PARP inhibitor predictive value of the Leuven HRD test compared with Myriad MyChoice CDx PLUS HRD on 468 ovarian cancer patients from the PAOLA-1/ENGOT-ov25 trial

BACKGROUND

The PAOLA-1/ENGOT-ov25 trial showed improved progression-free (PFS) and overall survival (OS) in homologous recombination deficient (HRD) positive patients treated with olaparib, but not when HRD negative (HRD tested with MyChoice CDx PLUS [Myriad test]).

PATIENTS AND METHODS

The academic Leuven HRD test consists of capture-based targeted sequencing of genome-wide single-nucleotide polymorphisms and coding exons of eight HR genes including BRCA1, BRCA2, and TP53. We compared the predictive value of the Leuven HRD versus Myriad HRD test for PFS and OS in the randomised PAOLA-1 trial.

RESULTS

468 patients had left-over DNA after Myriad testing for Leuven HRD testing. Positive/negative/overall percent agreement for the Leuven versus Myriad HRD status was 95%/86%/91%, respectively. Tumours were HRD+ in 55% and 52%, respectively. In Leuven HRD+ patients, 5years PFS (5yPFS) was 48.6% versus 20.3% (HR 0.431; 95% confidence intervals (CI) 0.312-0.595) for olaparib versus placebo, respectively (Myriad test 0.409; 95% CI 0.292-0.572). In Leuven HRD+/BRCAwt patients 5yPFS was 41.3% versus 12.6% (HR 0.497; 95% CI 0.316-0.783), and 43.6% versus 13.3% (HR 0.435; 95% CI 0.261-0.727) for the Myriad test. 5yOS was prolonged in the HRD+ subgroup with both tests 67.2% versus 54.4% (HR 0.663; 95% CI 0.442-0.995) for the Leuven test, and 68.0% versus 51.8% (HR 0.596 95% CI 0.393-0.904) for the Myriad test. HRD status was undetermined in 10.7% and 9.4% of the samples, respectively.

CONCLUSIONS

A robust correlation between the Leuven HRD and Myriad test was observed. For HRD+ tumours, the academic Leuven HRD showed a similar difference in PFS and OS as the Myriad test.

Abstract 5785: A pan-cancer single-cell tumor micro-environment atlas predictive of immunotherapy response

The tumor microenvironment (TME) shapes response to immune checkpoint blockade (ICB). Several pan-cancer single-cell RNA-sequencing (scRNA-seq) analyses have reported how TME heterogeneity profoundly differs between cancer types. These studies mainly focused on one cell type (e.g., T-cells) and combined different technologies and bioinformatics pipelines with data being collected from both published and newly generated datasets. A comprehensive pan-cancer scRNA-seq map of the TME involving all cell types is therefore still lacking.

We obtained scRNA-seq (10x Genomics) on 234 fresh tissue samples from 161 treatment-naïve patients. Samples were collected from 9 cancer types and subjected to a uniform in-house optimized protocol of tissue dissociation, sequencing and bioinformatics analysis. Abundancies of cell types and subtypes were correlated with each other and a tumor-reactive T-cell signature.

From 683,184 high-quality single cells, we identified 9 cell types and 71 subtypes of T-cells, B-cells, dendritic cells (DCs), monocytes/macrophages and endothelial-cells (ECs), shared between cancer types. PDCD1 (PD1) was expressed by differentiated T-cells subtypes (e.g., CD8+ exhausted and CD4+ T-helper-1 subclusters), while CD274 and PDCD1LG (PDL-1/PDL-2) were mainly expressed by regulatory B-cells, immune-regulatory DCs, CXCL10+ and CCL2+ monocyte-derived macrophages as well as inflammatory ECs. Pairwise analyses showed positive correlations between PD1-expressing T-cell subclusters, CD4+ T-regulatory cells, plasma B-cells (plasmablasts, IgA and IgG plasma cells), immune-regulatory DCs, CXCL10+ and CCL2+ macrophages and lymphatic ECs. On the other hand, negative correlations were observed with naïve T- and B-cells, conventional DC2 (cDC2), monocytes, CX3CR1+ macrophages, as well as arterial and capillary ECs. When ranking individual tumors based on a tumor-reactive T-cell signature, we found reactive tumors to correlate with positively interacting subtypes, while they anti-correlated with subclusters negatively interacting with PD1-expressing differentiated T-cells. Upon deconvolution of bulk RNA-seq data using gene signatures derived from each subcluster, these correlations were replicated in TCGA datasets across cancers. These signature scores correlated with tumor mutation burden (TMB) and other immunological features, while they were also predictive of response in clinical trials involving ICB.

