Citations

Multigene panel testing has allowed for the detection of a growing number of inherited pathogenic/likely pathogenic variants in people at high risk of cancer, including endometrial cancer (EC). Hereditary syndromes associated with EC include Lynch syndrome, PTEN hamartoma tumor syndrome, and Peutz-Jeghers syndrome. This manuscript provides the latest recommendations from the NCCN Guidelines for Genetic/Familial High-Risk Assessment: Colorectal, Endometrial, and Gastric on the screening and management of EC in patients at high risk for these syndromes, as well as the advantages and limitations of multigene panel testing. This manuscript also describes recent updates to these guidelines regarding de-implementation of colon cancer screening in individuals with CHEK2 pathogenic/likely pathogenic variants, based on the most up-to-date evidence regarding the association between CHEK2 pathogenic/likely pathogenic variants and colon cancer risk.

Abstract The interactions between transcription factors (TFs) and the target genes could provide a basis for constructing gene regulatory networks (GRNs) for mechanistic understanding of various biological complex processes. From gene expression data, particularly single-cell transcriptomic data containing rich cell-to-cell variations, it is highly desirable to infer TF–gene interactions (TGIs) using deep learning technologies. Numerous models or software including deep learning–based algorithms have been designed to identify transcriptional regulatory relationships between TFs and the downstream genes. However, these methods do not significantly improve predictions of TGIs due to some limitations regarding constructing underlying interactive structures linking regulatory components. In this study, we introduce a deep learning framework, DeepTGI, that encodes gene expression profiles from single-cell and/or bulk transcriptomic data and predicts TGIs with high accuracy. Our approach could fuse the features extracted from Auto-encoder with self-attention mechanism and other networks and could transform multihead attention modules to define representative features. By comparing it with other models or methods, DeepTGI exhibits its superiority to identify more potential TGIs and to reconstruct the GRNs and, therefore, could provide broader perspectives for discovery of more biological meaningful TGIs and for understanding transcriptional gene regulatory mechanisms.

ABSTRACT The alpha 1 and 2 chains of type IV collagen, encoded by the COL4A1 (MIM 120130) and COL4A2 (MIM 120090) respectively, play essential roles in the vascular basement membranes. Pathogenic variants in COL4A1 / COL4A2 are associated with autosomal dominant cerebral angiopathies. The clinical manifestations of COL4A1 / COL4A2 ‐related disorders include: aneurysms, intracerebral hemorrhage, polymicrogyria, porencephaly, heterotopia, periventricular leukomalacia, epilepsy, and neurodevelopmental disorders. COL4A1 pathogenic variants that are in exons 24 and 25 have been associated with hereditary angiopathy, nephropathy, aneurysms, and cramps. The multisystemic phenotypes of COL4A1 / COL4A2 ‐related disorders are increasingly being studied. Animal models have suggested that COL4A2 ‐related disorders may also manifest with a variable combination of multisystemic abnormalities affecting the eyes, muscles, and kidneys. Okano and colleagues recently reported a case of recurrent episodes of rhabdomyolysis in a 2‐year‐old with COL4A1 ‐related disorder raising fundamental questions on mechanisms of COL4A1 / COL4A2 variants in muscle homeostasis. To date, rhabdomyolysis has not been associated with COL4A2 ‐related disorder in humans. Rhabdomyolysis is a medical emergency, where there is elevated creatine kinase (CK) level in the blood and increased excretion of myoglobin in urine, due to skeletal muscle damage and release of intracytoplasmic proteins into systemic circulation. Rhabdomyolysis is a serious medical condition. It require intensive care management due to an increased risk of some life‐threatening complications [including disseminated intravascular coagulation, renal failure, and severe hyperkalemia]. Herein, we report a case of rhabdomyolysis in an adult with COL4A2 ‐related structural brain malformations (including polymicrogyria and heterotopia).

Abstract Motivated by studies showing an association between beta blocker (BB) use and positive bone outcomes, a pilot randomized control trial was performed at the Mayo Clinic which randomized postmenopausal women to placebo, propranolol (40 or 80 mg twice daily), atenolol (50 mg/d), or nebivolol (5 mg/d) to determine changes in bone turnover markers (BTMs) and in BMD over 20 wk. Pharmacogenetic effects and microRNA-mediated mechanisms involving beta adrenergic receptor and related genes have previously been found. We sought to validate these effects and discover new candidates in an ancillary study to the pilot clinical trial. We genotyped all participants and performed microRNA (miRNA) sequencing at baseline and at 20 wk for 24 participants from the atenolol or placebo groups. We discovered several variants in ADRB1, ADRB2, and HDAC4 which showed significant pharmacogenetic effects with BMD at multiple sites and with BTMs. Our miRNA results showed a significant treatment effect for miR-19a-3p over time with atenolol use in the low-responder group compared to placebo. Overall, the longitudinal miRNA analysis showed a large number of miRNAs which were up-regulated over the trial in the low responders but not the high responders compared to placebo, of which miR-19a-3p was one example. Finally, we compared the response to atenolol treatment for cardiovascular traits (pulse and blood pressure) with the response for the bone resorption marker, C-terminal telopeptide, and found a largely independent effect. Our results have implications for personalized therapy and for understanding mechanisms of BB treatment effect on bone.

