Cross-Comparison Individual Patient Level Analysis of Three Gene Expression Signatures in Localized Prostate in over 50,000 Men

PURPOSE/OBJECTIVE(S)

Risk stratification guides the management of localized prostate cancer. Multiple commercial gene expression biomarkers have been developed to improve estimates of prognosis, however the 22-gene Decipher genomic classifier (22-GC) is the only test with level 1 evidence supporting its use per NCCN guidelines. It is unknown whether other commercial signatures, Oncotype (GPS) or Prolaris (CCP), are sufficiently correlated to negate the differences in evidence supporting these commercial tests. Herein, we aim to perform a cross-comparison of these signatures in a large cohort of patients diagnosed with localized prostate cancer.

MATERIALS/METHODS

Patients diagnosed with localized prostate cancer who underwent whole transcriptome gene expression microarray analysis on their primary tumor biopsy specimen were included. The 22-GC score was calculated by Veracyte using a commercially locked model. Individual genes in each of the GPS and CCP gene signatures were identified, and the gene weights in each signature were retrained for prediction of metastasis in a multi-institutional cohort of 1,574 men with long-term outcome data. This was performed to improve correlation performance of GPS and CCP given only the 22-GC was trained for prediction of metastasis. For each of the three signatures, both continuous and categorical scores were calculated. Linear regression and spearman correlations were calculated both on univariable and multivariable analyses adjusting for age, grade group, PSA, and T-stage.

RESULTS

A total of 50,881 patients were included (15,379 (30.2%) NCCN low-risk, 14,773 (29.0%) favorable intermediate-risk, 15,544 (30.5%) unfavorable intermediate-risk, and 5,185 (10.2%) high/very high-risk) with a median age of 68 years, and a median PSA of 6.2 ng/mL. On linear regression, the GPS model had poor goodness-of-fit to the 22-GC with an R2 of 0.36, as did the CCP model to the 22-GC with an R2 of 0.32. For CCP, the linear sum of the 31-genes was also tested but had inferior performance (R2 0.28) compared to the reoptimized CCP model. Results were similar on multivariable analysis adjusting for age, PSA, clinical stage and grade group. Spearman correlation between the continuous GPS model scores and the 22-GC was moderate at 0.59, as was the correlation between CCP model and the 22-GC of 0.54. CCP is a measure of proliferation, but in 22-GC high-risk patients, the majority (64.1%) of patients had low-average proliferation and only 35.9% had high proliferation, potentially explaining the lack of strong correlation.

CONCLUSION

There is minimal to moderate correlation between the 22-GC and GPS or CCP gene expression signatures tested. Therefore, these tests should not be viewed as interchangeable, and utilization should be based on the level of evidence supporting each gene expression biomarker.

Trends in Utilization and Medicare Spending on Shorter vs. Longer Radiotherapy Courses for Breast and Prostate Cancer

PURPOSE/OBJECTIVE(S)

Evidence based research supports shorter, similarly efficacious, and potentially more cost-effective hypofractionated treatment regimens in many clinical scenarios for breast cancer (BC) and prostate cancer (PC). However, practice patterns of hospital-affiliated and standalone facilities vary considerably. We used the most recent Centers for Medicare and Medicaid Services data to assess trends in radiotherapy (RT) costs and practice patterns among episodes of BC and PC.

MATERIALS/METHODS

We performed a retrospective cohort analysis of all external beam episodes for BC and PC from 2015-2019. For patients with BC, receipt of shorter-course RT (SCRT) was defined as receiving 11-20 fractions of external beam radiation therapy (including IMRT), and conventional RT as >20 fractions. For patients with PC, SBRT was defined as receipt of <10 fractions and moderate hypofractionation as 10-30 fractions (SCRT defined as SBRT and moderate hypofractionation), and >30 fractions for conventional RT. Total Medicare spending were defined as the sum of winsorized payment for professional and technical services furnished during the episode in 2019 dollars. Multivariable logistic regression defined adjusted odds ratios (ORs) of receipt of SCRT over conventional RT by treatment modality, age, year of diagnosis, type of practice, as well as a time*treatment setting interaction term. Medicare spending was evaluated using multivariable linear regression controlling for duration of RT regimen (SCRT vs conventional) in addition to the covariables above.

RESULTS

Of 47,283 BC episodes and 45,917 PC episodes, 23,705 (50.13%) and 9,125 (19.87%) were SCRT, respectively. Median total spending for SCRT among BC episodes was $9,324 (IQR, $7,916-$10,921) vs. $13,372 (IQR, $11,511-$15,283) for conventional RT. Among PC episodes, median total spending was $12,917 (IQR, $9,551-$15,271) for SBRT, $18,944 (IQR, $16,530-$20,615) for moderate hypofractionation, and $26,935 (IQR, $25,062-$28,959) for conventional RT. For both cancers, total episode spending was reduced with SCRT utilization [(BC adjusted β, -$4,200; p<0.001), (PC adjusted β, -$8,747; p<0.001)], older age, and non-IMRT-based treatment. On logistic regression, receipt of SCRT was associated with older age among both BC and PC episodes (p<0.001), as well as treatment at hospital-affiliated over freestanding sites [(BC OR [95% CI], 1.41 [1.29-1.54], p<0.001), (PC OR, 1.64 [1.39-1.94], p<0.001)].

CONCLUSION

In this evaluation of all BC and PC RT episodes from 2015-2019, we found that shorter-course RT resulted in increased cost-savings vs. conventional RT. SCRT was also more common in hospital-affiliated sites. Further research is needed to devise payment incentives that encourage SCRT when clinically applicable in the two most common sites treated with RT, and to prospectively study cost-effective hypofractionation in other disease sites.

Genomic Characterization of Locally Recurrent Prostate Cancer after Radiation Therapy

PURPOSE/OBJECTIVE(S)

Radiation therapy (RT) is a backbone of treatment for patients with prostate cancer (PCa). However, locally recurrent disease after definitive RT (i.e., radiorecurrent PCa) is not uncommon and is associated with a higher risk of distant metastases and death from PCa. While the genomic landscape of primary PCa is well-characterized, little is known regarding the genomic landscape of radiorecurrent PCa or how this compares to that of primary PCa. We hypothesized that the genomic landscape of radiorecurrent PCa differs significantly from primary PCa and that these differences have clinical relevance. We examined this hypothesis by performing whole exome sequencing (WES) of radiorecurrent PCa.

