Mutations In Cancer-related Genes Research Articles

Hematologic malignancies and increased cardiovascular risk: a new issue to be considered for patient follow-up

The last decade has seen a significant increase in the number of long survivors after a hematologic cancer, both children and adults, due to significant improvement in treatment. This exciting result, however, has been associated with an increase in the occurrence of previously unknown cardiovascular complications, including acute myocardial infarction, stroke, heart failure, deep vein thrombosis and pulmonary embolism. These adverse outcomes are due to both the hematologic cancer per se and to antineoplastic therapy. Cancer-dependent complications are caused by a shift of blood and endothelial cells to a prothrombotic and proinflammatory phenotype associated also with cancer-related somatic gene mutations. Antineoplastic therapy, instead, can lead to adverse outcomes due to an increase in oxidative stress resulting from the effects of reactive oxygen and nitrogen species which can induce alterations of mitochondria and other intracellular organelles. In addition, cardiovascular complications following a hematologic malignancy are also due to the interaction between cancer and traditional cardiovascular risk factors such as smoking, hypertension, obesity and diabetes. Clinicians should take all of these factors into account, and adapt their usual follow-up schemes accordingly in patients who have survived a hematologic cancer.

Effect on Non-Small Cell Lung Cancer after Combination of Driver Gene Mutations and Anti-PD-1/PD-L1 Immunotherapy as Well as Chemotherapy.

We aimed to reveal the correlation between pathological indicators and PD-L1, between gene mutation status in lung cancer through clinico-pathological data and lung cancer-related gene mutation and PD-L1 expression analysis. The study was conducted in Jinhua Municipal Central Hospital, Zhejiang, China from 2017 to 2022. PD-L1 testing and targeted gene mutations detection were evaluated. The clinical characteristics of these non-small cell lung cancer (NSCLC) samples have been obtained. The groups (LUAD, n=142; LUSC, n=143) were grouped according to clinico-pathological features and PD-L1 expression (Yes/No or High/Low), and the clinico-pathological and genetic and molecular features and correlation with PD-L1 expression were compared across the above groups. Comparisons and analyses were made between different treatment schemes. Lung adenocarcinoma (LUAD, n=142) and lung squamous carcinoma (LUSC, n=143) samples were enrolled (median age: 64 years old). Pleural invasion and M staging were significantly different from PD-L1 alterations (P<0.05). The percentage of patients with PD-L1 tumor proportion score (TPS)≥50% was 36.24% and the percentage of patients with PD-L1 TPS<50% was 29.53%. The percentage of patients with PD-L1 high-expressed and treated by immunotherapy was 75.93% and 63.41% experienced Partial Response/Complete Response. The mutations ratio of EGFR, ALK, KRAS, MET, RET and TP53 were 28.86%, 1.34%, 6.04%, 0.67%, 1.34% and 0.67%, respectively. KRAS mutation was significantly different from PD-L1 alterations (P<0.01). There are individual differences in PD-L1 expression, which can also vary depending on the different clinical features. Specific molecular features correlate with differential PD-L1 expression and may influence the response to therapy.

OncoGPT: An AI assistant for genomic-driven precision oncology.

160 Background: Cancer patient’s unique genomic profile can help oncologists select a course of precise personalized treatment for the subject. High throughput next-generation sequencing (NGS) technology allows us to identify genomic alterations simultaneously within a patient’s tumor tissue and blood-circulating tumor DNA (ctDNA) in a single test, however, robust tool for accessing mutation-treatment matching is limited. Methods: OncoGPT was built on a cloud-based elastic computing platform. The NGS data analytical module consists of a cascade of computational algorithms for NGS data processing and gene variant calling. The interactive and univariate Cox proportional hazards models were used for mutation-treatment matching and prognostic effect analysis, respectively. Machine learning algorithms including decision tree, random forest, and neural network were trained and tested with novel features for tissue-of-origin (TO) classification across 8 caner types. Results: We built an AI-driven NGS data analytical platform by integrating computational models, matching algorithms and variant annotation databases to highly accurate achieve cancer-related gene mutations, copy number variation, and structure variants using NGS data from 35,122 tumors across 8 cancer types from three institutions. Next, an AI-driven TO classifier was developed and achieved a weighted F1 score of 0.926 for high confidence predictions (≥ 0.9) on tumor samples. Furthermore, augmented AI matching algorithms were applied to match the optimal personalized treatment and provide prognostic prediction for cancer patients with significantly bett survival outcomes (hazard ratio (HR) = 0.326; 95% confidence interval (CI) = 0.213–0.565; P = 2.52×10−5). Conclusions: We have successfully developed an innovative intelligent system (OncoGPT) with AI capabilities to help accurately find actionable targets from patient tumor or blood ctDNA NGS sequencing data and precisely match individualized therapeutic and clinical trial options for patients. In addition, OncoGPT classified primary tumor sites across 8 different cancer types with high confidence predictions. We believe that OncoGPT would help clinicians make optimal treatment decisions for cancer patients through genomic-driven precision oncology.