Abstract Chemotherapy regimens for triple-negative breast cancer (TNBC) combine agents without knowing which agents drive response. Consequently, predictors derived from multi-agent regimens cannot be assumed to generalize to individual drugs or other regimens, motivating development of treatment-matched predictors. Here, we used TNBC patient-derived xenografts (PDXs) treated with carboplatin, docetaxel, or the combination to deconvolute drug-specific responses and identify associated molecular features. Combination treatment rarely improved upon the best single agent, with enhanced responses in only 13% of PDXs and antagonism in a comparable fraction. Proteogenomic analyses identified high cytokeratin-5 (KRT5) as a general marker of chemotherapy responsiveness and KRT5 immunohistochemistry discriminated responsive PDXs (AUROC, 0.83). To train treatment-specific predictors, we integrated these data with independent PDX and clinical cohorts with responses assessed after anthracycline-free platinum, taxane, or platinum-taxane therapy, ensuring response corresponded to the modeled treatment. Four feature selection strategies yielded largely nonoverlapping biomarker panels converging on treatment-relevant pathways. On independent test data, RNA-based predictors of complete response (CR) to platinum-based (carboplatin or cisplatin) and taxane-based (docetaxel or paclitaxel) chemotherapy achieved AUROCs of 0.80 and 0.86, respectively. For platinum-taxane regimens (carboplatin plus docetaxel or paclitaxel), proteomic-guided feature selection generated a 10-biomarker, protein- informed RNA predictor of pathologic complete response (pCR) that outperformed RNA-only feature selection and achieved an AUROC of 0.85 in an independent clinical cohort, while retaining practicality as an RNA-based assay. Treatment-matched integration of multi-omic PDX and clinical datasets provides a framework for chemotherapy-specific predictors with clinically relevant performance, supporting biomarker-guided precision selection and treatment optimization for patients with TNBC. Statement of significance Integration of multi-omic data from patient-derived xenografts with treatment-matched clinical cohorts yielded three retrospectively validated predictors of platinum, taxane, and platinum+taxane response, enabling biomarker-guided chemotherapy selection for patients with triple-negative breast cancer.

Abstract Objectives Fluorescence resonance energy transfer (FRET)–based ADAMTS13 activity assays are critical for the diagnosis of thrombotic thrombocytopenic purpura. However, these assays are susceptible to interference. As iodide has been suggested to interfere in laboratory testing via fluorophore quenching or promotion, we aimed to determine whether iodinated contrast (Omnipaque) interferes with the ATS-13 ADAMTS13 Activity Assay 2.0. Methods We evaluated the excitation, emission, and absorbance spectrum of Omnipaque alone and spiked in patient plasma with known ADAMTS13 activity and ADAMTS13 activity on Omnipaque alone, an abnormal control of patient plasma previously observed to display elevated baseline relative fluorescent units, and variable concentrations of patient plasma with known ADAMTS13 activity spiked with Omnipaque. Results No atypical fluorescent peaks were observed on any sample (Omnipaque alone or spiked in plasma) between 250 and 700 nm. There was no difference in the mean ADAMTS13 activity among the various concentrations of plasma spiked with Omnipaque or plasma spiked with saline. Conclusions Iodinated contrast does not appear to interfere—either via spectral overlap of the fluorophore or through physiologic inhibition of the ADAMTS13 enzyme—with ADAMTS13 activity FRET-based assays based on the findings from this in vitro analysis. Delaying sample collection for ADAMTS13 activity testing from suspected patients with thrombotic thrombocytopenic purpura following administration of iodinated radiocontrast agents is not necessary, and recent contrast administration should not yield erroneous ADAMTS13 activity results.