MATERIALS/METHODS

We identified 25 patients with radiorecurrent PCa with available post-RT tissue obtained from biopsy or radical prostatectomy, as well as germline tissue. The tumor and germline tissue for 19 patients successfully underwent WES. We identified genomic variants including single nucleotide variants (SNVs), insertions/deletions, and copy number alterations. Furthermore, we estimated the tumor mutational burden (TMB; number of nonsynonymous mutations per megabase [Mb]) and contribution of individual mutational signatures. We compared our samples to a publicly available large cohort of primary PCa (n = 680) to define genomic alterations unique to radiorecurrent PCa.

RESULTS

In the overall cohort of 25 patients, the RT modality included external beam RT (56%), brachytherapy (36%), and combination of both (8%). 40% of patients received upfront androgen deprivation therapy with RT. The median time to local recurrence was 6.5 years. For the 19 radiorecurrent patients with WES data, the median TMB was 2.7 mutations/Mb, which was significantly higher than the median TMB of 0.7 mutation/Mb for primary PCa (P = 0.002 after multivariable adjustment). Radiorecurrent PCa demonstrated an enrichment of short deletions, with a significantly higher deletion/SNV ratio compared to primary PCa (P = 0.006). TP53 was the most frequently mutated gene in radiorecurrent PCa (n = 6), and the TP53 mutation prevalence was significantly higher compared to primary PCa (32% vs 10%, P = 0.016 by Fisher's exact test). TP53 was also determined to be recurrently mutated using MutSigCV (Q = 0.0003). Additionally, 3 samples demonstrated evidence of whole genome doubling.

CONCLUSION

Radiorecurrent PCa has a distinct genomic profile compared to primary PCa, characterized by a higher TMB with an enrichment of short deletions as part of the mutational composition, which may be a scar of nonhomologous end joining subsequent to RT-induced DNA double-stranded breaks. In addition, TP53 mutations may be of functional consequence in radiorecurrent PCa. Further efforts are underway to examine other genomic features apparent in WES data, as well as perform whole transcriptome sequencing to provide complementary insights into radiorecurrent PCa.

Determinants of Widespread Metastases and of Metastatic Tropism in Patients with Prostate Cancer: A Genomic Analysis of Primary and Metastatic Tumors

PURPOSE/OBJECTIVE(S)

A growing body of evidence suggests that metastatic cancer is better described as a spectrum of disease rather than a binarily defined state, ranging from oligometastatic cancer to widespread metastases. Widespread metastases represent the most common cause of cancer-related death among patients with prostate cancer. Therefore, a greater understanding of the genomic features that determine the extent and location of metastatic spread may inform risk stratification, treatment, and monitoring. We identify genomic alterations from primary prostate tumors that are predictive of widespread metastatic potential.

MATERIALS/METHODS

Genomic and clinical data for 1,312 patients with primary prostate adenocarcinomas were extracted from the MSK-MET cohort through cBioPortal. Metastatic site counts and overall survival (OS) data were publicly available for all patients. All samples from primary tumors were profiled using the MSK-IMPACT targeted sequencing platform. Our study focused on 58 genes frequently altered in prostate cancer. Cox proportional hazard analyses defined hazard ratios (HRs) and 95% confidence intervals (CIs) for overall mortality in patients with different metastatic outcomes. Patterns of genomic alterations of the primary tumor associated with metastatic extent and location were compared.

RESULTS

Out of 1,312 patients, 939 (71%) developed metastases, and 113 (8.6%) had metastases to 5 or more distinct anatomical sites (defining wide-spread metastases, WSM). Bone was the most common site of metastasis (36%), and 80% of patients with liver metastases had 4 or more additional sites of metastasis. Among patients with metastases, increasing number of metastatic sites was associated with increased risk of death (HR:1.8, 95% CI:1.63-1.99, p<0.001). To define genomic determinants of WSM, we characterized genomic alterations in 58 prostate cancer related genes. Alterations in the following genes were enriched in tumors from patients with WSM vs others: TP53 mutation (40% vs 20%, p<0.0001), FOXA1-amplification (8% vs 3%, p = 0.02), AR-amplification (4.4% vs 1%, p = 0.01), RB1-deletion (5.3% vs 0.7%, p = 0.001), and BRCA2-deletion (4.4% vs 0.7%, p = 0.01). In a univariable survival analysis, all these alterations were predictive of OS (p<0.05). However, on multivariable analysis, only TP53 mutations, and FOXA1 and AR amplifications were independent prognostic factors. Amplifications of FOXA1 (n = 37) and AR (n = 13) were mutually exclusive (0 overlap), and we found that patients who have either AR or FOXA1 amplifications experienced very poor OS (HR:3.57, 95% CI:2.26-5.6, p p<0.001].

CONCLUSION

We identified genomic alterations (TP53 mutations, FOXA1 and AR amplification, RB1 and BRCA2 deletions) from primary prostate tumors that are predictive of wide-spread metastases and poor outcomes.

Health Equity Achievement in Radiation Therapy (HEART) Score: A Social Prognosis

PURPOSE/OBJECTIVE(S)

The aim of this study was to develop a Health Equity Achievement in Radiation Therapy (HEART) score that can help identify patients at risk of experiencing suboptimal quality-of-care (QoC) early on in the patient-provider encounter and prior to initiation of treatment. Such a score may improve shared decision making to improve QoC.

MATERIALS/METHODS

A retrospective analysis was conducted using the National Cancer Database (NCDB) for prostate cancer cases between 2004-2017. Sociodemographic factors, clinical characteristics, and treatment information were collected. A composite HEART score was built to predict suboptimal QoC, defined as treatment refusal, incomplete treatment, or treatment delay. 70% of the data was allocated to training and 30% to validating a logistic regression model through which a nomogram was constructed.