We provide insights into the TME complexity at unprecedented level, identifying numerous subclusters enriched in immune-reactive (hot) or -suppressive (cold) tumors across cancer types. We validate these observations in TCGA by deconvolution of bulk RNA-seq data, and show that already pre-treatment several TME subclusters predict response to ICB.

Citation Format: Francesca Lodi, Sam Vanmassenhove, Elena Donders, Pierre Van Mol, Amelie Franken, Sarah Cappuyns, Ayse Bassez, Siel Olbrecht, Liselore Loverix, Michel Bila, Hanne Vos, Joanna Pozniak, Kevin Punie, Diether Lambrechts. A pan-cancer single-cell tumor micro-environment atlas predictive of immunotherapy response. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5785.

CCNE1 and survival of patients with tubo-ovarian high-grade serous carcinoma: An Ovarian Tumor Tissue Analysis consortium study

BACKGROUND

Cyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo-ovarian high-grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large-scale, histotype-specific validation has been performed. The hypothesis was that high-level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC.

METHODS

Within the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated.

RESULTS

High-level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high-level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08-1.47, p = .034, and HR, 1.18; 95% CI, 1.05-1.32, p = .015, respectively). This was also true for cases with combined high-level amplification/overexpression (HR, 1.26; 95% CI, 1.09-1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1-SD increase; 95% CI, 0.94-1.06; p = .58). CCNE1 high-level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss.

CONCLUSION

This study provides large-scale validation that CCNE1 high-level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC.

Systematic study of tissue factor expression in solid tumors

BACKGROUND

Elevated tissue factor (TF) expression, although restricted in normal tissue, has been reported in multiple solid cancers, and expression has been associated with poor prognosis. This manuscript compares TF expression across various solid tumor types via immunohistochemistry in a single study, which has not been performed previously.

AIMS

To increase insight in the prevalence and cellular localization of TF expression across solid cancer types, we performed a detailed and systematic analysis of TF expression in tumor tissue obtained from patients with ovarian, esophageal, bladder, cervical, endometrial, pancreatic, prostate, colon, breast, non-small cell lung cancer (NSCLC), head and neck squamous cell carcinoma (HNSCC), and glioblastoma. The spatial and temporal variation of TF expression was analyzed over time and upon disease progression in patient-matched biopsies taken at different timepoints. In addition, TF expression in patient-matched primary tumor and metastatic lesions was also analyzed.

METHODS AND RESULTS

TF expression was detected via immunohistochemistry (IHC) using a validated TF-specific antibody. TF was expressed in all cancer types tested, with highest prevalence in pancreatic cancer, cervical cancer, colon cancer, glioblastoma, HNSCC, and NSCLC, and lowest in breast cancer. Staining was predominantly membranous in pancreatic, cervical, and HNSCC, and cytoplasmic in glioblastoma and bladder cancer. In general, expression was consistent between biopsies obtained from the same patient over time, although variability was observed for individual patients. NSCLC biopsies of primary tumor and matched lymph node metastases showed no clear difference in TF expression overall, although individual patient changes were observed.

CONCLUSION

This study shows that TF is expressed across a broad range of solid cancer types, and expression is present upon tumor dissemination and over the course of treatment.

Nucleosome footprinting in plasma cell-free DNA for the pre-surgical diagnosis of ovarian cancer

Fragmentation patterns of plasma cell-free DNA (cfDNA) are known to reflect nucleosome positions of cell types contributing to cfDNA. Based on cfDNA fragmentation patterns, the deviation in nucleosome footprints was quantified between diagnosed ovarian cancer patients and healthy individuals. Multinomial modeling was subsequently applied to capture these deviations in a per sample nucleosome footprint score. Validation was performed in 271 cfDNAs pre-surgically collected from women with an adnexal mass. We confirmed that nucleosome scores were elevated in invasive carcinoma patients, but not in patients with benign or borderline disease. Combining nucleosome scores with chromosomal instability scores assessed in the same cfDNA improved prediction of malignancy. Nucleosome scores were, however, more reliable to predict non-high-grade serous ovarian tumors, which are characterized by low chromosomal instability. These data highlight that compared to chromosomal instability, nucleosome footprinting provides a complementary and more generic read-out for pre-surgical diagnosis of invasive disease in women with adnexal masses.

