly efficacious against KRAS G12D mutant tumors. The potential benefit of INCB161734 for patients with KRAS G12D mutant disease is under investigation in ongoing clinical trials. Citation Format: Matthew R. Farren, Valerie Roman, Alexandra Gallion, Abdellah Allali-Hassani, Alexander Sokolsky, Weixi Kong, Amanda Smith, Hui Wang, Gina Correa, Marc Deller, Leslie B. Epling, Jessica Procak, Guofeng Zhang, Katherine Pecko, Keith Kennedy, Jason Boer, Kerri Kurzeja-Lipinski, Maryanne Covington, Kwang-Jong Chen, Renee Wallower, Jennifer Rocha, Rina Pan, Anthony Perry, Brad Yuska, Xiaozhao Wang, Ricardo Macarron, Sunkyu Kim. INCB161734: A novel, potent, and orally bioavailable KRAS G12D selective inhibitor demonstrates antitumor activity in KRAS G12D mutant tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5900.

Abstract 1614: Macroscopic clonal expansion with driver mutations in normal human endometrium

Abstract Introduction: The epithelial cells of the endometrium undergo rapid proliferation and shedding each month under the influence of estrogen and progesterone. Recent studies have demonstrated pervasive driver mutations in the endometrium with ageing. However, previous observations have been limited to the microscopic scale, and it is still unclear how clonal expansion occurs over the entire endometrium and what driver mutations are responsible therein. To address these issues, we performed multisampling of the endometrium with extensive spatial mapping. Methods: We collected multiple endometrial glands from normal endometrium in a 5mm lattice in 19 patients aged 30 to 85 years who underwent hysterectomy (3-31 samples per case), followed by DNA extraction, detected somatic mutations by whole exome sequencing, to identify large clones that spread across samples based on shared mutations. Results: In total, 213 bulk endometrial glands were analyzed. The number of detected somatic mutations per sample ranged from 4 to 81 (mean±SD: 32.5±14.1), with at least one known driver gene mutation detected in 204 of 213 samples (mean±SD: 3.03±1.78). The mutational signature analysis revealed the predominance of the age-related SBS1 and SBS5 signatures. dN/dS analysis identified 20 genes that were positively selected in normal endometrium, including PIK3CA, PIK3R1, KRAS, PPP2R1A, ARHGAP35, and FBXW7, most of which are also known as driver genes for endometrial cancer. The number of mutations and their frequency for each driver gene did not differ by background diseases: endometriosis, endometriosis-associated ovarian cancer and other non-endometrial related diseases. In contrast to the high frequency of driver gene mutations, copy-number alterations were found in only 3 samples, such as +1q, +7, +10 and +12. We found clones showing a large expansion involving multiple samples in 8 cases, most of which harbored one or more driver mutations, such as PIK3CA and KRAS. The size of the largest clone carrying a KRAS mutation, which was found in a 32-year-old woman with cervical cancer, spanned as long as 10 mm in diameter. This suggests that clonal expansion in the endometrium could be very rapid even in healthy women, which contrasts to the observations that clonal expansion in other organs is usually seen in aged individuals. Conclusion: We confirmed the high frequency of driver mutations in the normal endometrium, most of which overlapped to those found in endometrial cancers, suggesting that these driver genes are involved in the early phase of the development in the endometrial cancer. Some of the driver-mutated clones expanded in macroscopic size. Our findings provide an interesting insight into the clonal structure and underlying genetic variation in the normal endometrium. Citation Format: Koichi Watanabe, Nobuyuki Kakiuchi, Kosuke Ieiri, Hirona Maeda, Tomonori Hirano, Sachiko Kitamura, Mana Taki, Koji Yamanoi, Ryusuke Murakami, Ken Yamaguchi, Junzo Hamanishi, Hiroko Tanaka, Satoru Miyano, Masaki Mandai, Seishi Ogawa. Macroscopic clonal expansion with driver mutations in normal human endometrium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1614.

46P The frequency of driver mutations in non-small cell cancer patients: Analysis of the 5064 patients in the Turkish nation-wide, observational, registurkLung study

46P The frequency of driver mutations in non-small cell cancer patients: Analysis of the 5064 patients in the Turkish nation-wide, observational, registurkLung study

Abstract PR002: Somatic mutation rates and strength of selection on driver genes change by age in melanoma

Abstract The frequencies of driver mutations in melanoma vary in patients of different ages. However, it is unclear whether these differences in frequency are driven by variation in underlying mutation rates or by a changing selective regime in the aging body. Employing a bulk tumor sequence dataset from 5472 melanomas (459 whole-exome sequences and 5013 cancer gene-panel sequences) analyzed with the cancereffectsizeR package, we quantified somatic mutation rates and the strength of selection on somatic mutations, measuring the survival advantage conferred by a somatic mutation across the tumorigenic trajectory. Likelihood ratio tests were used to compare cancer effect sizes between age groups: <40 y/o, 40-59 y/o and ≥ 60 y/o. The proportion of cancer effect attributable to each mutational source was calculated by averaging over bootstrapped resample of mutational signature weights. Mann-Whitney U statistics were used to test the difference in signature weights and cancer effect sources across the groups.The underlying mutation rate increased with age, with a mean of 4.49e-6, 4.88e-6, 6.45e-6 in patients <40 y/o, 40-59 y/o and ≥ 60 y/o respectively. From the whole-exome and panel data, 23 variants differed significantly across age groups, among which BRAF V600E had the largest effect sizes, followed by NRAS Q61R, NRAS Q61K, NRAS Q61L. BRAF V600E were significantly larger in patients <40 y/o, while NRAS Q61R, NRAS Q61K, NRAS Q61L were significantly larger in patients 40-59 y/o and ≥ 60 y/o. Although underlying mutation rates and strengths of selection varied across age groups, the origin of melanomas from patients in all three age groups was predominantly attributed to UV light. These observations illuminate numerous theoretical questions regarding the origins of cancer at different ages. They are helpful to widespread implementation of prevention strategies. Moreover, understanding the relative strength of selection on driver mutations within patients at distinct ages is crucial for improving precision therapeutic interventions. Citation Format: Yihan Liu, Moein Rajaei, Jeff Mandell, Jeffrey Townsend. Somatic mutation rates and strength of selection on driver genes change by age in melanoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr PR002.

