Citations

Abstract TP53 aberrations, including mutations and deletion of 17p13, are important adverse prognostic markers in chronic lymphocytic leukemia (CLL) but are less studied in high count monoclonal B-cell lymphocytosis (HCMBL), an asymptomatic pre-malignant stage of CLL. Here we estimated the prevalence and impact of TP53 aberrations in 1,230 newly diagnosed treatment-naïve individuals (849 CLL, 381 HCMBL). We defined TP53 state as: wild-type (no TP53 mutations and normal 17p), single-hit (del(17p) or one TP53 mutation), or multi-hit (TP53 mutation and del(17p), TP53 mutation and loss of heterozygosity, or multiple TP53 mutations). Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for time to first treatment and overall survival by TP53 state. We found 64 (7.5%) CLL patients and 17 (4.5%) HCMBL individuals had TP53 mutations with variant allele fraction >10%. Del(17p) was present in 58 (6.8%) of CLL and 11 (2.9%) of HCMBL cases. Most individuals had wild-type (N=1,128, 91.7%) TP53 state, followed by multi-hit (N=55, 4.5%) and then single-hit (N=47, 3.8%) TP53 state. The risk of shorter time to therapy and death increased with the number of TP53 abnormalities. Compared to wild-type patients, multi-hit patients had 3-fold and single-hit patients had 1.5-fold increased risk of requiring therapy. Multi-hit patients also had 2.9-fold increased risk of death compared to wild-type. These results remained stable after accounting for other known poor prognostic factors. Both TP53 mutations and del(17p) may provide important prognostic information for HCMBL and CLL that would be missed if only one were measured.

Abstract PURPOSE To examine incremental values of estrogen receptor (ER) status, body mass index (BMI), menopausal status, and a previously reported multi-gene classifier over commonly used clinical factors (i.e. age, tumor grade, comedonecrosis, surgical margins, and treatment) in predicting risk of any ipsilateral recurrence (IR) event within five years after DCIS diagnosis. METHODS A derivation cohort consisted of participants in the Translational Breast Cancer Research Consortium (TBCRC) 038, a retrospective multicenter cohort study in women undergoing surgical resection for DCIS between 01/01/1998 and 02/29/2016 (n=216). The validation cohort, the Repository of Archival Human Breast Tissue (RAHBT) at Washington University School of Medicine, provided cases meeting the same eligibility criteria as TBCRC038 (n=97). Participants in both cohorts had RNA-seq data and either developed IR 1-5y after initial DCIS diagnosis or were free from subsequent breast events for at least five years. The previously reported 812-gene classifier had been developed from a subset of the TBCRC038 samples using a negative-binomial regression model to identify differentially expressed genes in the primary tumor associated with subsequent recurrence events. This classifier has been shown to be highly correlated with 5-year invasive, DCIS, and all breast cancer events, and validated in the RAHBT cohort. Cox proportional hazards regression was used to estimate hazard ratios (HRs) of IR in the TBCRC038 cohort (76 with IR). The clinical score was developed using clinical predictors (aforementioned clinical factors and ER) and their regression coefficients from the model with the maximum predictive accuracy (e.g. c-index) and the minimum number of predictors; the summary score integrated the clinical score and multi-gene classifier. Predictive performance of both clinical and summary scores was validated in the RAHBT cohort (20 with IR). RESULTS In the TBCRC cohort derivation set, we used a multivariable model based on clinical factors alone (clinical score) and found that ER status, but not BMI or menopausal status, was independently associated with a higher IR risk (HR=2.06, 95% CI 1.18-3.58). Adding the multi-gene classifier to the clinical factors-based model (summary score) in the TBCRC038 test set increased predictive accuracy (c-index 0.68 to 0.70), with the genomic classifier-adjusted HR of 14.96 (95% CI 8.64-25.91). The summary score had higher predictive performance for IR risk than clinical score alone (c-index 0.82 vs. 0.70). In the RAHBT validation samples, model performance was similarly improved using summary scores clinical factors-based model plus multigene classifier as compared to clinical scores along (c-index 0.74 vs. 0.58). CONCLUSION Combining clinical factors and a multigene classifier provided more accurate risk estimates of IR within five years after excision of DCIS than clinical factors alone. Figure 1. Observed and predicted recurrence-free survival in the first five years after initial DCIS diagnosis in the RAHBT validation cohort, by risk groups defined by clinical scores (left) and clinical score plus multigene classifier (right). Citation Format: Ying Liu, Siri H. Strand, Lorraine King, Bryan Harmon, Fergus J. Couch, Kristalyn Gallagher, Mark Kilgore, Shi Wei, Angela DeMichele, Tari King, Priscilla F. McAuliffe, Jeffrey Marks, Carlo Maley, Robert West, E Shelley Hwang, Graham A. Colditz. Using clinical characteristics and molecular markers to predict the risk of subsequent ipsilateral breast events after excision of DCIS [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-07-02.