Basic knowledge for counseling patients undergoing risk-reducing salpingo-oophorectomy.

Significant progress has been made in the molecular diagnosis of cancer. It provides personalized medicine, including cancer diagnosis, prognosis, targeted therapy, and risk detection. These advances allow physicians to identify patients at risk for cancer before it develops and offer them an opportunity to prevent its development. Mutations in breast cancer susceptibility genes 1 and 2 (BRCA1 and 2) are one of the most well-known cancer-related gene mutations since actor Angelina Jolie shared her experience with genetic mutations and risk-reducing surgery in the media. In Korea, tests for germline BRCA1/2 mutations have been covered by insurance since May 2012 and the number of women of BRCA1/2 mutations has continued to increase over the past decade. Most carriers of BRCA1/2 mutations consider risk-reducing salpingo-oophorectomy (RRSO) resulting in early menopause and want to know the lifetime risks and benefits of RRSO. However, despite the increasing number of carriers of BRCA1/2 mutations, the counseling and management of patients requiring RRSO varies among physicians. This article provides basic knowledge on RRSO to help physicians comprehensively assess its risks and benefits and manage at-risk women.

Linking the companion diagnostic function of cancer genome profiling to therapy: Investigation of TMB-high predictors.

e13033 Background: Based on the companion diagnostic function of the Comprehensive Cancer Genome Profiling (CGP) test in Japan, pembrolizumab is the standard treatment for patients with Tumor Mutational Burden (TMB)-high (H) solid tumors. In this report, we attempted to extract predictive factors of TMB-H from CGP test results. Methods: We carried out a retrospective cohort study of 42 patients with malignant breast tumors (excluding circulating tumor DNA in the blood) who underwent CGP testing between June 1, 2019, and November 30, 2023, at our hospital and affiliated institutions. We analyzed the association between clinicopathological factors, the number of analyzed cancer-related gene mutations (SNV, InDel), and TMB-H using univariate and multivariate statistical analysis. Results: Of the 42 cases (27 positive and 15 negative for estrogen receptor (ER), respectively), seven (16.7%) were TMB-H. Samples significantly associated with TMB-H according to univariate analysis were submitted as pathology specimens (non-primary (16.7%) vs. primary (0%), p = 0.011), ER (positive (16.7%) vs. negative (0%), p = 0.044), letrozole (LET) (yes (11.9%) vs. no (4.8%), p = 0.008), and previous treatment (after 6th line (14.3%) vs. before (2.4%), p = 0.041). Multivariate analysis showed that LET had a significant effect on TMB-H in Aromatase inhibitor agents (LET + Anastrozole + Exemestane) (LET: OR, 19.9; 95% CI, 2.2–183.5; p = 0.008) and the number of cancer-related gene mutations (PIK3CA+TP53) were significantly affected (PIK3CA: OR, 3.8; 95% CI, 1.1–13.2; p = 0.032. TP53: OR, 0.08; 95% CI, 0.01–0.66; p = 0.015). Single regression analysis showed a significant association between the number of PIK3CA mutations and LET. (β, 0.31; SE, 0.11; p = 0.008). Conclusions: ER positivity, history of LET use, prior therapy after the 6th line, and submission of pathology specimens from non-primary tumors to CGP testing are predictive factors for TMB-H. In multivariate analysis, the history of LET use and the number of PIK3CA mutations were significantly associated with TMB-H. Research shows that PIK3CA mutations are most frequent in patients who have undergone preoperative endocrine therapy with LET (Breast Cancer Res Treat. 2020 Nov;184(1):123–133.), suggesting that an increased number of PIK3CA mutations due to LET contributed to TMB-H. Although immune checkpoint inhibitors (ICIs) are not indicated for ER-positive breast cancer, TMB-H may be a predictor of ICI efficacy in such cases. The limitations of our research were the small sample size, and the study population only included Japanese. For the next steps needed to continue in this research, clinical trials should take place to test whether TMB-H is a predictor of ICIs in a wider population of ER-positive breast cancer.

DIRMC: a database of immunotherapy-related molecular characteristics.

