Fecal Microbial Community Composition in Myeloproliferative Neoplasm Patients Is Associated with an Inflammatory State.

The capacity of the human microbiome to modulate inflammation in the context of cancer is becoming increasingly clear. Myeloproliferative neoplasms (MPNs) are chronic hematologic malignancies in which inflammation plays a key role in disease initiation, progression, and symptomatology. To better understand the composition of the gut microbiome in patients with MPN, triplicate fecal samples were collected from 25 MPN patients and 25 non-MPN controls. Although most of the variance between the microbial community compositions could be attributed to the individual (permutational analysis of variance [PERMANOVA], R2 = 0.92, P = 0.001), 1.7% of the variance could be attributed to disease status (MPN versus non-MPN). When a more detailed analysis was performed, significantly fewer reads mapping to a species of Phascolarctobacterium, a microbe previously associated with reduced inflammation, were found in MPNs. Further, our data revealed an association between Parabacteroides and tumor necrosis factor alpha (TNF-α), an inflammatory cytokine elevated in MPNs. Taken together, our results indicate a significant difference in the microbiome of MPN patients compared to non-MPN controls, and we identify specific species which may have a role in the chronic inflammation central to this disease. IMPORTANCE MPNs are chronic blood cancers in which inflammation plays a key role in disease initiation, progression, and symptomatology. The gut microbiome modulates normal blood development and inflammation and may also impact the development and manifestation of blood cancers. Therefore, the microbiome may be an important modulator of inflammation in MPN and could potentially be leveraged therapeutically in this disease. However, the relationship between the gut microbiome and MPNs has not been defined. Therefore, we performed an evaluation of the MPN microbiome, comparing the microbiomes of MPN patients with healthy donors and between MPN patients with various states of disease.

Drug metabolising enzyme polymorphisms and chemotherapy-related ovarian failure in young breast cancer survivors.

Cyclophosphamide is associated with chemotherapy-related ovarian failure (CROF) in breast cancer survivors, however little is known about predicting individual risks. We sought to identify genetic alleles as biomarkers for risk of CROF after cyclophosphamide treatment. One hundred fifteen premenopausal women with newly diagnosed breast cancer were genotyped for single nucleotide polymorphisms (SNPs) in genes involved in cyclophosphamide activation (CYP3A4 and CYP2C19) and detoxification (GSTP1 and GSTA1). Patients prospectively completed menstrual diaries. With median follow up of 808 days, 28% experienced CROF. Survivors homozygous for the GSTA1 minor allele had lower hazards for developing CROF (HR 0.22 [95% CI 0.05-0.94], p=.04), while survivors homozygous for the CYP2C19 minor allele had higher hazards for developing CROF (HR 4.5 [95% CI 1.5-13.4], p=.007) compared to patients with at least one major allele. In separate multivariable models adjusting for age and tamoxifen use, the associations were no longer statistically significant (GSTA1 HR 0.24 [95% CI 0.06-1.0], p=.05; CYP2C19 HR 2.5 [0.8-7.6], p=.11). CYP3A4 and GSTP1 SNPs were not significantly related to CROF. In younger breast cancer survivors undergoing cyclophosphamide-based chemotherapy, genetic variation in CYP2C19 and GSTA1 merits further study to determine its relationship with CROF.IMPACT STATEMENTWhat is already known on this subject? Young breast cancer survivors face important potential implications of chemotherapy-related ovarian failure (CROF). Little is known about individual risk for CROF. Cyclophosphamide, a particularly gonadotoxic drug commonly used in breast cancer treatment, is metabolised by various cytochrome p450 enzymes. Studies have shown genetic variation in p450 enzymes is associated with differential clinical outcomes after cyclophosphamide treatment: breast cancer patients homozygous for GSTA1 minor allele had improved overall survival; lupus patients homozygous for CYP2C19 minor allele had increased risk for CROF; and CYP3A4*1B I was associated with decreased risk for CROF.What do the results of this study add? We show a surprising opposite trend for the risk of CROF in breast cancer patients with GSTA1 and CYP2C19 variants, while we did not show a significant risk for genetic variation in CYP3A4 (which had previously been shown to have a protective effect) or GSTP1.What are the implications of these findings for clinical practice and/or further research? This study shows the complexity of genetic variation in predicting outcomes to treatment. We advocate for future replicative studies to potentially validate GSTA1 and CYP2C19 and definitively negate CYP3A4 and GSTP1 as biomarkers for risk of CROF after cyclophosphamide treatment. Understanding genetic variation in chemotherapy metabolism has the potential to individualise treatment regimens to maximise efficacy and minimise toxicity.

The current landscape of molecular profiling in the treatment of epithelial ovarian cancer.

Advances in next generation sequencing have allowed for rapid and economical germline and tumor genomic profiling. Targeted therapies based on molecular tumor profiling are now integrated into treatment guidelines for many solid tumors. In epithelial ovarian cancer, 50% of tumors possess damaging mutations in homologous recombination repair genes (aka homologous recombination deficiency or HRD) which includes the BRCA genes. Deleterious BRCA mutations and HRD have recently emerged as predictive biomarkers for the use of PARP inhibitors in ovarian cancer. Every patient with ovarian cancer must be referred for genetic counseling and germline testing for BRCA mutations. Multigene panel genetic testing may be more informative and cost-effective than limited testing of cancer susceptibility genes. Patients without a germline deleterious BRCA mutation must be assessed for a somatic BRCA mutation. Assays for HRD may help guide treatment options in women who do not have a BRCA mutation. Currently, all patients with a germline or somatic BRCA mutation should be offered upfront maintenance therapy with a PARP inhibitor. During May 2020, options for maintenance therapy with a PARP inhibitor were expanded to patients with HRD and HR-proficient tumors.

