Ovarian function in female survivors of high-risk neuroblastoma.

INTRODUCTION: Data on ovarian function in neuroblastoma survivors are limited. We sought to determine the prevalence of ovarian dysfunction in a cohort of high-risk neuroblastoma survivors and compare outcomes among survivors treated with and without autologous stem cell rescue (ASCR) preceded by myeloablative chemotherapy. METHODS: Retrospective review of female survivors of high-risk neuroblastoma ≥5 years from diagnosis, diagnosed between 1982 and 2014, and followed in a tertiary cancer center. Participants were divided into two groups: individuals treated with conventional chemotherapy ± radiation ("non-ASCR") (n = 32) or with chemotherapy ± radiation followed by myeloablative chemotherapy with ASCR ("ASCR") (n = 51). Ovarian dysfunction was defined as follicle-stimulating hormone ≥15 mU/mL, while premature ovarian insufficiency (POI) was defined as persistent ovarian dysfunction requiring hormone replacement therapy. Poisson models were used to determine prevalence ratios of ovarian dysfunction and POI. RESULTS: Among 83 females (median attained age: 19 years [range, 10-36]; median follow-up: 15 years [range, 7-36]), 49 (59%) had ovarian dysfunction, and 34 (41%) developed POI. Survivors treated with ASCR were 3.2-fold more likely to develop ovarian dysfunction (95% CI: 1.8-6.0; p < 0.001) and 4.5-fold more likely to develop POI (95% CI: 1.7-11.7; p = 0.002) when compared with those treated with conventional chemotherapy, after adjusting for attained age. Two participants in the non-ASCR group and six in the ASCR group achieved at least one spontaneous pregnancy. DISCUSSION: Ovarian dysfunction is prevalent in female high-risk neuroblastoma survivors, especially after ASCR. Longitudinal follow-up of larger cohorts is needed to inform counseling about the risk of impaired ovarian function after neuroblastoma therapy.

Identifying somatic fingerprints of cancers defined by germline and environmental risk factors.

Numerous studies over the past generation have identified germline variants that increase specific cancer risks. Simultaneously, a revolution in sequencing technology has permitted high-throughput annotations of somatic genomes characterizing individual tumors. However, examining the relationship between germline variants and somatic alteration patterns is hugely challenged by the large numbers of variants in a typical tumor, the rarity of most individual variants, and the heterogeneity of tumor somatic fingerprints. In this article, we propose statistical methodology that frames the investigation of germline-somatic relationships in an interpretable manner. The method uses meta-features embodying biological contexts of individual somatic alterations to implicitly group rare mutations. Our team has used this technique previously through a multilevel regression model to diagnose with high accuracy tumor site of origin. Herein, we further leverage topic models from computational linguistics to achieve interpretable lower-dimensional embeddings of the meta-features. We demonstrate how the method can identify distinctive somatic profiles linked to specific germline variants or environmental risk factors. We illustrate the method using The Cancer Genome Atlas whole-exome sequencing data to characterize somatic tumor fingerprints in breast cancer patients with germline BRCA1/2 mutations and in head and neck cancer patients exposed to human papillomavirus.

Adaptation of a mutual exclusivity framework to identify driver mutations within oncogenic pathways.

Distinguishing genomic alterations in cancer-associated genes that have functional impact on tumor growth and disease progression from the ones that are passengers and confer no fitness advantage have important clinical implications. Evidence-based methods for nominating drivers are limited by existing knowledge on the oncogenic effects and therapeutic benefits of specific variants from clinical trials or experimental settings. As clinical sequencing becomes a mainstay of patient care, applying computational methods to mine the rapidly growing clinical genomic data holds promise in uncovering functional candidates beyond the existing knowledge base and expanding the patient population that could potentially benefit from genetically targeted therapies. We propose a statistical and computational method (MAGPIE) that builds on a likelihood approach leveraging the mutual exclusivity pattern within an oncogenic pathway for identifying probabilistically both the specific genes within a pathway and the individual mutations within such genes that are truly the drivers. Alterations in a cancer-associated gene are assumed to be a mixture of driver and passenger mutations with the passenger rates modeled in relationship to tumor mutational burden. We use simulations to study the operating characteristics of the method and assess false-positive and false-negative rates in driver nomination. When applied to a large study of primary melanomas, the method accurately identifies the known driver genes within the RTK-RAS pathway and nominates several rare variants as prime candidates for functional validation. A comprehensive evaluation of MAGPIE against existing tools has also been conducted leveraging the Cancer Genome Atlas data.

Adaptation of a Mutual Exclusivity Framework to Identify Driver Mutations within Biological Pathways.

Distinguishing genomic alterations in cancer genes that have functional impact on tumor growth and disease progression from the ones that are passengers and confer no fitness advantage has important clinical implications. Evidence-based methods for nominating drivers are limited by existing knowledge on the oncogenic effects and therapeutic benefits of specific variants from clinical trials or experimental settings. As clinical sequencing becomes a mainstay of patient care, applying computational methods to mine the rapidly growing clinical genomic data holds promise in uncovering novel functional candidates beyond the existing knowledge-base and expanding the patient population that could potentially benefit from genetically targeted therapies. We propose a statistical and computational method (MAGPIE) that builds on a likelihood approach leveraging the mutual exclusivity pattern within an oncogenic pathway for identifying probabilistically both the specific genes within a pathway and the individual mutations within such genes that are truly the drivers. Alterations in a cancer gene are assumed to be a mixture of driver and passenger mutations with the passenger rates modeled in relationship to tumor mutational burden. A limited memory BFGS algorithm is used to facilitate large scale optimization. We use simulations to study the operating characteristics of the method and assess false positive and false negative rates in driver nomination. When applied to a large study of primary melanomas the method accurately identified the known driver genes within the RTK-RAS pathway and nominated a number of rare variants with previously unknown biological and clinical relevance as prime candidates for functional validation.