Cancer immunotherapy has brought about a revolutionary breakthrough in the field of cancer treatment. Immunotherapy has changed the treatment landscape for a variety of solid and hematologic malignancies. To assist researchers in efficiently uncovering valuable information related to cancer immunotherapy, we have presented a manually curated comprehensive database called DIRMC, which focuses on molecular features involved in cancer immunotherapy. All the content was collected manually from published literature, authoritative clinical trial data submitted by clinicians, some databases for drug target prediction such as DrugBank, and some experimentally confirmed high-throughput data sets for the characterization of immune-related molecular interactions in cancer, such as a curated database of T-cell receptor sequences with known antigen specificity (VDJdb), a pathology-associated TCR database (McPAS-TCR) etal. By constructing a fully connected functional network, ranging from cancer-related gene mutations to target genes to translated target proteins to protein regions or sites that may specifically affect protein function, we aim to comprehensively characterize molecular features related to cancer immunotherapy. We have developed the scoring criteria to assess the reliability of each MHC-peptide-T-cell receptor (TCR) interaction item to provide a reference for users. The database provides a user-friendly interface to browse and retrieve data by genes, target proteins, diseases and more. DIRMC also provides a download and submission page for researchers to access data of interest for further investigation or submit new interactions related to cancer immunotherapy targets. Furthermore, DIRMC provides a graphical interface to help users predict the binding affinity between their own peptide of interest and MHC or TCR. This database will provide researchers with a one-stop resource to understand cancer immunotherapy-related targets as well as data on MHC-peptide-TCR interactions. It aims to offer reliable molecular characteristics support for both the analysis of the current status of cancer immunotherapy and the development of new immunotherapy. DIRMC is available at http://www.dirmc.tech/. Database URL: http://www.dirmc.tech/.

Molecular profiling of a bladder cancer with very high tumour mutational burden

The increasing incidence of urothelial bladder cancer is a notable global concern, as evidenced by the epidemiological data in terms of frequency, distribution, as well as mortality rates. Although numerous molecular alterations have been linked to the occurrence and progression of bladder cancer, currently there is a limited knowledge on the molecular signature able of accurately predicting clinical outcomes. In this report, we present a case of a pT3b high-grade infiltrating urothelial carcinoma with areas of squamous differentiation characterized by very high tumor mutational burden (TMB), with up-regulations of immune checkpoints. The high TMB, along with elevated expressions of PD-L1, PD-L2, and PD1, underscores the rationale for developing a personalized immunotherapy focused on the use of immune-checkpoint inhibitors. Additionally, molecular analysis revealed somatic mutations in several other cancer-related genes, including TP53, TP63 and NOTCH3. Mutations of TP53 and TP63 genes provide mechanistic insights on the molecular mechanisms underlying disease development and progression. Notably, the above-mentioned mutations and the elevated hypoxia score make the targeting of p53 and/or hypoxia related pathways a plausible personalized medicine option for this bladder cancer, particularly in combination with immunotherapy. Our data suggest a requirement for molecular profiling in bladder cancer to possibly select appropriate immune-checkpoint therapy.

BRAF mutation, selected miRNAs and genes expression in primary papillary thyroid carcinomas and local lymph node metastases

Mutations in cancer-related genes are now known to be accompanied by epigenetic events in carcinogenesis by modification of the regulatory pathways and expression of genes involved in the pathobiology. Such cancer-related mutations, miRNAs and gene expression may be promising molecular markers of the most common papillary thyroid carcinoma (PTC). However, there are limited data on their relationships. The aim of this study was to analyse the interactions between BRAF mutations, selected microRNAs (miR-21, miR-34a, miR-146b, and miR-9) and the expression of selected genes (LGALS3, NKX2–1, TACSTD2, TPO) involved in the pathogenesis of PTC. The study cohort included 60 primary papillary thyroid carcinomas (PTC) that were classified as classical (PTC/C; n=50) and invasive follicular variant (PTC/F; n=10), and 40 paired lymph node metastases (LNM). BRAF mutation status in primary and recurrent/persistent papillary thyroid carcinomas was determined. The mutation results were compared both between primary and metastatic cancer tissue, and between BRAF mutation status and selected genes and miRNA expression in primary PTC. Furthermore, miRNAs and gene expression were compared between primary PTCs and non-neoplastic tissue, and local lymph node metastatic tumor, respectively. All studied markers showed several significant mutual interactions and contexts. In conclusion, to the best our knowledge, this is the first integrated study of BRAF mutational status, the expression levels of mRNAs of selected genes and miRNAs in primary PTC, and paired LNM.

Association between KRAS and PIK3CA Mutations and Progesterone Resistance in Endometriotic Epithelial Cell Line.