Abstract Background Adjuvant abemaciclib (a CDK4 and 6 inhibitor) combined with ET resulted in significant and clinically meaningful improvement in invasive disease-free survival (IDFS) and distant relapse-free survival (DRFS) in patients (pts) with HR+, HER2-, node-positive, high risk EBC in the monarchE trial, and is an approved adjuvant therapy for these patients. Here we present efficacy results from a pre-specified overall survival interim analysis (OS IA2) which was planned to occur 2 years (yrs) after the primary outcome analysis. Methods Pts were randomized (1:1) to receive ET for up to 10 yrs +/- abemaciclib for 2 yrs (study treatment period). High-risk EBC was defined as either ≥4 positive axillary lymph nodes (ALN), or 1-3 ALN with either Grade 3 disease and/or tumor ≥5 cm (Cohort 1). While the proliferation biomarker Ki-67 was centrally assessed in all pts with available tissue sample, an additional smaller group of pts with 1-3+ ALN and central Ki-67 ≥20% as the only high-risk feature were included (Cohort 2). The intent-to-treat (ITT) population consisted of both Cohort 1 (5120 pts) and Cohort 2 (517 pts). Hazard ratios (HR) were estimated using Cox proportional hazard model. Results At a median follow-up of 42 months, all pts were off abemaciclib. IDFS and DRFS data illustrate a sustained benefit beyond the treatment period. In the ITT population, the HR for IDFS was 0.664 (95% CI: 0.578, 0.762) and DRFS was 0.659 (95% CI: 0.567, 0.767). At 4 yrs, this reflected an improvement in IDFS rates from 79.4% to 85.8% (absolute difference 6.4%), and in DRFS rates from 82.5% to 88.4% (absolute difference 5.9%). The continued separation of the curves was associated with an increase in absolute benefit in IDFS 4-year rates compared to 2-and 3-year IDFS rates (absolute difference 2.8% and 4.8% respectively). While OS remained immature, there was a lower number of deaths observed in the abemaciclib plus ET arm compared to the ET alone arm (157 [5.6%] vs 173 [6.1%], HR 0.929 [95% CI: 0.748, 1.153], p = 0.503), suggesting that the robust benefit in IDFS and DRFS began to translate into a numerically favorable OS HR. As previously described, within Cohort 1, a Ki-67 index of ≥20% was associated with a worse prognosis, but similar abemaciclib treatment effects were observed regardless of Ki-67 index. No new safety signals were observed. Conclusion The clinically meaningful benefit of adjuvant abemaciclib added to ET in HR+, HER2-, node-positive, high-risk EBC persists beyond completion of abemaciclib therapy, yielding an increase in absolute IDFS and DRFS benefit at 4 yrs. While OS remains immature at this time, the lower number of deaths in the abemaciclib arm compared to the ET arm suggest that a survival signal favoring abemaciclib is emerging. Citation Format: Stephen Johnston, Masakazu Toi, Joyce O’Shaughnessy, Priya Rastogi, Mario Campone, Patrick Neven, Chiun Sheng Huang, Jens Huober, Georgina Garnica Jaliffe, Irfan Cicin, Sara Tolaney, Matthew P. Goetz, Hope Rugo, Elżbieta Senkus, Laura Testa, Lucia Del Mastro, Chikako Shimizu, Ran Wei, Ashwin Shahir, Maria Munoz, Belen San Antonio, Valerie Andre, Nadia Harbeck, Miguel Martín. Abemaciclib plus endocrine therapy for HR+, HER2-, node-positive, high-risk early breast cancer: results from a pre-planned monarchE overall survival interim analysis, including 4-year efficacy outcomes [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS1-09.