Background/Objectives: Lung cancer is a devastating disease with the highest mortality rate among cancer types. Over 60% of non-small cell lung cancer (NSCLC) patients, accounting for 87% of lung cancer diagnoses, require radiation therapy. Rapid treatment initiation significantly increases the patient’s survival rate and reduces the mortality rate. Accurate tumor segmentation is a critical step in diagnosing and treating NSCLC. Manual segmentation is time- and labor-consuming and causes delays in treatment initiation. Although many lung nodule detection methods, including deep learning-based models, have been proposed. Most of these methods still have a long-standing problem of high false positives (FPs). Methods: Here, we developed an electronic health record (EHR)-guided lung tumor auto-segmentation called EXACT-Net (EHR-enhanced eXACtitude in Tumor segmentation), where the extracted information from EHRs using a pre-trained large language model (LLM) was used to remove the FPs and keep the TP nodules only. Results: The auto-segmentation model was trained on NSCLC patients’ computed tomography (CT), and the pre-trained LLM was used with the zero-shot learning approach. Our approach resulted in a 250% boost in successful nodule detection using the data from ten NSCLC patients treated in our institution. Conclusions: We demonstrated that combining vision-language information in EXACT-Net multi-modal AI framework greatly enhances the performance of vision only models, paving the road to multimodal AI framework for medical image processing.

Background: The BeatAML Master Trial (BAMT) began in 2016 with a goal of determining the feasibility of a precision-medicine approach in treating acute myeloid leukemia (AML) in older adults ≥ 60 years of age where outcomes are poor. At the time, standard of care (SOC) for older patients with AML was intensive 7+3 chemotherapy (cytarabine + daunorubicin) if fit and hypomethylating agents (HMA: azacitidine or decitabine) if unfit. Besides confirming the feasibility, the early results (2019) from the Master Trial suggested that patients who received therapy on one of the sub-studies had a lower early death rate and superior overall survival compared to patients receiving off-protocol SOC, which was primarily single-agent HMA at the time. Since then, the 2019 approval of venetoclax (ven) + azacitidine for older unfit AML patients has been transformative and emerged as the SOC. Using data from the BAMT from 2016-2024, we suggest that knowing the comprehensive genomic profile of AML at the time of diagnosis is still beneficial in determining therapy that would lead to the optimal outcome and that development of targeted therapies and combination regimens with ven/HMA is still needed. Methods: This is a retrospective analysis of 1096 patients who consented and enrolled on the BAMT (NCT03013998) from Nov 2016 through Jun 2024. Patients ≥ 60 years with newly diagnosed AML were included. Patients underwent therapy on a BeatAML sub-study based on their genetics (N=433) or treatment off-protocol (N=663). We divided the patients according to what therapy they received: (1) Non-Intensive (Off-Protocol, N=121), (2) Ven/HMA (Off-Protocol, N=234), (3) Non-Intensive (Sub-Study, N=407), (4) Intensive (Sub-Study, N=26), and (5) Intensive (Off-Protocol, N=155). 94 patients received no treatment and 59 were unknown. Non-intensive therapies included primarily targeted agents or non-ven combinations. We analyzed baseline characteristics and demographics, overall survival (OS), and the impact of allogenic stem cell transplant (SCT). OS, using Kaplan-Meier method, was measured from the start of therapy to all-cause death, censoring patients at last follow-up. Results: Characteristics and demographics were similar between Groups 1, 2 and 3. Group 4 and 5 were treated with intensive chemotherapy and their characteristics are reflective of younger/fit patients appropriate for the intensive regimen. Groups 4 and 5 also had the longest median OS (mOS) of 40.2 months (95% CI: 13.9-not reached (NR)) and 42.3 months (95% CI: 25.1-NR) respectively. Group 3, which included patients treated with a non-intensive, targeted therapy on a sub-study, had an mOS of 14.0 months (95% CI: 12.3-16.7), which was similar to Group 2, treated with Ven/HMA, that had an mOS of 13.2 months (95% CI: 10.9-16.3). Lastly, patients in Group 1, who were treated primarily with HMA monotherapy, did poorly in comparison, with an mOS of 6.0 months (95% CI: 3.3-10.1). Additionally, we looked at the cumulative incidence rate (CIR) of SCT. The CIR in 12 months of Group 1 was 9.8% (95% CI: 6.9-13.4), Group 2: 5.4% (95% CI: 2.2-10.7), Group 3 and 4 combined: 35.0% (95% CI: 628.1-42.1), and Group 5: 13.1% (95% CI: 6.9-13.4). In a multi-variable analysis, after adjusting for typical favorable risk factors like NPM1 mutations and core binding factor, SCT was highly significant (p<0.0001) in improving OS with a hazard ratio of 0.23 (95% CI: 0.16-0.32), and Group 3 performed similarly to Group 2 (p=0.20). Conclusions: First, our results suggest that it is clinically relevant to correctly identify whether an intensive chemotherapy, targeted-therapy, or ven/HMA regimen is best suited for older AML patients, for which a precision-medicine trial is ideal for. Secondly, in this group of patients, our results show that patients treated with a non-intensive targeted therapy (Group 3) has a similar mOS to those treated with ven/HMA (Group 2). Especially after controlling for patient characteristics, patients in Group 2 performed similar to those in Group 3 (p=0.20). Patients in Group 3 were treated on Beat AML sub-studies which included targeted therapy alone or with non-venetoclax combinations, which is a strong rationale for continued development of targeted agents to optimize toxicity and quality of life with similar survival. Lastly, this data also supports the need to improve the ven/HMA SOC by developing combination regimens with targeted agents to further improve outcomes.