RESULTS

A total of 1,599,785 patients were included in the analysis, of whom 126,917 (7.9%) had at least one suboptimal QoC. The strongest predictors were Black race, uninsured status, lower educational status, geographic location, and nodal disease (Table). The nomogram demonstrated a fair ability to predict quality metrics, with an area under the receiver operating characteristic curve (AUC) of 0.57 in the test group. The nomogram facilitated graphic interpretation of systemic factors in contributing to suboptimal QoC.

CONCLUSION

With observed potential for predicting suboptimal QoC outcomes in patients with prostate cancer by considering systemic barriers, this NCDB-based nomogram has potential utility as a tool for identifying patients who may benefit from additional social support, including the financial resources associated with these services, to improve access to care. Further validation in diverse datasets is needed to improve performance and generalizability to broader patient populations and different disease sites.

Indications for Adjuvant Radiation after Radical Prostatectomy as Predicted by Artificial Intelligence-Derived Dominant Intraprostatic Lesion Volume

PURPOSE/OBJECTIVE(S)

In prostate cancer, PI-RADs scores of dominant intraprostatic lesions (DILs) in multi-parametric magnetic resonance imaging (mpMRI) are prognostic; however, their inter-observer agreement is only moderate. Artificial intelligence (AI) may be a powerful tool for prognostication by analyzing a large number of scans consistently in a short amount of time. This study investigated whether the DIL volume (DILvol) provided by an AI deep-learning segmentation algorithm could predict adverse findings at radical prostatectomy (RP), some of which could warrant adjuvant radiation therapy (RT).

MATERIALS/METHODS

We conducted a retrospective study of 185 consecutive patients with localized prostate cancer who underwent an endorectal coil, high B-value (> = 1000 s/mm2), 3-Tesla mpMRI followed by RP between 2015 and 2017. Using a previously trained deep learning nnUNet algorithm for providing DIL segmentations from patients treated with definitive RT, we segmented the DIL for the RP cohort. We evaluated the association of AI DILvol with the risks of adverse pathologic factors, including positive margins, pathologic T3 (pT3) disease, and pathologic Gleason (pGS8-10) disease, using separate univariate logistic regression models. We then included AI DILvol, pT3 (vs pT2), pGS8-10 (vs pGS6-7), margin status, and pre-RP PSA for predicting post-RP PSA values utilizing multivariate linear regression analysis. Finally, we included these same factors into a multivariate logistic regression analysis for predicting the risk of meeting adjuvant RT indications (PSA persistence post-RP > = 0.1 ng/mL or positive lymph nodes).

RESULTS

The median time between RP and post-PSA value was 1.6 months. The Pearson's correlation coefficient between AI and reference DILvol (sum of manually contoured PI-RADS 3-5 lesions) was 0.86 (p < 0.001). The Pearson's correlation coefficient between AI DILvol and pathologic tumor size was 0.63 (p < 0.001). Utilizing separate univariate logistic regression models, we found that AI DILvol was significantly associated with the risks of positive margins (OR 1.31 [1.10, 1.58]; p = 0.003), pT3 (OR 1.59 [95% CI: 1.30, 1.99]; p < 0.001), and pGS8-10 (OR 1.28 [1.07, 1.56]; p = 0.01). On multivariate linear regression, AI DILvol (0.27/mL [0.25, 0.29]; p < 0.001) was significantly correlated with post-RP PSA values, after controlling for adverse factors and pre-RP PSA. On multivariate logistic regression, AI DILvol (adjusted OR 1.32 [1.05, 1.69]; p = 0.03) was the only factor significantly associated with the risk of meeting adjuvant RT indications after controlling for these same factors.

CONCLUSION

For localized prostate cancer treated with RP, AI DILvol was the only factor significantly associated with the risk of meeting adjuvant RT indications, even after controlling for pathologic factors at RP. Further studies are needed to determine if AI DILvol is prognostic for long-term oncologic outcomes after RP.

Long-Term Follow-Up Analysis of NRG Oncology RTOG 0415: A Randomized Phase III Non-Inferiority Study Comparing Two Fractionation Schedules in Patients with Favorable-Risk Prostate Cancer

PURPOSE/OBJECTIVE(S)

To assess whether the efficacy of a hypofractionated (H) schedule is no worse than a conventional (C) schedule in men with low-risk prostate cancer.

MATERIALS/METHODS

Accrual began April 2006 and ended in December 2009. 1115 men with favorable-risk prostate cancer were randomly assigned 1:1 to a conventional (C) schedule (73.8 Gy in 41 fractions over 8.2 weeks) or to a hypofractionated (H) schedule (70 Gy in 28 fractions over 5.6 weeks). The trial was designed to establish with 90% power and alpha = 0.05 that (H) results in 5-year disease-free survival (DFS) that is not lower than (C) by more than 7% (hazard ratio (HR) < 1.52). Protocol specified secondary endpoints evaluated for noninferiority include: biochemical recurrence (BR), local progression, disease-specific survival, and overall survival.

RESULTS

One thousand ninety-two protocol eligible men were analyzed: 542 to C and 550 to H. Median follow-up is 12.75 years. Baseline characteristics were not different according to treatment arm. The estimated 12-year DFS is 56.1% (95% CI 51.5, 60.5) in the C arm and 61.8% (57.2, 66.0) in the H arm. The DFS hazard ratio (H/C) is 0.85 (0.71-1.03), confirming non-inferiority (p<0.001). Twelve-year cumulative incidence of biochemical recurrence (BR) was 17.0% (CI 13.8, 20.5) in the C-RT and 9.9% (CI 7.5, 12.6) in the H-RT arm; (HR = 0.56, (0.40-0.78) suggesting improved efficacy with H. Additional pre-specified secondary endpoints were non-inferior Late Grade ≥ 3 GI toxicity is 3.2% (C) vs. 4.4% (H), Relative risk (RR) for H vs. C 1.39 (CI 0.75, 2.55) Late Grade ≥ 3 GU toxicity is 3.4% (C) vs. 4.2% (H), RR = 1.26 (CI 0.69, 2.30).

CONCLUSION

In men with favorable-risk prostate cancer, long-term disease-free survival is non-inferior with 70 Gy in 28 fractions compared to 73.8 Gy in 41 fractions. The risk of BR is reduced with moderate hypofractionation. No differences in late Grade ≥3 GI/GU toxicity were observed between the arms. (ClinicalTrials.gov identifier: NCT00331773).