Although endometriosis is a benign disease, it is associated with cancer-related gene mutations, such as KRAS or PIK3CA. Endometriosis is associated with elevated levels of inflammatory factors that cause severe pain. In a previous study, we demonstrated that KRAS or PIK3CA mutations are associated with the activation of cell proliferation, migration, and invasion in a patient-derived immortalized endometriotic cell line, HMOsisEC10. In this study, we investigated the effects of these mutations on progesterone resistance. Since the HMOsisEC10 had suppressed progesterone receptor (PR) expression, we transduced PR-B to HMOsisEc10 cell lines including KRAS mutant and PIK3CA mutant cell lines. We conducted a migration assay, invasion assay, and MTT assay using dienogest and medroxyprogestrone acetate. All cell lines showed progesterone sensitivity with or without mutations. Regarding inflammatory factors, real-time quantitative RT-PCR revealed that the KRAS mutation cell line exhibited no suppression of Cox-2 and mPGES-1 on progesterone treatment, whereas IL-6, MCP-1, VEGF, and CYP19A1 were significantly suppressed by progesterone in both mutated cell lines. Our results suggest that KRAS mutation and PIK3CA mutation in endometriotic cells may not be associated with progesterone resistance in terms of aggressiveness. However, KRAS mutations may be associated with progesterone resistance in the context of pain.

Natural History of Germline BRCA1 Mutated and BRCA Wild-type Triple-negative Breast Cancer.

In germline BRCA1 mutated and BRCA wild-type patients, TNBC shows a branching evolutionary pattern of mutations with a single founding clone, are polyclonal throughout their disease course, and have widespread copy-number aberrations. This evolutionary pattern may be associated with treatment resistance or sensitivity and could be therapeutically exploited.

Comparative Evaluation of Machine Learning Models for Subtyping Triple-Negative Breast Cancer: A Deep Learning-Based Multi-Omics Data Integration Approach.

Objective: Triple-negative breast cancer (TNBC) poses significant diagnostic challenges due to its aggressive nature. This research develops an innovative deep learning (DL) model based on the latest multi-omics data to enhance the accuracy of TNBC subtype and prognosis prediction. The study focuses on addressing the constraints of prior studies by showcasing a model with substantial advancements in data integration, statistical performance, and algorithmic optimization. Methods: Breast cancer-related molecular characteristic data, including mRNA, miRNA, gene mutations, DNA methylation, and magnetic resonance imaging (MRI) images, were retrieved from the TCGA and TCIA databases. This study not only compared single-omics with multi-omics machine learning models but also applied Bayesian optimization to innovatively optimize the neural network structure of a DL model for multi-omics data. Results: The DL model for multi-omics data significantly outperformed single-omics models in subtype prediction, achieving a 98.0% accuracy in cross-validation, 97.0% in the validation set, and 91.0% in an external test set. Additionally, the MRI radiomics model showed promising performance, especially with the training set; however, a decrease in performance during transfer testing underscored the advantages of the DL model for multi-omics data in data consistency and digital processing. Conclusion: Our multi-omics DL model presents notable innovations in statistical performance and transfer learning capability, bearing significant clinical relevance for TNBC classification and prognosis prediction. While the MRI radiomics model proved effective, it requires further optimization for cross-dataset application to enhance accuracy and consistency. Our findings offer new insights into improving TNBC classification and prognosis through multi-omics data and DL algorithms.

Genomic Alterations Correlated to Trastuzumab Resistance and Clinical Outcomes in HER2+/HR- Breast Cancers of Patients Living in Northwestern China.

Anti-HER2 therapy has significantly improved the survival rates of patients with HER2+ breast cancer. However, a subset of these patients eventually experience treatment failure, and the underlying genetic mechanisms remain largely unexplored. This underscores the need to investigate the genomic heterogeneity of HER2+ breast cancer. In this study, we focus on HER2+/HR- breast cancer, as it differs from HER2+/HR+ breast cancer in terms of genetic and biological characteristics. We performed gene-targeted genome sequencing on 45 HER2+/HR- breast cancer samples and identified 650 mutations across 268 cancer-related genes. TP53 (71.1%) and PIK3CA (35.6%) were the most frequently mutated genes in our sample. Additionally, ERBB2 (77.8%), CDK12 (42.2%), and MYC (11.1%) exhibited a high frequency of copy number amplifications (CNAs). Comparative analysis with two other HER2+/HR- breast cancer cohorts revealed that our cohort had higher genetic variation rates in ARID1A, PKHD1, PTPN13, FANCA, SETD2, BRCA2, BLM, STAG2, FAT1, TOP2A, POLE, ATM, KMT2B, FGFR4, and EPAS1. Notably, in our cohort, NF1 and ATM mutations were more prevalent in trastuzumab-resistant patients (NF1, p=0.016; ATM, p=0.006) and were associated with primary trastuzumab resistance (NF1, p=0.042; ATM, p=0.021). Moreover, patients with NF1 mutations (p=0.009) and high histological grades (p=0.028) were more likely to experience early relapse. Ultimately, we identified a unique cancer-related gene mutation profile and a subset of genes associated with primary resistance to trastuzumab and RFS in patients with HER2+/HR- breast cancer in Northwest China. These findings could lay the groundwork for future studies aimed at elucidating the mechanisms of resistance to trastuzumab and improving HER2-targeted treatment strategies.