The relationship between diabetes and coronavirus disease 2019 (COVID-19) is bidirectional: Although individuals with diabetes and high blood glucose (hyperglycemia) are predisposed to severe COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can also cause hyperglycemia and exacerbate underlying metabolic syndrome. Therefore, interventions capable of breaking the network of SARS-CoV-2 infection, hyperglycemia, and hyperinflammation, all factors that drive COVID-19 pathophysiology, are urgently needed. Here, we show that genetic ablation or pharmacological inhibition of mitochondrial pyruvate carrier (MPC) attenuates severe disease after influenza or SARS-CoV-2 pneumonia. MPC inhibition using a second-generation insulin sensitizer, MSDC-0602K (MSDC), dampened pulmonary inflammation and promoted lung recovery while concurrently reducing blood glucose levels and hyperlipidemia after viral pneumonia in obese mice. Mechanistically, MPC inhibition enhanced mitochondrial fitness and destabilized hypoxia-inducible factor–1α, leading to dampened virus-induced inflammatory responses in both murine and human lung macrophages. We further showed that MSDC enhanced responses to nirmatrelvir (the antiviral component of Paxlovid) to provide high levels of protection against severe host disease development after SARS-CoV-2 infection and suppressed cellular inflammation in human COVID-19 lung autopsies, demonstrating its translational potential for treating severe COVID-19. Collectively, we uncover a metabolic pathway that simultaneously modulates pulmonary inflammation, tissue recovery, and host metabolic health, presenting a synergistic therapeutic strategy to treat severe COVID-19, particularly in patients with underlying metabolic disease.

Radiation-induced brain injury (RIBI) is a debilitating sequela after radiotherapy to treat head and neck cancer, and 20 to 30% of patients with RIBI fail to respond to or have contraindications to the first-line treatments of bevacizumab and corticosteroids. Here, we reported a Simon’s minmax two-stage, single-arm, phase 2 clinical trial (NCT03208413) to assess the efficacy of thalidomide in patients with RIBI who were unresponsive to or had contraindications to bevacizumab and corticosteroid therapies. The trial met its primary endpoint, with 27 of 58 patients enrolled showing ≥25% reduction in the volume of cerebral edema on fluid-attenuated inversion recovery–magnetic resonance imaging (FLAIR-MRI) after treatment (overall response rate, 46.6%; 95% CI, 33.3 to 60.1%). Twenty-five (43.1%) patients demonstrated a clinical improvement based on the Late Effects Normal Tissues–Subjective, Objective, Management, Analytic (LENT/SOMA) scale, and 36 (62.1%) experienced cognitive improvement based on the Montreal Cognitive Assessment (MoCA) scores. In a mouse model of RIBI, thalidomide restored the blood-brain barrier and cerebral perfusion, which were attributed to the functional rescue of pericytes secondary to elevation of platelet-derived growth factor receptor β (PDGFRβ) expression by thalidomide. Our data thus demonstrate the therapeutic potential of thalidomide for the treatment of radiation-induced cerebral vasculature impairment.

Background: Long-QT syndrome (LQTS) is characterized by QT prolongation and increased risk for syncope, seizures, and sudden cardiac death. The majority of LQTS stems from pathogenic mutations in KCNQ1 , KCNH2 , or SCN5A . However, ≈10% of patients with LQTS remain genetically elusive. We utilized genome sequencing to identify a novel LQTS genetic substrate in a multigenerational genotype-negative LQTS pedigree. Methods: Genome sequencing was performed on 5 affected family members. Only rare nonsynonymous variants present in all affected family members were considered. The candidate variant was characterized functionally in patient-derived induced pluripotent stem cell and gene-edited, variant corrected, isogenic control induced pluripotent stem cell–derived cardiomyocytes. Results: A missense variant (p.G6S) was identified in ALG10B -encoded α-1,2-glucosyltransferase B protein. ALG10B (alpha-1,2-glucosyltransferase B protein) is a known interacting protein of KCNH2 -encoded K v 11.1 (HERG [human Ether-à-go-go–related gene]). Compared with isogenic control, ALG10B-p.G6S induced pluripotent stem cell–derived cardiomyocytes showed (1) decreased protein expression of ALG10B (p.G6S, 0.7±0.18, n=8 versus control, 1.25±0.16, n=9; P <0.05), (2) significant retention of HERG in the endoplasmic reticulum ( P <0.0005), and (3) a significantly prolonged action potential duration confirmed by both patch clamp (p.G6S, 531.1±38.3 ms, n=15 versus control, 324.1±21.8 ms, n=13; P <0.001) and multielectrode assay ( P <0.0001). Lumacaftor—a compound known to rescue HERG trafficking—shortened the pathologically prolonged action potential duration of ALG10B-p.G6S induced pluripotent stem cell–derived cardiomyocytes by 10.6% (n=31 electrodes; P <0.001). Conclusions: Here, we demonstrate that ALG10B-p.G6S downregulates ALG10B, resulting in defective HERG trafficking and action potential duration prolongation. Therefore, ALG10B is a novel LQTS-susceptibility gene underlying the LQTS phenotype observed in a multigenerational pedigree. ALG10B mutation analysis may be warranted, especially in genotype-negative patients with an LQT2-like phenotype.