Metaplastic carcinoma of the breast: matched cohort analysis of recurrence and survival.

PURPOSE: Metaplastic breast carcinoma (MBC) is a rare subtype of breast cancer, defined as mammary carcinoma with squamous or mesenchymal differentiation, that may include spindle cell, chondroid, osseous, or rhabdomyoid differentiation patterns. The implications of MBC recurrence and survival outcomes remains unclear. METHODS: Cases were ascertained from a prospectively maintained institutional database of patients treated from 1998 to 2015. Patients with MBC were matched 1:1 to non-MBC cases. Cox proportional-hazards models and Kaplan-Meier estimates were used to evaluate outcome differences between cohorts. RESULTS: 111 patients with MBC were matched 1:1 with non-MBC patients from an initial set of 2400 patients. Median follow-up time was 8 years. Most patients with MBC received chemotherapy (88%) and radiotherapy (71%). On univariate competing risk regression, MBC was not associated with locoregional recurrence (HR = 1.08; p = 0.8), distant recurrence (HR = 1.65; p = 0.092); disease-free survival (HR = 1.52; p = 0.065), or overall survival (HR = 1.56; p = 0.1). Absolute differences were noted in 8-year disease-free survival (49.6% MBC vs 66.4% non-MBC) and overall survival (61.3% MBC vs 74.4% non-MBC), though neither of these reached statistical significance (p = 0.07 and 0.11, respectively). CONCLUSION: Appropriately-treated MBC may exhibit recurrence and survival outcomes that are difficult to distinguish from those of non-MBC. While prior studies suggest that MBC has a worse natural history than non-MBC triple-negative breast cancer, prudent use of chemotherapy and radiotherapy may narrow these differences, although studies with more power will be required to inform clinical management. Longer follow-up among larger populations may further elucidate the clinical and therapeutic implications of MBC.

Pathway Alterations in Stage II/III Primary Melanoma.

PURPOSE: Genomic classification of melanoma has thus far focused on the mutational status of BRAF, NRAS, and NF1. The clinical utility of this classification remains limited, and the landscape of alterations in other oncogenic signaling pathways is underexplored. METHODS: Using primary samples from the InterMEL study, a retrospective cohort of cases with specimens collected from an international consortium with participating institutions throughout the United States and Australia, with oversampling of cases who ultimately died of melanoma, we examined mutual exclusivity and co-occurrence of genomic alterations in 495 stage II/III primary melanomas across 11 cancer pathways. Somatic mutation and copy number alterations were analyzed from next-generation sequencing using a clinical sequencing panel. RESULTS: Mutations in the RTK-RAS pathway were observed in 81% of cases. Other frequently occurring pathways were TP53 (31%), Cell Cycle (30%), and PI3K (18%). These frequencies are generally lower than was observed in The Cancer Genome Atlas, where the specimens analyzed were predominantly obtained from metastases. Overall, 81% of the cases had at least one targetable mutation. The RTK-RAS pathway was the only pathway that demonstrated strong and statistically significant mutual exclusivity. However, this strong mutual exclusivity signal was evident only for the three common genes in the pathway (BRAF, NRAS, and NF1). Analysis of co-occurrence of different pathways exhibited no positive significant trends. However, interestingly, a high frequency of cases with none of these pathways represented was observed, 8.4% of cases versus 4.0% expected (P < .001). A higher frequency of RTK-RAS singletons (with no other pathway alteration) was observed compared with The Cancer Genome Atlas. Clonality analyses suggest strongly that both the cell cycle and RTK-RAS pathways represent early events in melanogenesis. CONCLUSION: Our results confirm the dominance of mutations in the RTK-RAS pathway. The presence of many mutations in several well-known, actionable pathways suggests potential avenues for targeted therapy in these early-stage cases.

SBRT focal dose intensification using an MR-Linac adaptive planning for intermediate-risk prostate cancer: An analysis of the dosimetric impact of intra-fractional organ changes.

INTRODUCTION: Using an magnetic resonance linear accelerator (MR-Linac) may improve the precision of visible tumor boosting with ultra-hypofractionation by accounting for daily positional changes in the target and organs at risk (OAR). PATIENTS AND METHODS: Fifteen patients with prostate cancer and an MR-detected dominant lesion were treated on the MR-Linac with stereotactic body radiation (SBRT) to 40 Gy in 5 fractions, boosting the gross tumor volume (GTV) to 45 Gy with daily adaptive planning. Imaging was acquired again after initial planning (verification scan), and immediately after treatment (post-treatment scan). Prior to beam-on, additional adjustments were made on the verification scan. Contours were retrospectively adjusted on verification and post-treatment scans, and the daily plan recalculated on these scans to estimate the true dose delivered. RESULTS: The median prostate D95% for plan 1, 2 and 3 was 40.3 Gy, 40.5 Gy and 40.3 Gy and DIL D95% was 45.7 Gy, 45.2 Gy and 44.6 Gy, respectively. Bladder filling was associated with reduced GTV coverage (p = 0.03, plan 1 vs 2) and prostate coverage (p = 0.03, plan 2 vs 3). The D0.035 cc constraint was exceeded on verification and post-treatment plans in 24 % and 33 % of fractions for the urethra, 31 % and 45 % for the bladder, and 35 % and 25 % for the rectum, respectively. CONCLUSION: MR-Linac guided, daily adaptive SBRT with focal boosting of the GTV yields acceptable planned and delivered dosimetry. Adaptive planning with a MR-Linac may reliably deliver the prescribed dose to the intended tumor target.