Impact of Mutations in Blood Cancer-Related Genes on Clinical Outcomes in Chronic Myeloid Leukemia in Chronic Phase (CML-CP) after ≥2 Tyrosine Kinase Inhibitors (TKIs) in the Ascembl Trial

CONCLUSIONS Somatic mutations in blood cancer-related genes are commonly detected in CML-AP. The most frequently mutated genes are RUNX1, ASXL1IKZF1 (submicroscopic deletions), and BCR:: ABL1 (kinase domain mutations). ASXL1 is the most frequently detected mutation at CML diagnosis (≈9%). However, the incidence and impact of mutations in blood cancer-related genes in patients (pts) with CML-CP previously treated with ≥2 TKIs have not been described since genomic studies have focused on pts at diagnosis or at progression. With &amp;gt;2 years of follow-up in the phase 3 ASCEMBL study, asciminib (ASC) has continued to demonstrate superior efficacy vs bosutinib (BOS) in pts with CML-CP after ≥2 prior TKIs, and analysis of cancer gene somatic mutations in this population has the potential to reveal additional insights into pts' response to study treatments or characteristics of the disease in later lines of therapy. Here we present a descriptive analysis of variants in the ASCEMBL pt population, including frequencies, co-occurrences, and association of mutations with clinical outcomes, specifically major molecular response (MMR) and treatment failure (TF; defined as discontinuation due to lack of efficacy or intolerance). Adults with CML-CP previously treated with ≥2 TKIs with intolerance of their last TKI or lack of efficacy per 2013 European LeukemiaNet recommendations and without BCR:: ABL1 T315I or V299L mutations were randomized 2:1 to ASC 40 mg twice daily or BOS 500 mg once daily. DNA was isolated from blood collected at baseline (BL) and end of treatment (EOT; defined as treatment discontinuation for any reason or completion of the study). A next-generation sequencing panel of 89 commonly mutated genes in blood cancers, including ABL1 and IKZF1 deletion, was used to detect somatic mutations that met criteria for pathogenicity. Only samples with BCR::ABL1IS ≥2%, which was the level demonstrated to detect mutations in leukemic cells, were tested. A multivariable Cox proportional hazards regression model adjusted for age, sex, treatment, and reason for prior TKI discontinuation (intolerance vs lack of efficacy) was used to determine the prognostic value of BL mutations. A total of 233 pts were randomized to ASC (n=157) or BOS (n=76). Of 162 pts (ASC, n=110; BOS, n=52) with available sequencing data at BL, 102 had ≥1 mutation: 69 (63%) on ASC and 33 (63%) on BOS. Overall, 159 mutations were detected in 23 genes at BL, ranging from 0 to 5 per pt. The median variant allele frequency (VAF) was 19.6% (range, 0.9%-58%). ASXL1 (in 31% of pts) and ABL1 kinase domain (in 17% of pts) mutations were the most frequently detected. Of 27 pts with ≥1 ABL1 mutation at BL, 85% had ≥1 other mutated cancer gene. Co-occurrence of ASXL1 and ABL1 mutations at BL was reported in 12 of 162 pts (7.4%), which was higher than the expected 2.9% based on these genes' individual frequencies in this data set. RUNX1 and IKZF1 mutations were rare in CML-CP at BL. Of 162 pts tested at BL, 73 had TF and available samples for analysis at EOT with only 3 pts discontinuing due to disease progression. The presence of any mutation at BL was significantly prognostic of TF in the total cohort of 162 pts (Figure 1). In an unadjusted analysis, the presence of an ASXL1 mutation with VAF &amp;gt;5% at BL was a prognostic factor of TF. In 73 pts with TF, most BL mutations were also detected at EOT (110/116 mutations in 48/54 carriers) (Figure 2). Of 15 pts who acquired ≥1 mutation at EOT, 9 acquired ABL1 mutations. No single mutations at an individual or gene level were prognostic of MMR. Mutations were not predictive of MMR or TF when pts were examined by their assigned treatment of ASC or BOS. ASXL1 mutations are most frequently detected at CML diagnosis and were enriched at BL in this study of pts with CML-CP previously treated with ≥2 TKIs, which is consistent with a role in TKI resistance. RUNX1 and IKZF1 mutations, which are associated with progression to accelerated or blast phase in CML, were very rare in this pt population, supporting their role in CML disease progression. The high frequency of co-occurrence of BCR:: ABL1 mutations and blood cancer gene mutations in CML-CP is an important finding since cancer gene mutations could modify response to TKIs in individual pts. The presence of any somatic blood cancer mutation at BL was prognostic of TF. These mutations may serve as potential biomarkers that can identify pts who may be at higher risk of TF in later lines of therapy.