MCM3 is a novel proliferation marker associated with longer survival for patients with tubo-ovarian high-grade serous carcinoma

Tubo-ovarian high-grade serous carcinomas (HGSC) are highly proliferative neoplasms that generally respond well to platinum/taxane chemotherapy. We recently identified minichromosome maintenance complex component 3 (MCM3), which is involved in the initiation of DNA replication and proliferation, as a favorable prognostic marker in HGSC. Our objective was to further validate whether MCM3 mRNA expression and possibly MCM3 protein levels are associated with survival in patients with HGSC. MCM3 mRNA expression was measured using NanoString expression profiling on formalin-fixed and paraffin-embedded tissue (N = 2355 HGSC) and MCM3 protein expression was assessed by immunohistochemistry (N = 522 HGSC) and compared with Ki-67. Kaplan-Meier curves and the Cox proportional hazards model were used to estimate associations with survival. Among chemotherapy-naïve HGSC, higher MCM3 mRNA expression (one standard deviation increase in the score) was associated with longer overall survival (HR = 0.87, 95% CI 0.81-0.92, p < 0.0001, N = 1840) in multivariable analysis. MCM3 mRNA expression was highest in the HGSC C5.PRO molecular subtype, although no interaction was observed between MCM3, survival and molecular subtypes. MCM3 and Ki-67 protein levels were significantly lower after exposure to neoadjuvant chemotherapy compared to chemotherapy-naïve tumors: 37.0% versus 46.4% and 22.9% versus 34.2%, respectively. Among chemotherapy-naïve HGSC, high MCM3 protein levels were also associated with significantly longer disease-specific survival (HR = 0.52, 95% CI 0.36-0.74, p = 0.0003, N = 392) compared to cases with low MCM3 protein levels in multivariable analysis. MCM3 immunohistochemistry is a promising surrogate marker of proliferation in HGSC.

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

Randomized CLIO/BGOG-ov10 trial of olaparib monotherapy versus physician's choice chemotherapy in relapsed ovarian cancer

OBJECTIVE

Comparison of olaparib (OLA) monotherapy versus chemotherapy in patients with platinum-sensitive (PSOC) or platinum-resistant ovarian cancer (PROC).

METHODS

Patients with measurable disease and ≥ 1 prior line of chemotherapy (CT) were randomized 2:1 to OLA (300 mg tablets, BID) or physician's choice CT.: for PSOC: Carboplatin-Pegylated-Liposomal-Doxorubicin (PLD) or Carboplatin-Gemcitabine; for PROC: PLD, Topotecan, Paclitaxel or Gemcitabine.

RESULTS

160 patients (60 with PSOC and 100 with PROC) were randomized 2:1 to OLA (n = 107) or CT (n = 53). Baseline characteristics were similar between both arms. Overall objective response rate (ORR) for OLA and CT were similar (24.3% (26/107) and 28.3% (15/53), respectively). Clinical benefit rate (≥ 12 weeks) was similar with 54.2% (58/107) and 56.6% (30/53), respectively. In PSOC, ORR was 35.0% (14/40) and 65.0% (13/20) for OLA and CT (p = 0.053); in PROC, ORR was 17.9% (12/67) and 6.1% (2/33) for OLA and CT (p = 0.134). ORR in heavily pretreated PROC (>4 prior lines) was 22.9% (8/35) with OLA versus 0% (0/14) for CT. ORR of 35.7% (5/14) and 13.2% (7/53) was observed in BRCA-mutated and -wildtype PROC cases, respectively. Median PFS in PROC was not significantly different with 2.9 months (95% CI 2.8-5.1 in the OLA group versus 3.8 months (95% CI 3.0-6.4) in the CT group (hazard ratio [HR] 1.11 [95% CI 0.72-1.78]; log-rank p = 0.600).