Association between Artificial Intelligence-Derived Tumor Volume and Oncologic Outcomes for Localized Prostate Cancer Treated with Radiation Therapy

PURPOSE/OBJECTIVE(S)

Although clinical features of multi-parametric magnetic resonance imaging (mpMRI) have been associated with biochemical recurrence in localized prostate cancer, such features are subject to inter-observer variability. We evaluated whether the volume of the dominant intraprostatic lesion (DIL), as provided by a deep learning segmentation algorithm, could provide prognostic information for patients treated with definitive radiation therapy (RT).

MATERIALS/METHODS

We conducted a retrospective study of 438 patients with localized prostate cancer who underwent an endorectal coil, high B-value, 3-Tesla mpMRI and were treated with definitive RT at our institution between 2010 and 2017. We utilized the publicly available nnUNet to train a segmentation model which was used to identify the DIL. We examined the association between the artificial intelligence (AI)-generated DIL volume and oncologic outcomes, including biochemical recurrence and metastasis risk, using cause-specific Cox regression and time-dependent receiver operating characteristic analysis.

RESULTS

The AI model identified DILs with an area under the receiver operating characteristic (AUROC) of 0.827 at the patient level. For the 233 patients with available PI-RADS scores, with a median follow-up of 5.6 years, there were 28 biochemical failures. AI-defined DIL volume was significantly associated with biochemical failure (adjusted hazard ratio 1.60, 95% confidence interval 1.14-2.24, p = 0.007) after adjustment for PI-RADS score. Among all 438 patients with a median follow-up of 6.9 years, there were 49 biochemical failures and 22 metastases. The AUROC for predicting 7-year biochemical failure for AI volume (0.790) was similar to that for National Comprehensive Cancer Network (NCCN) category (p = 0.17). The AUROC for predicting 7-year metastasis for AI volume trended towards being higher compared to NCCN category (0.854 vs 0.769, p = 0.06).

CONCLUSION

An AI algorithm using deep learning could identify the DIL with good performance. AI-defined DIL volume may be able to provide prognostic information independent of the NCCN risk group or other radiologic factors for patients with localized prostate cancer treated with RT.

FORMULA-509: A Multicenter Randomized Trial of Post-Operative Salvage Radiotherapy (SRT) and 6 Months of GnRH Agonist with Either Bicalutamide or Abiraterone Acetate/Prednisone (AAP) and Apalutamide (Apa) Post-Radical Prostatectomy (RP)

PURPOSE/OBJECTIVE(S)

FORMULA-509 was designed to evaluate whether adding six months of AAP and Apa to a GnRH Agonist could improve outcomes compared to six months of bicalutamide plus GnRH Agonist for patients with unfavorable features receiving SRT for a detectable PSA post-RP.

MATERIALS/METHODS

FORMULA-509 is an investigator-initiated, multi-center, open-label, randomized trial. Patients had PSA ≥0.1 post-RP and one or more unfavorable features (Gleason 8-10, PSA >0.5, pT3/T4, pN1 or radiographic N1, PSA doubling time <10 months, negative margins, persistent PSA, gross local/regional disease, or Decipher High Risk). All patients received SRT plus 6 months of GnRH agonist and randomization was to concurrent bicalutamide 50 mg or AAP 1000 mg/5 mg + Apa 240 mg QD. Radiation to pelvic nodes was required for pN1 and optional for pN0. The primary endpoint was PSA progression-free survival (PFS) and secondary endpoint was metastasis-free survival (MFS) determined by conventional imaging. The study was powered to detect a HR of 0.50 for PFS and a HR of 0.30 for MFS, each with 80% power and one-sided type I error of 0.05. Stratification was by PSA at study entry (>0.5 vs.≤0.5) and pN0 vs pN1. Analyses within these subgroups were pre-planned and utilized two-sided p-values.

RESULTS

Three hundred forty-five participants (332 evaluable) from 9 sites were randomized from 11/24/2017 to 3/25/2020 (172 bicalutamide, 173 AAP/Apa). Median follow-up was 34 (6-53) months; 29% were pN1 and 31% had PSA >0.5 ng/mL. The HR for PFS was 0.71 (90% CI 0.49-1.03), stratified one-sided log-rank p = 0.06 (3-year PFS was 68.5% bicalutamide vs 74.9% AAP/Apa). The HR for MFS was 0.57 (90% CI 0.33-1.01), stratified one-sided log rank p = 0.05 (3-year MFS was 87.2% bicalutamide vs 90.6% AAP/Apa). In a pre-planned analysis by stratification factors, AAP/Apa was significantly superior for patients with PSA >0.5 for PFS [HR 0.50, (95% CI 0.27-0.95), p = 0.03 (2-sided); 3-year PFS 46.8% bicalutamide vs. 67.2% AAP/Apa] and for MFS [HR 0.32 (95% CI 0.13-0.84), p = 0.02 (2-sided); 3-year MFS 66.1% bicalutamide vs. 84.3% AAP/Apa.] No statistically significant benefit was detected in pre-planned analyses of stratification subgroups defined by PSA≤0.5, pN0, or pN1. Adverse events were consistent with the known safety profiles of the agents being studied, with more rash and hypertension in the AAP/Apa arm.

CONCLUSION

Although this primary analysis did not meet the pre-specified threshold for statistical significance, it does strongly suggest that the addition of AAP/Apa instead of bicalutamide to SRT+6 months of GnRH Agonist may improve PFS and MFS, particularly in the subgroup of patients with PSA>0.5 where a pre-planned subgroup analysis by stratification factors observed a statistically significant benefit for both PFS and MFS. (NCT03141671).