Somatic Mutations in Cancer-Related Genes Were Observed More Frequently in AYA CML Patients Compared to Elderly at Diagnosis, Whereas the Frequency Was Markedly Higher in Elderly Patients during TKI Treatment

CONCLUSIONS Several works showed that patients with chronic myeloid leukemia (CML) diagnosed at the age of 18 to 39 years (adolescent and young adults, AYAs), had a worse outcome of tyrosine kinase inhibitors (TKI) therapy compared to elderly patients. Only limited data on the molecular background differing AYA from the other age groups are available. To characterize the somatic mutation landscape of AYA CML patients in chronic phase at the time of diagnosis and follow-up in comparison to pediatric and elderly patients, and to follow their clonal evolution. Ph-positive acute lymphoblastic leukemia (Ph+ ALL) patients were included for comparison. Samples from the time of diagnosis (CML children N=18; AYA N=69; elderly N=70; Ph+ ALL children N=32, AYA N=13, elderly N=39) and TKI treatment follow-up (CML AYA N=69, elderly N=70) were analyzed with custom panel (22 whole genes, 40 selected exons). To follow the clonal evolution vital cells available from 10 CML patients were FACS sorted into populations of neutrophils, monocytes, T- and B-lymphocytes. Genomic BCR::ABL1 (g BCR::ABL1) and mutations were quantified using ddPCR in the sorted cells. At the time of diagnosis, a slightly higher frequency of somatic mutations was detected in AYA CML patients (28%, 19/69) compared to elderly (20%, 14/70) and children (11%, 2/18). The similar trend with markedly higher differences was observed in Ph+ ALL patients (62% 8/13 of AYA, 31% 12/39 of elderly, 22% 7/32 of pediatric). The most frequently mutated genes in AYA and elderly CML patients were identically ASXL1, DNMT3A, and TET2. Other mutated genes in AYA were FBXW7, IDH2, IKZF1 PHF6 and KDM6A, SETD2, SF3B1 in elderly. Considering the treatment response, a higher number of mutations at diagnosis were found in the AYA patients that responded optimally in follow-up (21%, 7/33) than in elderly 4% (1/26) and a slightly higher frequency of mutations in AYA patients who later failed on TKI (35%, 8/23) than in elderly 30% (13/43). In contrary, the frequency of acquired mutations or persisted mutations from diagnosis detected during TKI therapy was higher in elderly that failed on TKI therapy (67%, 29/43) than in AYA (52%, 12/23). The treatment failure was associated with de novo mutations in ABL1, RUNX1, TET2, ASXL1 in AYA and elderly CML patients, and in addition in IKZF1, and in DNMT3A, WT1, JAK2, respectively. Sorted cells were analyzed from the time of optimal response in 7 CML patients (+ diagnostic sample of 2 patients) with mutated ASXL1 in 6 patients, FBXW7 in 1 patient, DNMT3A in 1 patient and IDH2 in 1 patient. Samples from the time of therapy failure were available for sorting of 3 patients (+ diagnostic sample of 1 patient). All mutations were detected in g BCR::ABL1 positive neutrophiles and monocytes. The g BCR::ABL1 levels matched exactly with the levels of mutations except for 1 patient with ASXL1-mutated subclone (VAF 5%), which was found in g BCR::ABL1 positive cells. Similar data were found in patients with therapy failure. However, in one patient with secondary failure, the ASXL1 mutation detected at diagnosis disappeared. In all 10 CML patients, g BCR::ABL1 and mutations were not detected in T- and B- lymphocytes under the therapy. In diagnostic samples some g BCR::ABL1 and mutations positive T- and B- lymphocytes were found, but the levels were 3-4 log lower compared to levels in neutrophils and monocytes, which likely correspond to the contamination (purity check was done after sorting) than to the presence of a very small subset of physiological lymphoid cells. Of all age groups, AYAs had the highest number of mutations detected at the time of diagnosis with differences in the spectrum between CML and Ph+ ALL. A markedly higher de novo acquisition of mutations was observed in elderly CML patients during TKI treatment. Moreover, therapy failures were observed more frequently in elderly than in AYA CML patients. Clonal analysis of 10 CML patients outlined that myeloid, but not lymphoid stem/progenitor cells were mutated. Supported by MZCR NU21-07-00225

NOTCH1 and CREBBP co-mutations negatively affect the benefit of adjuvant therapy in completely resected EGFR-mutated NSCLC: translational research of phase III IMPACT study.