Understanding causes of racial/ethnic survival disparity in 47,178 patients with colorectal cancer: A quantitative evaluation of molecular, socioeconomic, and clinical covariates.

20 Background: A disparity in overall survival (OS) of colorectal cancer (CRC) patients based on self-reported race has been observed. Separately, differing frequencies of driver gene mutations among racial groups have been observed. The contribution of these molecular differences to disparity in outcomes is not well understood. We conducted a systematic investigation of molecular, socioeconomic (SES) and clinical covariates to quantitate the degree to which each influences the OS disparity. Methods: The Foundry software platform was used to query electronic health records to identify CRC patients and extract clinical and molecular data. The relative contribution of each variable to OS disparity was determined using mediation analysis consisting of sequential multivariate Cox regression models. Results: 47,178 patients with CRC diagnosed between 1973 and 2023 with self-reported race were identified. Relative to Non-Hispanic white (NHW), African American (AA) had worse OS (HR=1.16, P= 1.5E-6), while Asians and Hispanics had better OS (HR=0.66, P=4.2E-13 and HR=0.86, P=3.4E-6, respectively). The magnitude of disparity between AA and NHW was greater in metastatic disease (HR 1.2, P=1.7E-4). Among 7,628 patients with clinical molecular testing, five genes differed significantly in mutation frequencies; APC (54% NHW, 62% AA, 57% Hispanics, 46% Asian, FDR= 0.01), KRAS (45%, 58%, 50%, 44%, FDR=8.4E-9), PIK3CA (17%, 23%, 17%, 12%, FDR=0.006) were higher in AA, while BRAF (8%, 3%, 4%, 7%, FDR=2.4E-8), KIT (4%, 1%, 2%, 3%, FDR=0.013) were higher in NHW. In multivariate analysis mutations of BRAF (HR= 1.9, P=1.2E-8), KRAS (HR= 1.39, P=1.7E-7), and APC (HR= 0.81, P= 5E-4) were significantly associated with OS as was national area deprivation index (HR= 1.07, P=0.004), marital status (HR= 1.16, P=0.03), performance status (HR= 1.42, P= 5.3E-29), disease stage (HR= 1.502, P=4.4E-26), right sided tumors (HR= 1.23, P=0.003), tumor differentiation (HR= 1.22, P=0.004) and MSI-high (HR= 0.37, P=1.8E-7). Mediation analysis identified neighborhood SES as the greatest contributor to disparity (38%), followed by primary tumor side (10%), and molecular characteristics (MSI-status, KRAS and BRAF mutations, 10%). After including all covariates, 39% of disparity remained unaccounted. Conclusions: Systematic evaluation of a large cohort from a single institution confirmed substantial racial disparity in survival and frequencies of driver mutations. SES factors have the largest contribution but account only for forty percent of the disparity, with tumor molecular features also contributing. Molecular characteristics should be incorporated in multicentric studies of racial survival disparity. Future clinical studies should ideally account for genetic ancestry and molecular features when evaluating chemotherapy outcomes.

Comparison of colorectal cancer (CRC) characteristics across genetic ancestries: Implications for early cancer detection (ECD).

164 Background: Blood-based ECD has the potential to reduce mortality rates by improving strategies for, adoption of, and adherence to screening. A deeper understanding of the cancer genomic landscape across genetic ancestries will aid comparable detection performance across a broad population. We evaluated the mutational landscape in patients with CRC across genetic ancestries. Methods: 16,080 de-identified patients with stage I-IV CRC who had personalized, tumor-informed commercial ctDNA testing (Signatera) based on whole exome sequencing (WES) were included. Genetic ancestry determined via supervised local ancestry inference (pmid36042219) included African (AFR), East Asian (EAS), European (EUR), Latino (LAT), and South Asian (SAS). Patients assigned to a single ancestry were included (except SAS due to small cohort size). Somatic single nucleotide variants called from WES were used for mutational signature inference. EUR was the reference group for standard statistical tests with corrections for multiple hypothesis testing. Results: A single genomic ancestry was assigned for 16,257 (99.2%) patients (AFR n=1697, 10%; EAS n=2247, 14%; EUR n=10,526, 64%; LAT n=1291, 1%; SAS n=184, 1%). Across AFR, EAS, EUR, and LAT, approximately half of patients were male (range, 47-54%) and most were aged >50 years. Microsatellite instability (MSI) rates were significantly higher in EUR (14.5%) v AFR (11%, p<0.001), EAS (8%, p<0.001), and LAT (11%, p=0.002). Compared to EUR (range 0.027-875.1 mut/Mb), the distribution of TMB was significantly higher in EAS (0.304-906.2 mut/Mb, p<0.001) and lower in LAT (0.053-476.7 mut/Mb, p<0.001). The POLE hyper-mutator signature was seen in 1.2% of all patients and in 7.6% of all hyper-mutated cases. Patients with the POLE signature were less common in EUR (1.1%) v AFR (2%, p=0.001). There were significant differences in the frequency of driver mutations in APC, BRAF, KRAS, TP53, and PIK3CA between EUR and the other ancestry groups in both MSI and MSS tumors (Table). Median exposure levels to alkylation were higher in EAS v EUR. Conclusions: These data confirm previous results in AFR populations, and reveal novel differences in the EAS and LAT populations. Findings from this study may provide information for developing risk stratification and prevention strategies for the early detection of cancer and provide rationale for precision treatment based on ancestry. [Table: see text]

Patient-derived biliary tract cancer organoid biobank: Is personalized medicine utilizing organoids feasible for patients with cholangiocarcinoma?