Bevacizumab use in the frontline, maintenance and recurrent settings for ovarian cancer.

On 13 June 2018, Genentech, Inc. issued a press release announcing that the US FDA had approved the antiangiogenesis drug, bevacizumab, in combination with chemotherapy for frontline and maintenance therapy for women with newly diagnosed ovarian cancer. Regulatory approval was based on the National Cancer Institute-sponsored Gynecologic Oncology Group (GOG) protocol 0218, the Phase III, randomized, placebo-controlled, double-blind, multi-center and multi-national clinical trial that met its primary end point, progression-free survival. Bevacizumab is now approved in the frontline, platinum-sensitive recurrent and platinum-resistant recurrent settings for epithelial ovarian cancer. This review will address the broad range of clinical trials addressing the efficacy of bevacizumab use in ovarian cancer.

Genetic variants of age at menopause are not related to timing of ovarian failure in breast cancer survivors.

OBJECTIVE: To determine if interindividual genetic variation in single-nucleotide polymorphisms (SNPs) related to age at natural menopause is associated with risk of ovarian failure in breast cancer survivors. METHODS: A prospective cohort of 169 premenopausal breast cancer survivors recruited at diagnosis with stages 0 to III disease were followed longitudinally for menstrual pattern via self-reported daily menstrual diaries. Participants were genotyped for 13 SNPs previously found to be associated with age at natural menopause: EXO1, TLK1, HELQ, UIMC1, PRIM1, POLG, TMEM224, BRSK1, and MCM8. A risk variable summed the total number of risk alleles in each participant. The association between individual genotypes, and also the risk variable, and time to ovarian failure (>12 months of amenorrhea) was tested using time-to-event methods. RESULTS: Median age at enrollment was 40.5 years (range 20.6-46.1). The majority of participants were white (69%) and underwent chemotherapy (76%). Thirty-eight participants (22%) experienced ovarian failure. None of the candidate SNPs or the summary risk variable was significantly associated with time to ovarian failure. Sensitivity analysis restricted to whites or only to participants receiving chemotherapy yielded similar findings. Older age, chemotherapy exposure, and lower body mass index were related to shorter time to ovarian failure. CONCLUSIONS: Thirteen previously identified genetic variants associated with time to natural menopause were not related to timing of ovarian failure in breast cancer survivors.

Prechemotherapy antimullerian hormone, age, and body size predict timing of return of ovarian function in young breast cancer patients.

BACKGROUND: Endocrine measures of ovarian reserve before breast cancer treatment may predict postchemotherapy ovarian function, providing prognostic information at the time of cancer diagnosis. The objectives of this study were 1) to determine whether prechemotherapy levels of antimullerian hormone (AMH), follicle-stimulating hormone (FSH), and inhibin B (inhB) are associated with the return of ovarian function after chemotherapy and 2) to generate a prognostic score for ovarian recovery in young women with breast cancer. METHODS: A prospective cohort study recruited 109 participants (median age, 39 years; age range, 23-45 years) before chemotherapy from 2 breast clinics and followed them longitudinally. By using time-to-event analysis, the authors tested the association between prechemotherapy AMH, FSH, and inhB levels and the time to return of ovarian function, as measured by menstrual pattern. RESULTS: After a median follow-up of 163 days (range, 4-1009 days) after chemotherapy, 62 participants (57%) experienced return of ovarian function. In adjusted analyses, AMH levels >0.7 ng/mL (hazard ratio, 2.9; 95% confidence interval, 1.5-5.6) and FSH levels ≤10 IU/L (hazard ratio, 4.7; 95% confidence interval, 1.3-16.8) were associated with a shorter time to ovarian recovery, whereas inhB levels were not related. A prognostic score based on age <40 years, AMH >0.7 ng/mL, and body mass index ≥25 kg/m(2) was used to estimate the timing of recovery. CONCLUSIONS: In reproductive-aged women with newly diagnosed breast cancer, prechemotherapy AMH and FSH levels were associated with the return of ovarian function, independent of age. A novel prognostic score incorporating AMH, age, and body size was capable of estimating the time to ovarian recovery. Pending validation, these data support using prechemotherapy ovarian reserve measures, particularly AMH, to prospectively counsel young patients on future ovarian function. Because ovarian function is not equivalent to fertility, follow-up studies on predicting fertility are needed.

Comparability of antimüllerian hormone levels among commercially available immunoassays.

OBJECTIVE: To compare antimüllerian hormone (AMH) levels among three commercially available AMH immunoassays: AMH Gen II (Beckman Coulter), Ultrasensitive AMH (Ansh Labs), and picoAMH (Ansh Labs). DESIGN: Cross-sectional. SETTING: Academic reproductive endocrinology program. PATIENT(S): 90 newly diagnosed breast cancer patients before cancer treatment. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Proportion of detectable AMH levels by immunoassay, and comparability among assays. RESULT(S): At a mean age of 38.1 years, the median (interquartile range) AMH level for the cohort was 0.92 [1.35] ng/mL for the Gen II assay, 1.68 [2.30] ng/mL for the Ultrasensitive assay, and 1.52 [2.41] ng/mL for the picoAMH assay. Significantly higher proportions of detectable AMH levels were observed with the picoAMH kit (97%) compared with both the Gen II (84%) and Ultrasensitive (92%) assays. Although the AMH results were highly correlated among the assays (r = 0.92-0.99), the Gen II AMH levels were consistently lower than both Ultrasensitive and picoAMH levels. Moreover, as AMH levels increased, the magnitude of difference grew larger between Gen II and each of the other two assays. CONCLUSION(S): Measurement of AMH levels with the picoAMH kit maximized detection at very low levels, particularly in contrast with the Gen II kit. Conversion of AMH levels from different immunoassays using regression equations is potentially highly inaccurate.