The phase III IMPACT study (UMIN000044738) compared adjuvant gefitinib with cisplatin plus vinorelbine (cis/vin) in completely resected epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC). Although the primary endpoint of disease-free survival (DFS) was not met, we searched for molecular predictors of adjuvant gefitinib efficacy. Of 234 patients enrolled in the IMPACT study, 202 patients were analyzed for 409 cancer-related gene mutations and tumor mutation burden using resected lung cancer specimens. Frequent somatic mutations included tumor protein p53 (TP53; 58.4%), CUB and Sushi multiple domains 3 (CSMD3; 11.8%), and NOTCH1 (9.9%). Multivariate analysis showed that NOTCH1 co-mutation was a significant poor prognostic factor for overall survival (OS) in the gefitinib group and cAMP response element binding protein (CREBBP) co-mutation for DFS and OS in the cis/vin group. In patients with NOTCH1 co-mutations, gefitinib group had a shorter OS than cis/vin group (Hazard ratio 5.49, 95% CI 1.07-28.00), with a significant interaction (P for interaction = 0.039). In patients with CREBBP co-mutations, the gefitinib group had a longer DFS than the cis/vin group, with a significant interaction (P for interaction = 0.058). In completely resected EGFR-mutated NSCLC, NOTCH1 and CREBBP mutations might predict poor outcome in patients treated with gefitinib and cis/vin, respectively.

BRAF V600E mutation co-existing with oncogenic mutations is associated with aggressive clinicopathologic features and poor prognosis in papillary thyroid carcinoma

BackgroundThe aim of this study was to evaluate the correlation among mutations in cancer-related genes, clinicopathologic features, and clinical outcome in classical papillary thyroid carcinoma (PTC). Patients and methodsA total of 130 patients with classical PTC who underwent curative surgery between April 2012 and June 2023 at Hokuto Hospital were included. Mutations in targeted regions of 160 cancer-related genes were detected by next-generation sequencing (NGS)-based cancer panel testing. ResultsThe BRAF V600E mutation was detected in 108 (83.1%) of 130 PTC patients. Among the 108 patients with the BRAF V600E mutation, other co-existing oncogenic mutations were found in 12 (9.2%) patients. When we divided into 3 groups of no mutations, BRAF V600E mutation alone, and BRAF V600E and other oncogenic mutations, significant differences were observed in terms of tracheal invasion (P = 0.0024), and bilateral neck lymph node metastasis (P = 0.0047). Kaplan–Meier analysis of overall survival (OS) revealed patients with BRAF V600E and other oncogenic mutations had significantly poorer survival than those with BRAF V600E mutation alone (P = 0.0026). Multivariate cox proportional hazard analysis revealed BRAF V600E and other oncogenic mutations was an independent prognostic factor for OS (HR: 10.559; 95%CI: 1.007-110.656, P = 0.0493). ConclusionsThe BRAF V600E mutation co-existing with other oncogenic mutations but not the BRAF V600E mutation alone was associated with aggressive clinicopathologic features, resulting in poor prognosis in patients with classical PTC. Detection of oncogenic mutations using NGS-based cancer panel testing could enhance understanding of the clinical features of classical PTC.

Prospects and challenges of CRISPR/Cas9 gene-editing technology in cancer research.

Cancer, one of the leading causes of death, usually commences and progresses as a result of a series of gene mutations and dysregulation of expression. With the development of clustered regularly interspaced palindromic repeat (CRISPR)/Cas9 gene-editing technology, it is possible to edit and then decode the functions of cancer-related gene mutations, markedly advance the research of biological mechanisms and treatment of cancer. This review summarizes the mechanism and development of CRISPR/Cas9 gene-editing technology in recent years and describes its potential application in cancer-related research, such as the establishment of human tumor disease models, gene therapy and immunotherapy. The challenges and future development directions are highlighted to provide a reference for exploring pathological mechanisms and potential treatment protocols of cancer.

Genetic Landscape of Chronic Myeloid Leukemia and a Novel Targeted Drug for Overcoming Resistance.