533 Background: Cholangiocarcinoma (CC) is an aggressive malignancy with an all stage 5-year survival rate of less than 15%. Preclinical research is of pivotal importance to acquire a deeper understanding of CC and improve outcomes. The establishment of CC organoids has previously been described to be difficult due to fewer driver mutations and limitations in the ability to mimic tumor microenvironment. The aim of this study was to develop a successful culturing system for CC organoids that preserves intratumoral heterogeneity, and in turn, to determine the feasibility of personalized medicine in patients with CC using organoids. Methods: From 2020-2023, 75 CC tumor samples were prospectively collected from 65 patients. The tumors were sequenced using MSK-IMPACT, a targeted next generation sequencing (NGS) platform. Samples were processed, and organoids were generated and cultured following a standardized protocol. The organoids were grown in three different types of enriched media (M1, M2, and M3). Once cultures were adequately expanded, organoid lines were sequenced using MSK-IMPACT and/or MiSeq, a benchtop NGS platform. Mutations of the organoid line were compared to that of the tumor of origin to determine tumor enrichment. To ascertain genotypic association with organoid formation, we examined frequencies of driver mutations of interest. Logistic regression was used to assess the univariate association between mutations of interest and organoid establishment. Two-sided p-values less than 0.05 were considered to be significant. Results: Of the 75 samples collected, 24 (32%) were extrahepatic CC tumors, and the remaining were of intrahepatic origin. 92% of the samples were collected from primary tumors, and 71% of the samples were chemotherapy naïve. 64 samples successfully grew organoids. Upon evaluation of MSK-IMPACT and MiSeq data, 11 of the 64 samples were noted to retain the mutations of the tumor of origin in organoid culture; the overall success rate of tumor organoid formation was 14.6% (11/75). Tumor enrichment of organoid lines was most commonly achieved using M3 (9 out of 11 samples), the median passage at which tumor enrichment occurred was 8 (interquartile range (IQR) 2-10), indicating that the approximate median time to tumor organoid formation was 16 weeks (IQR 4-20 weeks). There was no statistically significant association between driver mutations and organoid establishment. Conclusions: Intratumoral heterogeneity of cholangiocarcinoma is maintained in organoid culture. This preclinical model potentially recapitulates the clinical features of the disease seen in humans. However, prolonged duration and low success rate of tumor enrichment makes it a less appealing avenue for personalized medicine.

High Frequency of HLA-Class II B Cell Receptor Neoantigens in IGHV Mutated-CLL

Introduction: Chronic lymphocytic leukemia (CLL) is the most common hematological malignancy and remains incurable. IGHV mutational status is an independent predictor of outcome with chemoimmunotherapy, however the mechanism(s) underpinning the superior prognosis of M-CLL are still to be elucidated. Clonal T cell expansions are well described in CLL. Neoantigens are immunogenic peptides unique to malignant cells, which are presented to host T cells via HLA-I/II, and if harnessed may have potential as a novel immunotherapeutic strategy. It is believed CLL has a low tumor mutational burden (TMB) due to few somatic mutations (~1/Mb) and hence few somatic neoantigens. However, traditional concepts of TMB fail to recognize that the IGH and IGκ/λ chains of the B cell receptor (BCR) also become highly mutated during B cell maturation. BCR mutations in B cell malignancies can create ‘BCR neoantigens’ (Khodadoust, Nature 2017 / Blood 2019). There is no large-scale analysis of HLA-I/II somatic and BCR neoantigens in CLL. Methods: Pre-therapy PBMCs from 23 patients with CLL (M17:F6, median 69 yrs, M-CLL=10, U-CLL=13) were tested. Cytogenetics and patient characteristics were similar between M-CLL and U-CLL. Samples underwent paired WES and RNAseq. Somatic mutations were called by Strelka2 and somatic neoantigens by pVACseq (TESLA guidelines; Wells, Cell 2020). BCR neoantigens were called from full-length BCR sequences by pVACbind. Neoantigen transcriptome expression was confirmed in all cases. Results: Importantly, expression of genes important for CLL antigen presentation was almost universally preserved. Furthermore, consistent with T cells controlling disease progression, central memory/effector T cells were expanded in both M-CLL and U-CLL by CIBERSORTx. Next, the somatic mutational landscape was characterized. WES revealed a median 1.06 somatic mutations/Mb, with frequency of driver mutations as expected (Knisbacher, Nature 2022). Only a median 22% of mutations/case were expressed, with expression of driver mutations only modestly increased in U-CLL vs M-CLL (1 vs 0, p=0.024), suggesting that enrichment of driver mutations in U-CLL only partially explains its inferior prognosis. Strikingly, unlike somatic mutations, all BCR mutations were expressed, with 12x > BCR mutations expressed in M-CLL vs U-CLL (37 vs 3, p<0.0001). Furthermore, in M-CLL expressed BCR mutations were 3x > somatic mutations, whereas BCR mutations were 3x < somatic mutations in U-CLL. Neoantigens were then assessed (Figure 1). Combining somatic + BCR neoantigens, there were a median 24 neoantigens/case. Somatic neoantigens included those found in driver mutations (ATM, XPO1, SF3B1, TP53, NOTCH1). Expression of driver neoantigens were retained in sequential patient samples and new driver neoantigens also acquired. Importantly, public neoantigens (i.e., neoantigens shared across CLL patients) in TP53 and XPO1 were detected. Notably, the frequency of BCR neoantigens was higher than somatic neoantigens, with differences most marked and enriched for HLA-II (HLA-I: 5 vs 2, p<0.0001 and HLA-II: 17 vs 3, p<0.0001). Strikingly, there were 2x > BCR neoantigens in M-CLL vs U-CLL (HLA-I: 6 vs 2, p<0.001; HLA-II: 23 vs 15, p=0.032). Interestingly, the nature of BCR neoantigens between M-CLL and U-CLL was different. Consistent with M-CLL B cells undergoing somatic hypermutation, IGHV mutations strongly positively correlated with numbers of V region BCR neoantigens (R 2=0.784, p<0.0001), and weakly negatively correlated with V(D)J recombination region BCR neoantigens (R 2=0.3992, p<0.005). As expected, there was no correlation between the number of IGHV mutations and somatic neoantigens. Conclusions: The reported low TMB in CLL does not reflect the true frequency of neoantigens, as it fails to account for BCR neoantigens. These contribute ~80% of the neoantigen pool and are predominantly presented by HLA-II. The majority of BCR neoantigens in M-CLL are within the V region, whereas in U-CLL, BCR neoantigens are largely restricted to the V(D)J recombination site. The known enrichment of driver mutations in U-CLL coupled with the increase of BCR neoantigens in M-CLL, are the likely mechanisms behind the different survival outcomes between M-CLL and U-CLL. The presence of public neoantigens in driver mutations opens up the possibility of off-the-shelf neoantigen specific immunotherapy and warrants further investigation.