Abstract Preclinical studies have shown augmented activity when combining Bruton tyrosine kinase inhibitors (BTKi) with inhibitors of mammalian target of rapamycin (mTOR) and immunomodulatory agents (IMiD). We conducted a phase 1, open‐label study at five centers in USA to evaluate the safety of triplet BTKi/mTOR/IMiD therapy. Eligible patients were adults aged 18 years or older with relapsed/refractory CLL, B cell NHL, or Hodgkin lymphoma. Our dose escalation study used an accelerated titration design and moved sequentially from single agent BTKi (DTRMWXHS‐12), doublet (DTRMWXHS‐12 + everolimus), and then to triplet therapy (DTRMWXHS‐12 + everolimus + pomalidomide). All drugs were dosed once daily on days 1–21 of each 28‐day cycle. The primary goal was to establish the recommended phase 2 dose of the triplet combination. Between September 27, 2016, and July 24, 2019, a total of 32 patients with a median age of 70 years (range 46 to 94 years) were enrolled. No MTD was identified for monotherapy and the doublet combination. The MTD for the triplet combination was determined to be DTRMWXHS‐12 200 mg + everolimus 5 mg + pomalidomide 2 mg. Responses across all studied cohorts were seen in 13 of 32 (41.9%). Combining DTRMWXHS‐12 with everolimus and pomalidomide is tolerable and shows clinical activity. Additional trials could confirm benefit of this all‐oral combination therapy for relapsed/refractory lymphomas.

AbstractBackground and ObjectivesThe impact upon wound healing of targeted molecular therapies, when incorporated into neoadjuvant therapy of soft tissue sarcoma, is largely unknown. Here, we describe wound complications following addition of pazopanib, a tyrosine kinase inhibitor (TKI), to neoadjuvant radiotherapy (RT) +/− chemotherapy for soft tissue sarcoma.MethodsWound complications were evaluated on dose‐finding and randomized arms of ARST1321, a phase II/III study incorporating neoadjuvant RT, +/− pazopanib, +/− ifosfamide/doxorubicin (ID) for sarcoma therapy.ResultsOf 85 evaluable patients, 35 (41%) experienced postoperative wound complications. Most (57%) were grade III. Randomization to pazopanib + RT + ID carried a 50% wound complication rate (17/34, with 47% grade III), compared to 22% (5/23) with ID + RT alone. In nonchemotherapy study arms, pazopanib + RT resulted in a 59% wound complication rate versus 25% for those receiving RT alone. Grade III wound complications occurred among 26% (15/58) of all patients receiving pazopanib. Wound complications occurred a median of 35 days postoperatively. Some occurred following diagnostic biopsies and at remote surgical sites.ConclusionThe addition of pazopanib to neoadjuvant chemotherapy and RT resulted in a higher wound complication rate following therapy of soft tissue sarcoma. The rate of grade III complications remained comparable to that reported in contemporary literature.

Abstract Prediction of the response of cancer patients to different treatments and identification of biomarkers of drug response are two major goals of individualized medicine. Here, we developed a deep learning framework called TINDL, completely trained on preclinical cancer cell lines (CCLs), to predict the response of cancer patients to different treatments. TINDL utilizes a tissue-informed normalization to account for the tissue type and cancer type of the tumors and to reduce the statistical discrepancies between CCLs and patient tumors. Moreover, by making the deep learning black box interpretable, this model identifies a small set of genes whose expression levels are predictive of drug response in the trained model, enabling identification of biomarkers of drug response. Using data from two large databases of CCLs and cancer tumors, we showed that this model can distinguish between sensitive and resistant tumors for 10 (out of 14) drugs, outperforming various other machine learning models. In addition, our small interfering RNA (siRNA) knockdown experiments on 10 genes identified by this model for one of the drugs (tamoxifen) confirmed that tamoxifen sensitivity is substantially influenced by all of these genes in MCF7 cells, and seven of these genes in T47D cells. Furthermore, genes implicated for multiple drugs pointed to shared mechanism of action among drugs and suggested several important signaling pathways. In summary, this study provides a powerful deep learning framework for prediction of drug response and identification of biomarkers of drug response in cancer. The code can be accessed at https://github.com/ddhostallero/tindl.

Abstract Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).