Tyrosine kinase inhibitors (TKIs) exemplify the success of molecular targeted therapy for chronic myeloid leukemia (CML). However, some patients do not respond to TKI therapy. Mutations in the kinase domain of BCR::ABL1 are the most extensively studied mechanism of TKI resistance in CML, but BCR::ABL1-independent mechanisms are involved in some cases. There are two known types of mechanisms that contribute to resistance: mutations in known cancer-related genes; and Philadelphia-associated rearrangements, a novel mechanism of genomic heterogeneity that occurs at the time of the Philadelphia chromosome formation. Most chronic-phase and accelerated-phase CML patients who were treated with the third-generation TKI for drug resistance harbored one or more cancer gene mutations. Cancer gene mutations and additional chromosomal abnormalities were found to be independently associated with progression-free survival. The novel agent asciminib specifically inhibits the ABL myristoyl pocket (STAMP) and shows better efficacy and less toxicity than other TKIs due to its high target specificity. In the future, pooled analyses of various studies should address whether additional genetic analyses could guide risk-adapted therapy and lead to a final cure for CML.

How can cancer research be illuminated by brain research (and vice versa)?

Cancer and brain research have historically followed concrete pathways and converged mostly to studying brain cancer. Nowadays, the fields of neuro-oncology and neuroendocrine regulation of tumorigenesis are both emerging fields of intense research and promising applications. An increasing body of evidence suggests that somatic mutations in cancer-related genes are prevalent in several noncancerous brain disorders. These findings highlighting that certain aspects of cancer development/progression and pathologies of the nervous system share molecular alterations, could assist in elucidating the unique hallmarks of cancer and in cancer drugs repurposing for brain disorders. In so doing, identifying the commonalities in these conditions could be crucial not only for better understanding the basis of these pathologies but also for considering the previously underappreciated and/or neglected possibility of using drugs known to be effective in one type of pathology for the other type.

Genetic testing outcomes and pathogenic germline mutation prevalence in renal cell carcinoma.

10601 Background: Germline mutations have been observed in renal cell carcinoma (RCC) with varying frequencies reported from 5% to 18% of patients. Due to the prevalence of germline mutations, current guidelines by the National Comprehensive Cancer Network (NCCN) recommend genetic testing for patients with RCC and high-risk factors such as young age, bilateral or multifocal tumors, family history of RCC, as well as certain RCC histologies. However, the germline mutational landscape in RCC has not been fully characterized. Here, we report the genetic testing results and clinicopathologic factors of patients with RCC who were referred for germline testing. Methods: All patients with a diagnosis code of kidney cancer and referred to the Cancer Genetics clinic at the University of Michigan between 2004 and 2022 were identified. Patients were excluded if they had erroneous RCC diagnosis codes, no history of RCC diagnosis, known familial/hereditary mutation or syndrome, or did not undergo germline testing. Genetic testing outcomes, germline mutation frequency, and clinical factors were obtained through chart review and analyzed using descriptive statistics. Results: A total of 322 patients with a history of RCC and referred for genetic testing were identified. The median age at diagnosis in all patients was 47 (interquartile range: 38-58). Males accounted for 56.8% of the cohort. Most patients (62.4%) had clear cell histology at initial diagnosis, whereas 30.7% had non-clear cell histology. The majority of patients (61.5%) were diagnosed at stage 1. Bilateral and multifocal tumors at diagnosis accounted for 18.9% and 12.7%, respectively. Pathogenic or likely pathogenic variants (P/LP) were identified in 43 patients (13.4%); 225 patients had negative germline testing (69.9%); 54 patients (16.8%) had a variant of unknown significance (VUS). The most frequently mutated RCC-associated genes were FLCN (n=10, 3.1%), SDHA/B/D (n=7, 2.2%), VHL (n=4, 1.2%), MLH1 (n=3, 0.9%), and FH (n=2, 0.6%). Common mutations in other cancer-related genes were CHEK2 (n=4, 1.2%), ATM (n=2, 0.6%), and RAD50 (n=2, 0.6%). Most patients (81.4%) with a P/LP test result had at least 1 of the following: diagnosis age ≤ 46 years, bilateral or multifocal tumors, or at least 1 first-degree relative with RCC. Out of the patients with a P/LP result, 18 patients (39.1%) had a potentially actionable mutation. Conclusions: Among patients with RCC who were unselected for a known familial/hereditary predisposition, P/LP variants were present in 13.4% which is consistent with previous studies. The prevalence of FLCN mutations was higher in our cohort (3.1%) compared to prior observations. Most patients with a P/LP variant met the NCCN criteria for genetic testing. Future studies should optimize the current genetic testing criteria to identify a broader group of patients who may have germline mutations given potential cascade testing and therapeutic implications.