ATG/ATLG Improves GvHD-Free and Relapse-Free Survival in Myelofibrosis Undergoing Hematopoietic Stem Cell Transplantation

Background Despite recent improvements in the field of JAK inhibitors, allogeneic hematopoietic stem cell transplantation (HSCT) remains the only potentially curative treatment for patients with myelofibrosis. However, HSCT is associated with a non-negligible treatment-related morbidity and mortality, with graft-versus-host disease (GvHD) being one of the major complications for these patients. In vivo T-cell depletion with antithymocyte/antilymphocyte globulin (ATG/ATLG, short ATG) as part of the conditioning regimen prior to HSCT is widely used as a GvHD prophylaxis, but data on its role in the setting of myelofibrosis is scarce. The aim of this study was to evaluate the impact of ATG on clinical outcomes of patients with myelofibrosis undergoing HSCT in a large international retrospective study. Patients and Methods We leveraged a multicenter collaborative network of 7 European and US academic transplant centers to accrue myelofibrosis patients who underwent first HSCT. The primary endpoint was GvHD-free and relapse-free survival (GRFS), whereas secondary endpoints were acute and chronic GvHD, relapse incidence, non-relapse mortality (NRM), and overall survival (OS). We applied multivariate Cox and Fine & Gray modelling to adjust for potential confounders. In addition, a Dependent Dirichlet Process model for censored data was developed, which can adjust for potential violations of the ubiquitous proportional hazards assumption. Finally, to check results and to obtain another reliable comparison, we applied a propensity score matching of the two groups. Results Overall, we identified 806 patients, of whom 513 received ATG and 293 received non-ATG GvHD prophylaxis. No significant differences were observed between the two groups with regards to median age at HSCT (57 years for both) nor for gender, disease ontogenesis (primary or secondary), frequency of driver mutations, and treatment with ruxolitinib prior to transplant. Patients in the ATG and the non-ATG group differed for other characteristics including splenectomy prior to transplant (8% vs. 20%), donor type (matched related donor (MRD): 21% vs. 39%), Karnofsky Performance Status (<90%: 39% vs. 26%), intensity of conditioning therapy (reduced intensity conditioning (RIC) in 80% vs. 40%) and the presence of constitutional symptoms (58% vs. 44%). Regarding the Dynamic International Prognostic Scoring System (DIPSS), the ATG cohort was more enriched in intermediate-2 and high-risk diseases (64% vs. 58%). Notably, the most common stem cell source in the ATG and the non-ATG cohort was in both cases peripheral blood (98% vs. 95%). The cumulative incidence of acute GvHD grade II-IV was 35% (95% CI, 31-39%) for the ATG group vs. 58% (95% CI, 52-64%) for the non-ATG group (P<0.001). No difference in incidence of chronic GvHD was observed, showing 53% (95% CI, 49-57%) for the ATG group vs. 52% (95% CI, 47-57%) for the non-ATG group (P=0.52). With a median follow-up of 6.5 years for the ATG group and 7 years for the non-ATG group (P=0.10), the 5-year estimates for GRFS were 47% (95% CI, 43-51%) vs. 44% (95% CI, 38-50%; P=0.007; Figure), respectively. The 5-year cumulative incidence of relapse was 14% (95% CI, 10-18%) vs. 13% (95% CI, 8-18%; P=0.62) and the 5-year cumulative incidence of death without relapse for both groups was 28%, respectively (P=0.59). Remarkably, 5-year OS was similar, being 63% (95% CI, 59-67%) for the ATG group vs. 62% (95% CI, 58-68%) for the non-ATG group (P=0.56). Multivariable modelling for GRFS (adjusting for donor type, performance status, conditioning intensity, and DIPSS categories) showed an independent significant reduction in risk for GvHD or relapse in the ATG group (HR=0.85, 95% CI 0.79-0.91; P=0.007). Propensity score matching of 150 pairs confirmed the significant effect of ATG on GRFS (HR 0.90, 95% CI, 0.82-0.98; P=0.03). No differences between the two groups were identified for secondary endpoints of relapse, non-relapse mortality, and overall survival. Conclusion The use of ATG as GvHD prophylaxis in patients with myelofibrosis undergoing HSCT resulted in significantly reduced GRFS. This effect was mainly driven by a significant reduction in acute GvHD.

Systematic Mapping of Gene-Editable Mutations in GATA2 and SAMD9/SAMD9L Syndromes