CONCLUSION

OLA monotherapy showed overall an equal response rate in relapsed ovarian cancer compared with CT. In PROC, ORR and TFST tended to be higher with OLA than with CT. In heavily pretreated patients (four lines or more) with PROC disease, OLA treatment seemed to be more effective than CT.

High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

BACKGROUND

High-grade serous tubo-ovarian cancer (HGSTOC) is characterised by extensive inter- and intratumour heterogeneity, resulting in persistent therapeutic resistance and poor disease outcome. Molecular subtype classification based on bulk RNA sequencing facilitates a more accurate characterisation of this heterogeneity, but the lack of strong prognostic or predictive correlations with these subtypes currently hinders their clinical implementation. Stromal admixture profoundly affects the prognostic impact of the molecular subtypes, but the contribution of stromal cells to each subtype has poorly been characterised. Increasing the transcriptomic resolution of the molecular subtypes based on single-cell RNA sequencing (scRNA-seq) may provide insights in the prognostic and predictive relevance of these subtypes.

METHODS

We performed scRNA-seq of 18,403 cells unbiasedly collected from 7 treatment-naive HGSTOC tumours. For each phenotypic cluster of tumour or stromal cells, we identified specific transcriptomic markers. We explored which phenotypic clusters correlated with overall survival based on expression of these transcriptomic markers in microarray data of 1467 tumours. By evaluating molecular subtype signatures in single cells, we assessed to what extent a phenotypic cluster of tumour or stromal cells contributes to each molecular subtype.

RESULTS

We identified 11 cancer and 32 stromal cell phenotypes in HGSTOC tumours. Of these, the relative frequency of myofibroblasts, TGF-β-driven cancer-associated fibroblasts, mesothelial cells and lymphatic endothelial cells predicted poor outcome, while plasma cells correlated with more favourable outcome. Moreover, we identified a clear cell-like transcriptomic signature in cancer cells, which correlated with worse overall survival in HGSTOC patients. Stromal cell phenotypes differed substantially between molecular subtypes. For instance, the mesenchymal, immunoreactive and differentiated signatures were characterised by specific fibroblast, immune cell and myofibroblast/mesothelial cell phenotypes, respectively. Cell phenotypes correlating with poor outcome were enriched in molecular subtypes associated with poor outcome.

CONCLUSIONS

We used scRNA-seq to identify stromal cell phenotypes predicting overall survival in HGSTOC patients. These stromal features explain the association of the molecular subtypes with outcome but also the latter's weakness of clinical implementation. Stratifying patients based on marker genes specific for these phenotypes represents a promising approach to predict prognosis or response to therapy.

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4⁺ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Incisional hernia repair in a high-fidelity silicone model for open retro-muscular mesh implantation with preparation of the fatty triangle: validation and educational impact study

BACKGROUND

Incisional hernia repair requires detailed anatomic knowledge. Regarding median subxiphoidal hernias, the proper preparation of the fatty triangle is challenging. To foster proficiency-based training, a cost-efficient model for open median retromuscular mesh repair resembling the human body was developed, including the main anatomical structures related to the procedure. The aim is to create and validate a high-fidelity model on open retromuscular mesh repair suitable for "training before doing".

MATERIALS AND METHODS

Different types of fabrics for imitation of connective tissue and 2-component silicones were used to construct the incisional hernia model. Sample size for validation of the model was determined by a triangular testing approach. Operations from six beginners and six experts were assessed by three blinded-raters. Reliability and construct-validity were evaluated on a behaviorally anchored rating scale (highest score: 4) for the criteria: "instrument use", "tissue handling", "near misses and errors", and "end-product quality".

RESULTS

The model authentically mimicked an open median retromuscular mesh repair. Participants considered the procedure realistic. Reliability was excellent, ranging from 0.811 to 0.974 for "end-product quality", and "tissue handling" respectively. Construct-validity was confirmed with experts significantly outperforming beginners in the "use of instruments" (M_beg. = 2.33, M_exp. = 3.94, p < 0.001), "tissue handling" (M_beg. = 2.11, M_exp. = 3.72, p < 0.001), "near misses and errors" (M_beg. = 2.67, M_exp. = 3.67, p < 0.001), and "end-product quality" (M_beg. = 2.78, M_exp. = 3.72, p < 0.001). Criterion-validity revealed a paradox effect: beginners performed significantly better than experts (p < 0.05) when preparing the fatty triangle.