εγ-Thalassemia, a New Hemoglobinopathy Category

BACKGROUND

Large β-globin gene cluster deletions (hereditary persistence of fetal hemoglobin [Hb] or β-, δβ-, γδβ-, and ϵγδβ-thalassemia), are associated with widely disparate phenotypes, including variable degrees of microcytic anemia and Hb F levels. When present, increased Hb A2 is used as a surrogate marker for β-thalassemia. Notably, ϵγδβ-thalassemias lack the essential regulatory locus control region (LCR) and cause severe transient perinatal anemia but normal newborn screen (NBS) results and Hb A2 levels. Herein, we report a novel deletion of the ϵ, Aγ, Gγ, and ψβ loci with intact LCR, δ-, and β-regions in 2 women and newborn twins.

METHODS

Capillary electrophoresis (CE), high-performance liquid chromatography (HPLC), DNA sequencing, multiplex ligation-dependent probe amplification (MLPA), gap-polymerase chain reaction (gap-PCR), and long-read sequencing (LRS) were performed.

RESULTS

NBS showed an Hb A > Hb F pattern for both twins. At 20 months, Hb A2 was increased similarly to that in the mother and an unrelated woman. Unexplained microcytosis was absent and the twins lacked severe neonatal anemia. MLPA, LRS, and gap-PCR confirmed a 32 599 base pair deletion of ϵ (HBE1) through ψβ (HBBP1) loci.

CONCLUSIONS

This deletion represents a hemoglobinopathy category with a distinct phenotype that has not been previously described, an ϵγ-thalassemia. Both the NBS Hb A > F pattern and the subsequent increased Hb A2 without microcytosis are unusual. A similar deletion should be considered when this pattern is encountered and appropriate test methods selected for detection. Knowledge of the clinical impact of this new category will improve genetic counselling, with distinction from the severe transient anemia associated with ϵγδβ-thalassemia.

"It's Like You Stuck a Pin in It:" African American/Black Patients Describe Cutaneous Toxicity From Epidermal Growth Factor Receptor Inhibitors

Background: Epidermal growth factor receptor (EGFR) inhibitors cause cutaneous toxicity in over 90% of patients. Conceivably, healthcare providers could overlook such toxicity in African American/Black patients because of a darker complexion. This qualitative study sought to learn about such cutaneous signs and symptoms and, if present, to report them in patients' own words. Methods: Any patient who self-identified as African American/Black and who had been prescribed an EGFR inhibitor was eligible. The current report focuses on patients' responses to the following question, "What have you noticed since starting your cancer treatment (the EGFR inhibitor), any particular symptoms or reactions, positive or negative?" All interview data were audio-recorded, transcribed, and then independently coded and analyzed by two investigators. Results: Fifteen patients are the focus of this report, and all described cutaneous toxicity. Patients appeared troubled by the cosmetic aspect of these drug-induced skin changes, including their acneiform appearance, describing "little pimples with little, little pus in it." Notable were comments on hyperpigmentation, "I'm a black person but…. became darker." Furthermore, patients experienced physical symptoms: "it itches;" "it's like you stuck a pin in it;" "stinging;" and "burning;". Conclusion: Although cutaneous toxicity from EGFR inhibitors might be more difficult to visualize among darkly complected patients, the graphic descriptions offered in this qualitative study underscore the need for clinicians to heighten their awareness of such toxicity in African American/Black patients.

Abnormal CD13/HLA-DR Expression Pattern on Myeloblasts Predicts Development of Myeloid Neoplasia in Patients With Clonal Cytopenia of Undetermined Significance

OBJECTIVES

Patients with clonal cytopenia of undetermined significance (CCUS) are at increased risk of developing myeloid neoplasia (MN). We evaluated whether a simple flow cytometry immunophenotyping (FCIP) assay could differentiate the risk of development of MN in patients with CCUS.

METHODS

Bone marrow aspirates were assessed by FCIP panel in a cohort of 80 patients identified as having CCUS based on next-generation sequencing or cytogenetics from March 2015 to May 2020, with available samples. Flow cytometric assay included CD13/HLA-DR expression pattern on CD34-positive myeloblasts; CD13/CD16 pattern on maturing granulocytic precursors; and aberrant expression of CD2, CD7, or CD56 on CD34-positive myeloblasts. Relevant demographic, comorbidity, and clinical and laboratory data, including the type and extent of genetic abnormalities, were extracted from the electronic health record.

RESULTS

In total, 17 (21%) patients with CCUS developed MN over the follow-up period (median survival follow-up, 28 months [95% confidence interval, 19-31]). Flow cytometry immunophenotyping abnormalities, including the aberrant pattern of CD13/HLA-DR expression, as detected at the time of the diagnosis of CCUS, were significantly associated with risk of developing MN (hazard ratio, 2.97; P = .006). Additional FCIP parameters associated with the development of MN included abnormal expression of CD7 on myeloblasts and the presence vs absence of any FCIP abnormality.

CONCLUSIONS

A simple FCIP approach that includes assessment of CD13/HLA-DR pattern on CD34-positive myeloblasts can be useful in identifying patients with CCUS at higher risk of developing MN.