Germline predisposition to bone marrow failure (BMF) and myelodysplastic syndromes (MDS) cause substantial economic and psychosocial burden and early mortality in affected individuals. Due to the limitations and risks of hematopoietic stem cell transplantation, there is an urgent need for new and innovative treatment approaches. Conventional lentiviral-based gene therapy is not feasible for most BMF/MDS predisposing genes because their uncontrolled overexpression is detrimental and lentiviral vectors might cause insertional mutagenesis. However, new technologies that precisely modify the endogenous allele can overcome these limitations. Base editing (BE) using cytosine base editors (CBE) and adenine base editors (ABE) as well as prime editing (PE) are advanced gene editing techniques with great therapeutic promise. The goal of this project is to develop a comprehensive map of gene-editable mutations in the GATA2, SAMD9, and SAMD9L genes as a preclinical effort to facilitate gene editing trials. Germline heterozygous mutations in these key predisposing genes lead to highly penetrant disorders characterized by progressive immunodeficiency and BMF/MDS risk, with particularly high prevalence in children, as recently reported by us (Sahoo, Nature Medicine 2021) and others. For in depth analysis, we focused on the 5 most recurrent mutations in respective genes and devise strategies to correct mutations in cellular models. We first created a comprehensive database encompassing reported and unpublished pathogenic mutations (single nucleotide variants [SNVs] and <20bp insertion/deletions[indels]). In total, we annotated 506 cases with GATA2, 195 cases with SAMD9, and 187 cases with SAMD9L mutations. SNVs were detected in 83.2% (421/506), 94.4% (184/195), and 93.1% (174/187) patients with GATA2, SAMD9, SAMD9L mutations, respectively, while remaining cases had indels. Among all GATA2 cases, 59.9% (303/506) mutations are editable by ABE, 4.5% (23/506) by CBE, while remaining 35.6% (180/506) can be “rescued” by PE ( Fig. 1A). For SAMD9, 34.4% (67/195) cases were found to be amenable to editing by ABE, 30.3% (59/195) by CBE, and 35.4% (69/195) using PE. For SAMD9L, 47.1% (88/187) are editable by ABE, 20.3% (38/187) by CBE, and 32.6% (61/187) using PE. Having a well-annotated mutation list, we proceeded to identify the top 5 most common mutations in each gene ( Fig. 1B). Remarkably, all 5 mutations in both GATA2 and SAMD9 and 4 out of 5 top mutations in SAMD9L and amenable to BE. Next, we explored in depth the target editing window, protospacer adjacent motif (PAM) sites, and bystander editing effect (utilizing BE that recognize the canonical [NGG], and non-canonical PAM sequences [NG and near PAMless SpRY-NRN/NYN]. This stepwise approach resulted in successful identification of at least one potential guide RNA for each mutation with predicted low bystander editing. Ongoing work includes guide RNA validation, off-target analysis, and assessment of gene-editing efficiency using model cell lines. In conclusion, we have undertaken a systematic analysis of the gene editing landscape for frequent germline driver mutations in BMF/MDS. Our findings reveal promising editing strategies for the majority of prevalent mutations in key predisposing genes GATA2, SAMD9 and SAMD9L using CBE, ABE, or PE editors, and lay a groundwork to enable future clinical translation.

The SF3B1 K666 Hotspot Mutation Confers Unfavourable Disease Risk across Major Myeloid Neoplasm Subgroups

SF3B1 is the most prevalent splicing factor mutated in myeloid neoplasms, detected in 20-30% of patients with myelodysplasia (MDS) and associated with a milder disease phenotype. SF3B1 mutations are typically single nucleotide variations occurring in hotspots in the HEAT domain. Disease-specific SF3B1 hotspot predilection is observed; for example, K700E is most common in MDS and R625 in uveal melanoma. The K666 hotspot has been associated with increased risk of MDS disease progression to acute myeloid leukemia (AML). However, the prognostic impact across all myeloid neoplasms inclusive of myeloproliferative neoplasms (MPN) and MDS/MPN overlap syndromes has not been established. Mutation information was collated from available datasets inclusive of unpublished clinical trial cohorts across patients with myeloid neoplasms (MDS, MPN, MDS/MPN, AML) and patients with solid malignancies and clonal hematopoiesis (CH). SF3B1 hotspot mutations were correlated with additional somatic mutations, disease type and other clinical parameters. Overall, 11,744 patients with myeloid neoplasms; MDS (n=4275), AML (n=3526), MDS/MPN (n=192), MPN (n=3751) and 24,146 patients with solid malignancies and CH were included in this analysis. SF3B1 mutations were present in 11.1% of patients; 21.3% MDS, 4.1% AML, 51% MDS/MPN and 3.7% MPN. In MDS, SF3B1 mutations were predominantly present in low risk MDS (23.8%) as compared with 4.1% in intermediate to high risk MDS. This contrasts with MPN where SF3B1 mutations were present at a higher frequency in more advanced MPN (5.5% in treatment-resistant ET, 8.8% in all MF cases and further augmented at 14% in JAK inhibitor resistant high-risk thrombocytopenic MF) as compared with earlier phase MPN (2.1% and 1.3% in ET and PV respectively). In MPN SF3B1-mutant cases, JAK-STAT signaling driver mutation frequency and distribution were in line with published data; 65.6% JAK2V617F-mutated, 18.8% CALR-mutated, 8.5% MPL-mutated and 7% triple negative. As previously described, SF3B1 K700E hotspot mutations were most prevalent (frequency 49.1%), followed by K666, H622 and R625 hotspot mutations at 20.6%, 7.6% and 6.1% respectively. K700E was enriched as expected in MDS cohorts and K666 hotspot mutations were enriched in AML (42%). Although less common in MDS (11.6 - 17.8%), the frequency of K666 mutation correlated with higher IPSS-M risk category in MDS (p=0.001; chi-squared test). In contrast to MDS, SF3B1 K666 was the dominant hotspot in MPN ranging 46-70% in frequency across subtypes from earlier to more advanced MPN such as MF (Fig 1A). SF3B1 K700E mutations were more often co-mutated with epigenetic mutations such as in DNMT3A, TET2, EZH2 and KMT2C genes (Fig 1B) whereas SF3B1 K666 mutations were significantly co-mutated with NPM1 and FLT3 in AML cases (odds ratio, OR, 25.6 and 4.2 respectively, p-value <0.0001) and JAK2V617F in MPN cases (OR 3.2, p<0.0001). SF3B1 K666 mutations also showed a trend towards significant co-occurrence with adverse prognostic mutations in AML; PHF6, PTPN11 and RUNX1. No differences were observed for SF3B1 hotspots for CALR or MPL-mutated MPN but numbers were too few to draw conclusions. In patients with SF3B1 mutations, 58% were male and K666 hotspot was more frequent in males (21% as compared with 11% in females, p<0.001, chi-squared test). There were no hotspot differences observed in age, ethnicity, bloods counts or karyotype where data was available for this analysis. In CH, SF3B1 mutations were detected in 0.5% with K700E (34.2%) and K666 (26.7%) frequencies equivalent (p=0.24). In summary, this large multi-cohort myeloid neoplasm analysis reveals myeloid disease-specific SF3B1 hotspot propensity. The K666 hotspot was frequent in MPN, particularly in persons with advanced disease where SF3B1 mutations are more prevalent than earlier phase MPN. We conclude that different SF3B1 hotspots are associated with distinct clinical phenotypes and in chronic myeloid malignancies; K666 SF3B1 mutation is associated with adverse clinical course. Additional studies to elucidate the distinct biological effects of different SF3B1 mutations are warranted.

Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

MGMT promoter methylation testing is required for prognosis and predicting temozolomide response in gliomas. Accurate results depend on sufficient tumor cellularity, but histologic estimates of cellularity are subjective. We sought to determine whether driver mutation variant allelic frequency (VAF) could serve as a more objective metric for cellularity and identify possible false-negative MGMT samples. Among 691 adult-type diffuse gliomas, MGMT promoter methylation was assessed by pyrosequencing (N = 445) or DNA methylation array (N = 246); VAFs of TERT and IDH driver mutations were assessed by next generation sequencing. MGMT results were analyzed in relation to VAF. By pyrosequencing, 56% of all gliomas with driver mutation VAF ≥ 0.325 had MGMT promoter methylation, versus only 37% with VAF < 0.325 (p < 0.0001). The mean MGMT promoter pyrosequencing score was 19.3% for samples with VAF VAF ≥ 0.325, versus 12.7% for samples with VAF < 0.325 (p < 0.0001). Optimal VAF cutoffs differed among glioma subtypes (IDH wildtype glioblastoma: 0.12–0.18, IDH mutant astrocytoma: ~0.33, IDH mutant and 1p/19q co-deleted oligodendroglioma: 0.3–0.4). Methylation array was more sensitive for MGMT promoter methylation at lower VAFs than pyrosequencing. Microscopic examination tended to overestimate tumor cellularity when VAF was low. Re-testing low-VAF cases with methylation array and droplet digital PCR (ddPCR) confirmed that a subset of them had originally been false-negative. We conclude that driver mutation VAF is a useful quality assurance metric when evaluating MGMT promoter methylation tests, as it can help identify possible false-negative cases.

The Patent Landscape of BRAF Target and KRAS Target.

KRAS and BRAF targets are involved in the epidermal growth factor receptor pathway. KRAS and BRAF targets are the most frequent driver mutations in cancer. The objective of the study was to present the recent developments in the KRAS target and the BRAF target. KRAS target and BRAF target were analyzed by US patent analysis. All US granted patent documents from January 2002 to November 2021 were retrieved. The results showed both KRAS and BRAF targets to be attractive targets for developing anticancer drugs. The technology of RNA interference has been developed for drug discovery related to the KRAS target. Our study indicates that the structural screening of inhibitors between the KRAS target and the BRAF target should be an inverse option. The chemical structures of inhibitors of BRAF target exhibited a unique classification of C07D405. The inhibitors of BRAF target could be used for the treatment of various cancers. However, the inhibitors of KRAS target did not show this feature. The present study provides new insight into drug discovery involving KRAS and BRAF targets.

Cerebrospinal fluid circulating tumour DNA genotyping and survival analysis in lung adenocarcinoma with leptomeningeal metastases

PurposeThe prognosis of patients with leptomeningeal metastasis (LM) remains poor. Circulating tumour DNA (ctDNA) has been proven to be abundantly present in cerebrospinal fluid (CSF); hence, its clinical implication as a biomarker needs to be further verified.MethodsWe conducted a retrospective study of 35 lung adenocarcinoma (LUAD) patients with LM, and matched CSF and plasma samples were collected from all patients. All paired samples underwent next-generation sequencing (NGS) of 139 lung cancer-associated genes. The clinical characteristics and genetic profiling of LM were analysed in association with survival prognosis.ResultsLM showed genetic heterogeneity, in which CSF had a higher detection rate of ctDNA (P = 0.003), a higher median mutation count (P < 0.0001), a higher frequency of driver mutations (P < 0.01), and more copy number variation (CNV) alterations (P < 0.001) than plasma. The mutation frequencies of the EGFR, TP53, CDKN2A, MYC and CDKN2B genes were easier to detect in CSF than in LUAD tissue (P < 0.05), possibly reflecting the underlying mechanism of LM metastasis. CSF ctDNA is helpful for analysing the mechanism of EGFR-TKI resistance. In cohort 1, which comprised patients who received 1/2 EGFR-TKIs before the diagnosis of LM, TP53 and CDKN2A were the most common EGFR-independent resistant mutations. In cohort 2, comprising those who progressed after osimertinib and developed LM, 7 patients (43.75%) had EGFR CNV detected in CSF but not plasma. Furthermore, patient characteristics and various genes were included for interactive survival analysis. Patients with EGFR-mutated LUAD (P = 0.042) had a higher median OS, and CSF ctDNA mutation with TERT (P = 0.013) indicated a lower median OS. Last, we reported an LM case in which CSF ctDNA dynamic changes were well correlated with clinical treatment.ConclusionsCSF ctDNA could provide a more comprehensive genetic landscape of LM, indicating the potential metastasis-related and EGFR-TKI resistance mechanisms of LM patients. In addition, genotyping of CSF combined with clinical outcomes can predict the prognosis of LUAD patients with LM.

Undifferentiated and Dedifferentiated Metastatic Melanomas Masquerading as Soft Tissue Sarcomas: Mutational Signature Analysis and Immunotherapy Response