CONCLUSIONS

The model covers all relevant aspects involved in median-open retromuscular incisional hernia mesh repair. Performance differences between beginners and experts confirm construct-validity and thereby realism of the model. It enables to efficiently improve and practice technical skills of the demanding surgery.

ESMO-ESGO consensus conference recommendations on ovarian cancer: pathology and molecular biology, early and advanced stages, borderline tumours and recurrent disease

The development of guidelines is one of the core activities of the European Society for Medical Oncology (ESMO) and European Society of Gynaecologial Oncology (ESGO), as part of the mission of both societies to improve the quality of care for patients with cancer across Europe. ESMO and ESGO jointly developed clinically relevant and evidence-based recommendations in several selected areas in order to improve the quality of care for women with ovarian cancer. The ESMO-ESGO consensus conference on ovarian cancer was held on April 12-14, 2018 in Milan, Italy, and comprised a multidisciplinary panel of 40 leading experts in the management of ovarian cancer. Before the conference, the expert panel worked on five clinically relevant questions regarding ovarian cancer relating to each of the following four areas: pathology and molecular biology, early-stage and borderline tumours, advanced stage disease and recurrent disease. Relevant scientific literature, as identified using a systematic search, was reviewed in advance. During the consensus conference, the panel developed recommendations for each specific question and a consensus was reached. The recommendations presented here are thus based on the best available evidence and expert agreement. This article presents the recommendations of this ESMO-ESGO consensus conference, together with a summary of evidence supporting each recommendation.

ESMO-ESGO consensus conference recommendations on ovarian cancer: pathology and molecular biology, early and advanced stages, borderline tumours and recurrent disease†

The development of guidelines recommendations is one of the core activities of the European Society for Medical Oncology (ESMO) and European Society of Gynaecologial Oncology (ESGO), as part of the mission of both societies to improve the quality of care for patients with cancer across Europe. ESMO and ESGO jointly developed clinically relevant and evidence-based recommendations in several selected areas in order to improve the quality of care for women with ovarian cancer. The ESMO-ESGO consensus conference on ovarian cancer was held on 12-14 April 2018 in Milan, Italy, and comprised a multidisciplinary panel of 40 leading experts in the management of ovarian cancer. Before the conference, the expert panel worked on five clinically relevant questions regarding ovarian cancer relating to each of the following four areas: pathology and molecular biology, early-stage and borderline tumours, advanced stage disease and recurrent disease. Relevant scientific literature, as identified using a systematic search, was reviewed in advance. During the consensus conference, the panel developed recommendations for each specific question and a consensus was reached. The recommendations presented here are thus based on the best available evidence and expert agreement. This article presents the recommendations of this ESMO-ESGO consensus conference, together with a summary of evidence supporting each recommendation.

Prognostic Value of the Progesterone Receptor by Subtype in Patients with Estrogen Receptor-Positive, HER-2 Negative Breast Cancer

BACKGROUND

In estrogen receptor-positive (ER+), human epidermal growth factor receptor 2 (HER-2) negative breast cancers, the progesterone receptor (PR) is an independent prognostic marker. Little is known about the prognostic value of PR by tumor grade. We assessed this in two independent datasets.

PATIENTS AND METHODS

Women with primary operable, invasive ER+ HER-2 negative breast cancer diagnosed between 2000 and 2012, treated at University Hospitals Leuven, were included. We assessed the association of PR status and subtype (grade 1-2 vs. grade 3) with distant recurrence-free interval (DRFI) and breast cancer-specific survival. The interaction between PR status and subtype was investigated, and associations of PR status by subtype were calculated. The BIG 1-98 data set was used for validation.