Characteristics and prognosis of mutated STAG2 myeloid neoplasms

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Background: Stromal Antigen 2 ( STAG2), located on Xq25, is the most mutated (m) cohesin-complex gene in myeloid neoplasm (MN) patients (pts). mSTAG2 is present in around 5% of MN and has been linked to secondary AML and potential poor impact on outcome. Methods: We retrospectively screened MN pts who had next-generation sequencing (NGS) (OncoHeme) performed at Mayo Clinic between 2018-2021. m STAG2 pts were included at the date of NGS. Charts were reviewed for clinical information after obtaining IRB approval. BlueSky Software V7.40 was used for statistical analysis. Results: Characteristics: 70 pts with mSTAG2 MN were identified, their median age was 72 years (range 25-91); with 55 pts (79%) being males. Complete blood counts showed median white blood cell count of 2.8 x109/L, hemoglobin of 8.9 gm/dL and platelets of 89 x109/L. The diagnosis was MDS in 38 pts (54%), AML in 20 (29%), MDS/MPN in 9 (13%), MPN in 2 (3%), and CCUS in 1 (1%). 11 cases (16%) were defined as therapy-related MN (tMN). Cytogenetics were normal in 45 pts (64%) and abnormal in 22 (31%). 10/50 non-AML pts progressed to AML (after median time of 9.8 months). Hematopoietic cell transplantation (HCT) was done in 20 pts (29%). mSTAG2: median VAF (mVAF) was 50% (range, 5%-100%). Males had higher mVAF compared to females (64% vs. 27%, p= .001), and tMN pts had higher mVAF compared to de novo (dn) MN pts (66% vs. 43%, p= .03). mVAF had no correlation with disease classification (50% in AML, 52% in MDS, 41% in MDS/MPN, 36% in MPN and 5% in CCUS, p= .5). STAG2 mutations were nonsense, frameshift, and splice site in 50%, 37%, and 13%, respectively. Co-mutations : median number of co-mutations was 3 (range, 0-6). Most common co-mutations were ASXL1 (66%), SRSF2 (37%), TET2 (36%), RUNX1 (29%), IDH2 (21%), BCOR (20%) and U2AF1 (16%) while least common were TP53, SETBP and ZRSR2 (1% each). Neither number (p= .08) nor type of co-mutation correlated with MN classification. There was no difference in the co-mutational pattern between tMN and dnMN pts. Survival : median overall survival (mOS) was 16.3 months with a median follow up time of 24.5 months. Pts who received HCT had better OS compared to non-HCT pts (mOS not reached vs. 14.9 months, p= .003). Pts with an isolated m STAG2 had better OS than co-mutated pts (p= .04), while the type of STAG2 mutation did not affect OS (p= .3). Pts with tMN had worse OS than dnMN pts (9.9 vs. 20.4 months, p= .02). VAF ≥75% had a negative impact on OS (20.5 vs 8.1 months, p= .008). mOS did not differ based on MN diagnosis. On multivariate analysis, only HCT (HR 0.3, p= .01) and VAF ≥75% (HR 2.3, p= .02) had impact on OS. Conclusions: mSTAG2 was more common in elderly males and MDS diagnosis. mSTAG2 was uncommon as an isolated mutation, indicating a possible role in disease progression with preferred certain co-mutations ( ASXL1/SRSF2/RUNX1/IDH2). mOS was poor regardless of MN diagnosis indicating a molecularly driven significance of an aggressive disease. The study needs to be validated by larger studies.

Characteristics and prognosis of DDX41- and GATA2-mutated myeloid neoplasms

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Background: Mutated DEAD-box helicase 41 (m DDX41), and mutated GATA2 are germline mutations associated with familial predisposition syndromes. In this study, we compare the clinical characteristics and survival outcomes (OS) of m DDX41 and m GATA2 MN patients (pts). Methods: We retrospectively screened pts who had next-generation sequencing (NGS) (OncoHeme panel) performed at Mayo Clinic. 4,524 consecutive pts (2018-2021) were screened for DDX41 mutations and 3,872 for GATA2 mutations (2015-2020) and included 36 MN pts with m DDX41 genetic alterations, and 55 m GATA2 MN pts. m GATA2 cases were included at NGS date while m DDX41 were included at diagnosis date. Germline workup was not done in all cases. JMP 16.2.0 Software was used for statistical analysis. Results: Patient characteristics: The most common diagnosis was MDS (N = 22, 61% in m DDX41 N = 17, 31% in m GATA2 group; p = .0044). MDS/MPN overlap was seen in m GATA2 group only; (29% vs. 0%; p = .0004). Majority of pts were males with median age of 68 and 67 years for m DDX41 and m GATA2 pts; respectively (p = .7). m DDX41 pts had higher hemoglobin, platelets, and MCV (< .0001, 0.005, < .0001; respectively) and significantly lower white blood cells (WBC) count compared to m GATA2 pts (< .0001). All m DDX41-AML pts were (ELN) intermediate-risk, and 64% of m DDX41 MDS were intermediate risk (IPSS-R). In contrast, of m GATA2 pts 62% of AML were adverse risk and 44% of MDS very high risk. Majority of m DDX41 pts had normal karyotype (N = 32; 91% vs. N = 19, 37%; p < .0001), had isolated mutations (N = 23; 64%) and the most common co-mutations were DNMT3A (38%), ASXL1 (30%), JAK2 (23%). The majority of m GATA2 pts were co-mutated (96%) with a different co-mutation pattern ASXL1 (60%), SRSF2 (34%), RUNX1 (19%). Germline data: One m GATA2 pts had proven germline mutation, and 10/11 (91%) m DDX41 pts were confirmed Survival and progression in MDS/AML: After median follow-up of 30 months in MDS/AML, 7 (21%) m DDX41 and 23 (77%) m GATA2 pts died with superior OS in m DDX41 compared to m GATA2 pts with median OS of (136.7 vs. 6.8 months, p < .0001). Seven (31%) of 22 m DDX41 and 6 (35%) m GATA2 MDS pts progressed into AML with a median time to progression of (11.2 vs. 5.2 months, p = .045). The leukemia free survival (LFS) for m DDX41 MDS pts was significantly longer than LFS of m GATA2 MDS pts (24.4 vs. 6 months, p < .0001). Conclusions: We compare the outcomes of two unique mutations associated with germline predisposition. We found m DDX41 pts had fewer cytogenetic aberrations, no MDS/MPN overlap, and lower WBC count. Majority of m DDX41 MDS/AML pts were intermediate risk category, compared to predominance of adverse risk disease in m GATA2 pts, translating into better OS and LFS. This study is limited by the small size, lack of germline workup in all cases, and retrospective nature. However, it supports the favorable prognosis and indolent course of m DDX41 pts recently described.

Personal history of autoimmune disease and other medical conditions and risk of myelodysplastic syndromes

BACKGROUND

Autoimmune diseases and hematopoietic malignancies are known to cluster within individuals, suggesting intertwined etiologies. A limited number of studies have evaluated pre-existing medical conditions as risk factors for myelodysplastic syndromes (MDS). We evaluated associations between autoimmune disease and other medical conditions and risk of MDS.

METHODS

Cases were identified through the Minnesota Cancer Reporting System. Controls were identified through the Minnesota State driver's license/identification card list. History of autoimmune disease and other medical conditions was based on self-report; proxy interviews were not conducted. Unconditional logistic regression was used to calculate adjusted odds ratios (aORs) and 95% confidence intervals (CI).