The distinction between undifferentiated melanoma (UM) or dedifferentiated melanoma (DM) from undifferentiated or unclassifiable sarcoma can be difficult and requires the careful correlation of clinical, pathologic, and genomic findings. In this study, we examined the utility of mutational signatures to identify patients with UM/DM with particular attention as to whether this distinction matters for treatment because the survival of patients with metastatic melanoma has dramatically improved with immunologic therapy, whereas durable responses are less frequent in sarcomas. We identified 19 cases of UM/DM that were initially reported as unclassified or undifferentiated malignant neoplasm or sarcoma and submitted for targeted next-generation sequencing analysis. These cases were confirmed as UM/DM by harboring melanoma driver mutations, UV signature, and high tumor mutation burden. One case of DM showed melanoma in situ. Meanwhile, 18 cases represented metastatic UM/DM. Eleven patients had a prior history of melanoma. Thirteen of 19 (68%) of the tumors were immunohistochemically completely negative for 4 melanocytic markers (S100, SOX10, HMB45, and MELAN-A). All cases harbored a dominant UV signature. Frequent driver mutations involved BRAF (26%), NRAS (32%), and NF1 (42%). In contrast, the control cohort of undifferentiated pleomorphic sarcomas (UPS) of deep soft tissue exhibited a dominant aging signature in 46.6% (7/15) without evidence of UV signature. The median tumor mutation burden for DM/UM vs UPS was 31.5 vs 7.0 mutations/Mb (P < .001). A favorable response to immune checkpoint inhibitor therapy was observed in 66.6% (12/18) of patients with UM/DM. Eight patients exhibited a complete response and were alive with no evidence of disease at the last follow-up (median 45.5 months). Our findings support the usefulness of the UV signature in discriminating DM/UM vs UPS. Furthermore, we present evidence suggesting that patients with DM/UM and UV signatures can benefit from immune checkpoint inhibitor therapy.

Liquid Biopsies in Lung Cancer.

As lung cancer has the highest cancer-specific mortality rates worldwide, there is an urgent need for new therapeutic and diagnostic approaches to detect early-stage tumors and to monitor their response to the therapy. In addition to the well-established tissue biopsy analysis, liquid-biopsy-based assays may evolve as an important diagnostic tool. The analysis of circulating tumor DNA (ctDNA) is the most established method, followed by other methods such as the analysis of circulating tumor cells (CTCs), microRNAs (miRNAs), and extracellular vesicles (EVs). Both PCR- and NGS-based assays are used for the mutational assessment of lung cancer, including the most frequent driver mutations. However, ctDNA analysis might also play a role in monitoring the efficacy of immunotherapy and its recent accomplishments in the landscape of state-of-the-art lung cancer therapy. Despite the promising aspects of liquid-biopsy-based assays, there are some limitations regarding their sensitivity (risk of false-negative results) and specificity (interpretation of false-positive results). Hence, further studies are needed to evaluate the usefulness of liquid biopsies for lung cancer. Liquid-biopsy-based assays might be integrated into the diagnostic guidelines for lung cancer as a tool to complement conventional tissue sampling.

Crosstalk between tumor acidosis, p53 and extracellular matrix regulates pancreatic cancer aggressiveness.

Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive malignancy with minimal treatment options and a global rise in prevalence. PDAC is characterized by frequent driver mutations including KRAS and TP53 (p53), and a dense, acidic tumor microenvironment (TME). The relation between genotype and TME in PDAC development is unknown. Strikingly, when wild type (WT) Panc02 PDAC cells were adapted to growth in an acidic TME and returned to normal pH to mimic invasive cells escaping acidic regions, they displayed a strong increase of aggressive traits such as increased growth in 3-dimensional (3D) culture, adhesion-independent colony formation and invasive outgrowth. This pattern of acidosis-induced aggressiveness was observed in 3D spheroid culture as well as upon organotypic growth in matrigel, collagen-I and combination thereof, mimicking early and later stages of PDAC development. Acid-adaptation-induced gain of cancerous traits was further increased by p53 knockout (KO), but only in specific extracellular matrix (ECM) compositions. Akt- and Transforming growth factor-β (TGFβ) signaling, as well as expression of the Na+ /H+ exchanger NHE1, were increased by acid adaptation. Whereas Akt inhibition decreased spheroid growth regardless of treatment and genotype, stimulation with TGFβI increased growth of WT control spheroids, and inhibition of TGFβ signaling tended to limit growth under acidic conditions only. Our results indicate that a complex crosstalk between tumor acidosis, ECM composition and genotype contributes to PDAC development. The findings may guide future strategies for acidosis-targeted therapies.

In Multiple Myeloma Patients without Known Cytogenetic Risk Features, Genomic Features Contribute to Early Death Risk at Diagnosis

Multiple myeloma (MM) is a heterogeneous disease, and cytogenetic abnormalities such as t(4;14) and del17p are well-established independent high-risk features in newly diagnosed patients. In two clinical trials (N=1422), the IFM2009 and Determination, patients with del17p or t(4;14) had a hazard ratio of 1.9 (95% CI 1.5-2.4) and 1.6 (95% CI 1.2-2.1), respectively. However, the same study also showed that 25% of the remaining patients had a similar short PFS without any identified known high-risk features. To understand the genomic etiology of the high-risk in these patients, we generated WGS data from 640 newly diagnosed patients (GAMER dataset) in 3 categories (low risk [PFS > 36 months] without known risk features (LR), high-risk [PFS < 18 months] without known risk features (unknownHR, uHR) and high-risk with known risk features) (HR). Our primary focus was to find factors that contribute to high-risk without known risk features. As a validation set, we used WGS samples from newly diagnosed patients who enrolled in the DFCI 2009 study. Overall, we observed that t(14;16) was the only primary translocation that differs between uHR (7%) and the LR group (1%) (p value < 0.01). We found more frequent driver mutations in TP53(7%), ATM(6%), and EGR1(4%), in the uHR group (FDR < 0.05). In uHR group, we found that the cancer cell fraction carrying these mutations was significantly lower compared to double hits events observed in HR (p value = 6.4e-05), suggesting their presence in high-risk subclones. Chromosome 1q gain vs amplification were associated with similar outcomes in these patients (p value = 0.81), but both significantly differed from chr1q wild type (p value = 1.8e-07). High-risk patients with and without known risk features had a significant enrichment of mutations in the Genome Integrity pathways (24%) compared to the LR group. However, the enrichment in MAPK signaling pathway mutations (60%) was significantly different between the two high-risk groups. Features that contribute to genome integrity, such as structural variants (insertion, deletion, translocation and inversion, p value<0.001), mutational load (p=0.00025), and genomic scar scores (p=0.0007), were all significantly lower in the low-risk group compared to the uHR. The number of copy number alterations that have not been described before, such as del16, del8p and gain 9 and 19, were also significantly different between low-risk and high-risk patients without known risk features. We further searched for genomic factors that contribute to the classification of uHR using multiple statistical modeling and machine learning tools. All models were run using a 10-fold cross-validation for choosing variables to put into the final model. Using all variables in the final model, we created a classification model using the variables' significance and the model's accuracy. Out of 27 variables, we found that 7 (mutational load, structural variants, del8p, t(14;16), Genome Integrity Pathway, MAPK pathway and ISS > 2) significantly contributed to the classification model. On training and validation data, this model successfully detected the risk group (p value = 3.5e-09 and 0.0027, respectively). Our dataset gives the ability to identify genomic risk markers that are not currently considered in newly diagnosed MM and allows us to extend our understanding beyond traditional risk. The absence of unique and mutually exclusive markers between uHR and LR suggests the additive risk model in MM patients without known high risk markers. Additional risk features might be hidden in the transcriptome and regulation of the transcriptome. We are currently building an integrative model from the same patients with WGS, RNA-seq and methylation data. This will allow us to fine-tune our risk model and help us develop simplified and complex models on MM risk beyond known cytogenetic risk features.