Background: Mutations of isocitrate dehydrogenase (IDH) are recurrent in acute myeloid leukemia (AML) and the prevalence increases with age. The prognostic impact of IDH1 and IDH2 mutations remains controversial. IDH inhibitors are small molecules that bind within the IDH enzymatic active site, blocking aberrant 2-hydroxyglutarate production and inducing myeloid differentiation. While they can lead to differentiation syndrome, they generally have a more favorable side-effect profile, making them an attractive option for older patients. We aimed to describe the prevalence and prognostic impact of IDH mutations in newly diagnosed (ND) AML patients ≥ 60 years in a large cohort of patients treated on a Leukemia and Lymphoma Society-sponsored trial. Methods: We performed a retrospective observational analysis including patients ≥ 60 years with ND AML who were enrolled on the Beat AML clinical trial (NCT03013998) before May 10, 2023. Patients were treated with a variety of treatment regimens. Cytogenetic analysis and next-generation sequencing (FoundationOne®Heme) were obtained. Mutations were considered present at any detectable VAF. Cox proportional hazard models were used to describe the relative risk of each variable on death over time from the date of trial inclusion. Results: A total of 1023 patients with ND AML were identified. Patients had a median age of 72 (range 60-92) years and the majority were non-Hispanic White (83.2%), and male (57.6%). Ninety-nine (9.7%) patients were IDH1MUT, 193 (18.9%) patients were IDH2MUT including 10 (1.0%) patients with a co-occurring IDH1 and IDH2 gene mutations. Both IDH1MUT and IDH2MUT were associated with 2022 ELN favorable-risk (26.3% and 22.3% for IDH1 and IDH2 respectively, vs 15.5% overall (P<0.001)). IDH1MUT significantly co-occurred with DNMT3AMUT (42.4%), NPM1MUT (44.4%) and less frequently with TP53MUT (10.1%) (P<0.001 for all). IDH2MUT was associated with DNMT3AMUT (35.8%), NPM1MUT (31.1%), SRSF2MUT (38.3%), and less frequently with TET2MUT (6.7%) and TP53MUT (9.3%) (P<0.001 for all). Normal karyotype was higher in IDH1MUT (P<0.001) and IDH2MUT (P<0.001), whereas complex karyotype (P<0.001 for both) and core-binding factor AML (P=0.047, P=0.015) were lower in IDH1MUT and IDH2MUT. To evaluate the impact of IDH mutations in patients ≥ 60 years, we focused on patients evaluable for outcome treated with lower-intensity therapy (LIT) (N=674), and intensive chemotherapy (IC) (N=178), separately. Among the LIT treated patients, 96 patients received treatment with an IDH inhibitor, and 237 patients received a hypomethylating agent (HMA) plus venetoclax. For patients treated with LIT, the hazard ratios (HRs) of death over time were 0.58 [95% CI 0.47-0.72; P<0.002], 0.81 [95% CI 0.59-1.13; P=0.214] and 0.56 [95% CI 0.44-0.72; P<0.001] for IDHMUT, IDH1MUT, IDH2MUT respectively. Among patients receiving IC, the HRs were 1.05 [95% CI 0.68-1.69; P=0.777], 0.70 [95% CI 0.31-1.61; P=0.406] and 1.27 [95% CI 0.77-2.1; P=0.352] for IDHMUT, IDH1MUT, and IDH2MUT respectively. The HR of death for IDH1MUT patients treated with LIT with the addition of an IDH1 inhibitor (N=24) was significantly lower (HR 0.47 [95% CI 0.24-0.92; P=0.027] vs IDH1MUT patients treated without an IDH1 inhibitor, while an IDH2 inhibitor did not change survivial outcomes in patients with IDH2MUT (N=71). Discussion: To our knowledge this is the largest retrospective study characterizing the prevalence of IDH mutations in patients ≥ 60 years with AML. We demonstrated that IDH mutations were detected in ~27% of older patients with AML. Although there could have been selection bias as the Beat AML study had separate IDHMUT study arms, these findings are concordant with other studies showing an increase in frequency of IDH mutations with age. IDH2MUT was associated with a lower HR of death among patients treated with LIT, which was not seen in patients receiving IC. The high prevalence of IDH mutations suggests that IDH inhibitors used as single agents or in combination with lower-intensity therapies are an important class of drugs for this older patient population as they are generally well tolerated, that need further investigation.