RESULTS

We included 395 cases and 694 controls. Cases were significantly more likely to report a diagnosis of any autoimmune disease when compared with controls (aOR=1.41, 95% CI: 1.05-1.89) after adjustment for age, sex, education, NSAID use, exposure to benzene and body mass index. When we evaluated specific autoimmune conditions, a statistically significant association was observed for hypothyroidism (aOR=2.16, 95% CI: 1.39-3.34) and odds ratios were elevated for inflammatory bowel disease (aOR=1.75) and systemic lupus erythematosus (SLE; aOR=3.65), although these associations did not reach statistical significance. Presence of an autoimmune condition did not impact overall survival (p = 0.91).

CONCLUSION

Our results validate previous findings of an association between autoimmune disease and MDS. Further studies are required to determine whether this association is due to shared etiology, treatment for autoimmune diseases, or altered immune surveillance or bone marrow damage caused by the autoimmune condition.

Improving Serious Illness Communication: Testing the Serious Illness Care Program with Trainees

BACKGROUND

Early conversations about patients' goals and values improve care, but clinicians struggle to conduct them. The systems-based Serious Illness Care Program (SICP) helps clinicians have more, better, and earlier conversations. Central to this approach is a clinician conversation guide for patient encounters. While the SICP works for practicing clinicians, it has not been tested with medical trainees.

INTERVENTION

We adapted the SICP training to emphasize assessing prognostic awareness and responding to emotion. We developed a 2.5-hour SICP workshop for medical students and medical interns that included large- and small-group work, practice with an actor, and interdisciplinary clinician facilitators. We trained 81 students and 156 interns and obtained anonymous quantitative and qualitative feedback.

OUTCOMES

Eighty-six percent of students and 91% of residents rated the session as "very good" or "excellent" and >90% of all learners would either recommend this training or intended to apply this to their practice. Post-session learner confidence increased in all communication skills. Learners said the training provided a helpful framework and useful language for these conversations. Resident documentation of serious illness conversations in the medical record increased dramatically during the year following training commencement.

CONCLUSIONS

Grounded in principles of adult learning theory, this training was rated highly by trainees and resulted in demonstrable practice change. These early learners were more flexible and willing to try this approach than practicing clinicians who tend to resist or revert to old habits. A Guide represents a new paradigm for teaching communication skills and is valued by early learners.

Improved Characterization of Complex β-Globin Gene Cluster Structural Variants Using Long-Read Sequencing

Complex insertion-deletion (indel) events in the globin genes manifest in widely variable clinical phenotypes. Many are incompletely characterized because of a historic lack of efficient methods. A more complete assessment enables improved prediction of clinical impact, which guides emerging therapeutic choices. Current methods have limited capacity for breakpoint assignment and accurate assessment of mutation extent, especially in cases containing duplications or multiple deletions and insertions. Technology, such as long-read sequencing, holds promise for significant impact in the characterization of indel events because of read lengths that span large regions, resulting in improved resolution. Four known complex β-globin gene cluster indel types were assessed using single-molecule, real-time sequencing technology and showed high correlation with previous reports, including the Caribbean locus control deletion (g.5,305,478_5,310,336del), a large β-gene duplication containing the Hb S mutation (g.4,640,335_5,290,171dup with g.5,248,232T>A, c.20A>T; variant allele fraction, 64%), and two nested variants (double deletions with intervening inversion): the Indian ^Gγ(^Aγδβ)⁰-thalassemia (g.5,246,804-5,254,275del, g.5,254,276_5,269,600inv, and g.5,269,601_5,270,442del) and the Turkish/Macedonian (δβ)⁰ thalassemia (g.5,235,064_5,236,652del, g.5,236,653_5,244,280inv, and g.5,244,281_5,255,766del). Our data confirm long-read sequencing as an efficient and accurate method to identify these clinically significant complex events. Limitations include high-complexity sample preparation requirements, which hinder routine use in clinical laboratories. Continued improvements in sample and data workflow processes are needed to accommodate volumes in a tertiary clinical laboratory.

Spectrum of hematological malignancies, clonal evolution and outcomes in 144 Mayo Clinic patients with germline predisposition syndromes

Germline predisposition syndromes (GPS) result from constitutional aberrations in tumor suppressive and homeostatic genes, increasing risk for neoplasia in affected kindred. In this study, we present clinical and genomic data on 144 Mayo Clinic patients with GPS; 59 evaluated prospectively using an algorithm-based diagnostic approach in the setting of a dedicated GPS/ inherited bone marrow failure syndrome (IBMFS) clinic. Seventy-two (50%) patients had IBMFS (telomere biology disorders-32,Fanconi anemia-18, Diamond Blackfan Anemia - 11, congenital neutropenia-5, Schwachman-Diamond Syndrome-5 and Bloom Syndrome-1), 27 (19%) had GPS with antecedent thrombocytopenia (RUNX1-FPD-15, ANKRD26-6, ETV6-2, GATA1-1, MPL-3), 28 (19%) had GPS without antecedent thrombocytopenia (GATA2 haploinsufficiency-16, DDX41-10, CBL-1 and CEBPA-1) and 17 (12%) had general cancer predisposition syndromes (ataxia telangiectasia-7, heterozygous ATM variants-3, CHEK2-2, TP53-2, CDK2NA-1, NF1-1 and Nijmegen Breakage Syndrome-1). Homozygous and heterozygous ATM pathogenic variants were exclusively associated with lymphoproliferative disorders (LPD), while DDX41 GPS was associated with LPD and myeloid neoplasms. The use of somatic NGS-testing identified clonal evolution in GPS patients, with ASXL1, RAS pathway genes, SRSF2 and TET2 being most frequently mutated. Fifty-two (91%) of 59 prospectively identified GPS patients had a change in their management approach, including additional GPS-related screening in 42 (71%), referral for allogenic HSCT workup and screening of related donors in 16 (27%), medication initiation and selection of specific conditioning regimens in 14 (24%), and genetic counseling with specific intent of fertility preservation and preconceptual counseling in 10 (17%) patients; highlighting the importance of dedicated GPS screening, detection and management programs for patients with hematological neoplasms.