Cancer Chemotherapy Accelerates the Loss of Clonal Diversity in Hematopoietic Stem Cells and Promotes the Convergent Evolution of Therapy-Related Clonal Hematopoiesis

Approximately 20,000 to 200,000 hematopoietic stem cells (HSCs) contribute to adult human hematopoiesis (Lee-Six et al. Nature 2018). HSCs lose clonal diversity with age, which is partly driven by the expansion of HSCs acquiring driver mutations (i.e., clonal hematopoiesis [CH]) (Mitchell et al. Nature 2022). HSCs are also subject to various types of external stressors such as chemotherapy. How the external stressors shape HSC clonality and dynamics remains unknown. To understand the influence of cancer chemotherapy on clonality and dynamics of hematopoietic stem and progenitor cells (HSPCs), we performed whole genome sequencing of 1,120 single-HSPC derived colonies from 10 patients with multiple myeloma (ages 46-65). We generated methocult colonies from GCSF mobilized peripheral blood stem cells (PBSCs) collected at the time of autologous stem cell transplant (ASCT, median 86 colonies per PBSCs). Previous chemotherapy exposure included a melphalan-based (MEL) regimen in 2 patients, a cyclophosphamide-based (CY) regimen in 2 patients, and lenalidomide (LEN) and/or bortezomib (BTZ)-based regimens in 6 patients. Despite the history of chemotherapy treatment, the number of somatic mutations in treated-HSPCs was comparable to that of age-matched HSPCs from normal individuals (Mitchell et al. Nature 2022), except in two patients with MEL treatment exhibiting significantly increased numbers of somatic mutations (median 2,339 vs. 1,146 somatic mutations per cell, P < 0.001). The excess mutations observed in MEL-treated HSPCs were consistent with the MEL-related mutation signature, SBS-MM1. None of the other patients' HPSCs showed treatment-related signatures. Importantly, HSPCs treated with CY, a similar alkylating agent, did not show an increased number of mutations or treatment-related signatures. This is likely because HSCs metabolize CY to an inactive form through aldehyde dehydrogenase (ALDH), which allows HSCs to escape from CY-induced DNA damage. Using shared and unique somatic mutations, we reconstructed phylogenetic trees of the HSPCs. Overall, we observed decreased clonal diversity of HSPCs in the current cohort compared to age-matched normal individuals (Mitchell et al. Nature 2022). The clonality of treated-HSPCs resembled that of individuals with advanced age (age>75 years) in normal individuals. Low clonal diversity was particularly evident in MEL and CY-treated patients, whereas HSPCs treated with LEN and BTZ showed relatively preserved clonal diversity. TP53 and PPM1D mutations were the most frequent driver mutations representing the clades of phylogenies. We observed multiple clades in the same patients having different mutations in the same genes (TP53 and PPM1D), which is consistent with the convergent evolution, the findings suggestive of strong selective pressure from chemotherapy. We also developed mathematical models simulating the population dynamics of HSCs with or without chemotherapy. These models showed that the loss of clonal diversity is accelerated by the administration of cytotoxic chemotherapy. Our results suggest that cytotoxic chemotherapy accelerates the loss of clonal diversity in HSPCs and promotes convergent evolution of clonal hematopoiesis driven by the mutations in DNA damaging pathway genes (TP53 and PPM1D), which likely forms the basis of therapy-related toxicities in hematopoiesis. However, the impact of cancer chemotherapy differs between drugs, and more studies are needed to systematically evaluate the differential effect of chemotherapies.

Clonogenic assays improve determination of variant allele frequency of driver mutations in myeloproliferative neoplasms

Molecular diagnostics moves more into focus as technology advances. In patients with myeloproliferative neoplasms (MPN), identification and monitoring of the driver mutations have become an integral part of diagnosis and monitoring of the disease. In some patients, none of the known driver mutations (JAK2V617F, CALR, MPL) is found, and they are termed “triple negative” (TN). Also, whole-blood variant allele frequency (VAF) of driver mutations may not adequately reflect the VAF in the stem cells driving the disease. We reasoned that colony forming unit (CFU) assay–derived clonogenic cells may be better suited than next-generation sequencing (NGS) of whole blood to detect driver mutations in TN patients and to provide a VAF of disease-driving cells. We have included 59 patients carrying the most common driver mutations in the establishment or our model. Interestingly, cloning efficiency correlated with whole blood VAF (p = 0.0048), suggesting that the number of disease-driving cells correlated with VAF. Furthermore, the clonogenic VAF correlated significantly with the NGS VAF (p < 0.0001). This correlation was lost in patients with an NGS VAF <15%. Further analysis showed that in patients with a VAF <15% by NGS, clonogenic VAF was higher than NGS VAF (p = 0.003), suggesting an enrichment of low numbers of disease-driving cells in CFU assays. However, our approach did not enhance the identification of driver mutations in 5 TN patients. A significant correlation of lactate dehydrogenase (LDH) serum levels with both CFU- and NGS-derived VAF was found. Our results demonstrate that enrichment for clonogenic cells can improve the detection of MPN driver mutations in patients with low VAF and that LDH levels correlate with VAF.