RESULTS

In total, 4,228 patients from Leuven and 5,419 from BIG 1-98 were analyzed. In the Leuven cohort, the adjusted hazard ratio (HR) of PR-positive versus PR-negative tumors for DRFI was 0.66 (95% confidence interval [CI], 0.50-0.89). For the interaction with subtype (p = .34), the HR of PR status was 0.79 (95% CI, 0.61-1.01) in luminal A-like and 0.59 (95% CI, 0.46-0.76) in luminal B-like tumors. In luminal A-like tumors, observed 5-year cumulative incidences of distant recurrence were 4.1% for PR-negative and 2.8% for PR-positive tumors, and in luminal B-like 18.7% and 9.2%, respectively. In the BIG 1-98 cohort, similar results were observed; for the interaction with subtype (p = .12), the adjusted HR of PR status for DRFI was 0.88 (95% CI, 0.57-1.35) in luminal A-like and 0.58 (95% CI, 0.43-0.77) in luminal B-like tumors. Observed 5-year cumulative incidences were similar.

CONCLUSION

PR positivity may be more protective against metastatic relapse in luminal B-like versus luminal A-like breast cancer, but no strong conclusions can be made. In absolute risk, results suggest an absent PR is clinically more important in high compared with low proliferative ER+ HER-2 negative tumors.

IMPLICATIONS FOR PRACTICE

An absent progesterone receptor (PR) predicts a worse outcome in women treated for an estrogen receptor-positive, human epidermal growth factor receptor 2 negative breast cancer. As low proliferative tumors lacking PR are now also classified high risk, the prognostic value of PR across risk groups was studied. Despite a negative test for interaction of the prognostic value of PR by tumor grade, the magnitude of an absent PR on breast cancer relapse is much larger in high than in low proliferative breast cancers.

Genomic signatures as predictive biomarkers of homologous recombination deficiency in ovarian cancer

DNA repair deficiency is a common hallmark of many cancers and is increasingly recognised as a target for cancer therapeutics. Selecting patients for these treatments requires a functional assessment of multiple redundant DNA repair pathways. With the advent of whole-genome sequencing of cancer genomes, it is increasingly recognised that multiple signatures of mutational and chromosomal alterations can be correlated with specific DNA repair defects. The clinical relevance of this approach is underlined by the use of poly-(ADP-ribose) polymerase inhibitors (PARPi) in homologous recombination (HR) deficient high-grade serous ovarian cancers. Beyond deleterious mutations in HR-related genes such as BRCA1/2, it is recognised that HR deficiency endows ovarian cancers with specific signatures of base substitutions and structural chromosomal variation. Multiple metrics quantifying loss-of-heterozygosity (LOH) events were proposed and implemented in trials with PARPi. However, it was shown that some of the HR-deficient cases, i.e. CDK12-mutated tumours, were not associated with high LOH-based scores, but with distinct patterns of genomic alterations such as tandem duplication. Therefore, more complex signatures of structural genomic variation were identified and quantified. Ultimately, optimal prediction models for treatments targeting DNA repair will need to integrate multiples of these genomic signatures and will also need to assess multiple resistance mechanisms such as genomic reversion events that partially or fully re-activate DNA repair.

Genomic signatures as predictive biomarkers of homologous recombination deficiency in ovarian cancer

DNA repair deficiency is a common hallmark of many cancers and is increasingly recognised as a target for cancer therapeutics. Selecting patients for these treatments requires a functional assessment of multiple redundant DNA repair pathways. With the advent of whole-genome sequencing of cancer genomes, it is increasingly recognised that multiple signatures of mutational and chromosomal alterations can be correlated with specific DNA repair defects. The clinical relevance of this approach is underlined by the use of poly-(ADP-ribose) polymerase inhibitors (PARPi) in homologous recombination (HR) deficient high-grade serous ovarian cancers. Beyond deleterious mutations in HR-related genes such as BRCA1/2, it is recognised that HR deficiency endows ovarian cancers with specific signatures of base substitutions and structural chromosomal variation. Multiple metrics quantifying loss-of-heterozygosity (LOH) events were proposed and implemented in trials with PARPi. However, it was shown that some of the HR-deficient cases, i.e. CDK12-mutated tumours, were not associated with high LOH-based scores, but with distinct patterns of genomic alterations such as tandem duplication. Therefore, more complex signatures of structural genomic variation were identified and quantified. Ultimately, optimal prediction models for treatments targeting DNA repair will need to integrate multiples of these genomic signatures and will also need to assess multiple resistance mechanisms such as genomic reversion events that partially or fully re-activate DNA repair.