Pathologic Spectrum and Molecular Landscape of Myeloid Disorders Harboring SF3B1 Mutations

Objectives

SF3B1 mutations are the most common mutations in myelodysplastic syndromes (MDS). The International Working Group for the Prognosis of MDS (IWG-PM) recently proposed SF3B1-mutant MDS (SF3B1^-mut-MDS) as a distinct disease subtype. We evaluated the spectrum and molecular landscape of SF3B1-mutated myeloid disorders and assessed the prognostication in MDS harboring SF3B1 mutations (MDS-SF3B1).

Methods

Cases were selected by retrospective review. Clinical course and laboratory and clinical findings were collected by chart review. SF3B1^-mut-MDS was classified following IWG-PM criteria.

Results

SF3B1 mutations were identified in 75 of 955 patients, encompassing a full spectrum of myeloid disorders. In MDS-SF3B1, Revised International Prognostic Scoring System (IPSS-R) score greater than 3 and transcription factor (TF) comutations were adverse prognostic markers by both univariate and multivariate analyses. We confirmed the favorable outcome of IWG-PM-defined SF3B1^-mut-MDS. Interestingly, it did not show sharp prognostic differentiation within MDS-SF3B1.

Conclusions

SF3B1 mutations occur in the full spectrum of myeloid disorders. We independently validated the favorable prognostication of IWG-PM-defined SF3B1^-mut-MDS. However it may not provide sharp prognostication within MDS-SF3B1 where IPSS-R and TF comutations were prognostic-informative. Larger cohort studies are warranted to verify these findings and refine MDS-SF3B1 prognostication.

Interpreting sulfhemoglobin and methemoglobin in patients with cyanosis: An overview of patients with M-hemoglobin variants

INTRODUCTION

Methemoglobin (MetHb) and sulfhemoglobin (SHb) measurements are useful in the evaluation of cyanosis. When one or both values are elevated, additional analysis is important to establish the etiology of the disorder. Methemoglobinemia occurs from acquired or hereditary causes with diverse treatment considerations, while true sulfhemoglobinemia is only acquired and treatment is restricted to toxin removal. Some toxic exposures can result in a dual increase in MetHb and SHb. Hereditary conditions, such as M-Hemoglobin variants (M-Hbs), can result in increased MetHb and/or SHb values but are clinically compensated and do not require treatment if they are cyanotic but otherwise clinically well.

METHODS

Herein, we report 53 hemoglobin variant cases that have associated MetHb and SHb levels measured by an adapted Evelyn-Malloy laboratory assay method.

RESULTS

Our data indicate M-Hbs cause variable patterns of MetHb and SHb elevation in a fairly reproducible pattern for the particular variant. In particular, α globin chain M-Hbs can mimic acquired sulfhemoglobinemia due to an isolated increased SHb value.

CONCLUSION

If the patient appears clinically well other than cyanosis, M-Hbs should be considered early in the evaluation process to differentiate from acquired conditions to avoid unnecessary testing and treatment regimens and prompt genetic counseling.

Classification of Monocytes, Promonocytes and Monoblasts Using Deep Neural Network Models: An Area of Unmet Need in Diagnostic Hematopathology

The accurate diagnosis of chronic myelomonocytic leukemia (CMML) and acute myeloid leukemia (AML) subtypes with monocytic differentiation relies on the proper identification and quantitation of blast cells and blast-equivalent cells, including promonocytes. This distinction can be quite challenging given the cytomorphologic and immunophenotypic similarities among the monocytic cell precursors. The aim of this study was to assess the performance of convolutional neural networks (CNN) in separating monocytes from their precursors (i.e., promonocytes and monoblasts). We collected digital images of 935 monocytic cells that were blindly reviewed by five experienced morphologists and assigned into three subtypes: monocyte, promonocyte, and blast. The consensus between reviewers was considered as a ground truth reference label for each cell. In order to assess the performance of CNN models, we divided our data into training (70%), validation (10%), and test (20%) datasets, as well as applied fivefold cross validation. The CNN models did not perform well for predicting three monocytic subtypes, but their performance was significantly improved for two subtypes (monocyte vs. promonocytes + blasts). Our findings (1) support the concept that morphologic distinction between monocytic cells of various differentiation level is difficult; (2) suggest that combining blasts and promonocytes into a single category is desirable for improved accuracy; and (3) show that CNN models can reach accuracy comparable to human reviewers (0.78 ± 0.10 vs. 0.86 ± 0.05). As far as we know, this is the first study to separate monocytes from their precursors using CNN.

Metastatic or suspected metastatic cancer in patients 90 years of age or older: A single-institution, multi-site study

BACKGROUND

Metastatic cancer in nonagenarians and those older is rare and understudied. Here we explored whether these patients appear to benefit from antineoplastic therapy and whether outcomes differ based on whether or not untreated patients had a histologic/cytologic confirmation of cancer.

METHODS

In this single-institution, multi-site study, we reviewed 10 years of consecutive medical records of patients 90+ years of age with a histologic/cytologic cancer diagnosis and metastatic cancer or, alternatively, a presumed metastatic cancer diagnosis.

RESULTS

Sixty-eight patients are the focus with a median age of 93 years (range: 90, 103 years). Patients fell into 3 groups: 1) no tissue/cytologic cancer diagnosis and no treatment (=23); 2) tissue/cytologic diagnosis but no treatment (n = 21); and 3) cancer treatment rendered (n = 24). The median survival in groups 1,2, and 3 was 5 weeks (95% confidence interval (CI): 2, 11 weeks), 9 weeks (95% CI: 3, 23 weeks), and 60 weeks (95% CI: 38 weeks, not yet reached), respectively. For those patients in group 3 who received cancer therapy, chemotherapy, radiation, and surgery were administered in 11 (16%), 6 (9%), and 4 (6%), respectively. Fourteen received other cancer therapy: hormonal therapy (n = 6), targeted therapy (n = 6), and immunotherapy (n = 2). Only one patient experienced an adverse event that required hospitalization.

CONCLUSIONS

Although these older patients likely received cancer treatment on a selective basis, such treatment was associated with improved survival and was well-tolerated. However, based on survival outcomes, one might question whether to put patients through a biopsy, if they have limited therapeutic options.