Purpose:The clinical significance of the p53-abnormal (p53abn) molecular subtype in stage I low-grade endometrioid endometrial carcinoma (EEC) is debated. We aimed to review pathologic and... Show morePurpose:The clinical significance of the p53-abnormal (p53abn) molecular subtype in stage I low-grade endometrioid endometrial carcinoma (EEC) is debated. We aimed to review pathologic and molecular characteristics, and outcomes of stage I low-grade p53abn EEC in a large international cohort.Experimental Design:Previously diagnosed stage I p53abn EC (POLE–wild-type, mismatch repair–proficient) low-grade EEC from Canadian retrospective cohorts and PORTEC-1&2 trials were included. Pathology review was performed by six expert gynecologic pathologists blinded to p53 status. IHC profiling, next-generation sequencing, and shallow whole-genome sequencing was performed. Kaplan–Meier method was used for survival analysis.Results:We identified 55 stage I p53abn low-grade EEC among 3,387 cases (2.5%). On pathology review, 17 cases (31%) were not diagnosed as low-grade EEC by any pathologists, whereas 26 cases (47%) were diagnosed as low-grade EEC by at least three pathologists. The IHC and molecular profile of the latter cases were consistent with low-grade EEC morphology (ER/PR positivity, patchy p16 expression, PIK3CA and PTEN mutations) but they also showed features of p53abn EC (TP53 mutations, many copy-number alterations). These cases had a clinically relevant risk of disease recurrence (5-year recurrence-free survival 77%), with pelvic and/or distant recurrences observed in 12% of the patients.Conclusions:A subset of p53abn EC is morphologically low-grade EEC and exhibit genomic instability. Even for stage I disease, p53abn low-grade EEC are at substantial risk of disease recurrence. These findings highlight the clinical relevance of universal p53-testing, even in low-grade EEC, to identify women at increased risk of recurrence. Show less
PURPOSEThe molecular classification of endometrial cancer (EC) has proven to have prognostic value and is predictive of response to adjuvant chemotherapy. Here, we investigate its predictive value... Show morePURPOSEThe molecular classification of endometrial cancer (EC) has proven to have prognostic value and is predictive of response to adjuvant chemotherapy. Here, we investigate its predictive value for response to external beam radiotherapy (EBRT) and vaginal brachytherapy (VBT) in early-stage endometrioid EC (EEC).METHODSData of the randomized PORTEC-1 trial (n = 714) comparing pelvic EBRT with no adjuvant therapy in early-stage intermediate-risk EC and the PORTEC-2 trial (n = 427) comparing VBT with EBRT in early-stage high-intermediate-risk EC were used. Locoregional (including vaginal and pelvic) recurrence-free survival was compared between treatment groups across the four molecular classes using Kaplan-Meier's methodology and log-rank tests.RESULTSA total of 880 molecularly classified ECs, 484 from PORTEC-1 and 396 from PORTEC-2, were included. The majority were FIGO-2009 stage I EEC (97.2%). The median follow-up was 11.3 years. No locoregional recurrences were observed in EC with a pathogenic mutation of DNA polymerase-ε (POLEmut EC). In mismatch repair–deficient (MMRd) EC, locoregional recurrence-free survival was similar after EBRT (94.2%), VBT (94.2%), and no adjuvant therapy (90.3%; P = .74). In EC with a p53 abnormality (p53abn EC), EBRT (96.9%) had a substantial benefit over VBT (64.3%) and no adjuvant therapy (72.2%; P = .048). In EC with no specific molecular profile (NSMP EC), both EBRT (98.3%) and VBT (96.2%) yielded better locoregional control than no adjuvant therapy (87.7%; P < .0001).CONCLUSIONThe molecular classification of EC predicts response to radiotherapy in stage I EEC and may guide adjuvant treatment decisions. Omitting radiotherapy seems to be safe in POLEmut EC. The benefit of radiotherapy seems to be limited in MMRd EC. EBRT yields a significantly better locoregional recurrence-free survival than VBT or no adjuvant therapy in p53abn EC. VBT is the treatment of choice for NSMP EC as it is as effective as EBRT and significantly better than no adjuvant therapy for locoregional tumor control. Show less
Background Endometrial cancer can be molecularly classified into POLEmut , mismatch repair deficient (MMRd), p53 abnormal (p53abn), and no specific molecular profile (NSMP) subgroups. We aimed to... Show moreBackground Endometrial cancer can be molecularly classified into POLEmut , mismatch repair deficient (MMRd), p53 abnormal (p53abn), and no specific molecular profile (NSMP) subgroups. We aimed to develop an interpretable deep learning pipeline for whole-slide-image-based prediction of the four molecular classes in endometrial cancer (im4MEC), to identify morpho-molecular correlates, and to refine prognostication. Methods This combined analysis included diagnostic haematoxylin and eosin-stained slides and molecular and clinicopathological data from 2028 patients with intermediate-to-high-risk endometrial cancer from the PORTEC-1 (n=466), PORTEC-2 (n=375), and PORTEC-3 (n=393) randomised trials and the TransPORTEC pilot study (n=110), the Medisch Spectrum Twente cohort (n=242), a case series of patients with POLEmut endometrial cancer in the Leiden Endometrial Cancer Repository (n=47), and The Cancer Genome Atlas-Uterine Corpus Endometrial Carcinoma cohort (n=395). PORTEC-3 was held out as an independent test set and a four-fold cross validation was performed. Performance was measured with the macro and class-wise area under the receiver operating characteristic curve (AUROC). Whole-slide images were segmented into tiles of 360 & mu;m resized to 224 x 224 pixels. im4MEC was trained to learn tile-level morphological features with self-supervised learning and to molecularly classify whole-slide images with an attention mechanism. The top 20 tiles with the highest attention scores were reviewed to identify morpho-molecular correlates. Predictions of a nuclear classification deep learning model serve to derive interpretable morphological features. We analysed 5-year recurrence-free survival and explored prognostic refinement by molecular class using the Kaplan-Meier method. Findings im4MEC attained macro-average AUROCs of 0 & BULL;874 (95% CI 0 & BULL;856-0 & BULL;893) on four-fold cross-validation and 0 & BULL;876 on the independent test set. The class-wise AUROCs were 0 & BULL;849 for POLEmut (n=51), 0 & BULL;844 for MMRd (n=134), 0 & BULL;883 for NSMP (n=120), and 0 & BULL;928 for p53abn (n=88). POLEmut and MMRd tiles had a high density of lymphocytes, p53abn tiles had strong nuclear atypia, and the morphology of POLEmut and MMRd endometrial cancer overlapped. im4MEC highlighted a low tumour-to-stroma ratio as a potentially novel characteristic feature of the NSMP class. 5-year recurrence-free survival was significantly different between im4MEC predicted molecular classes in PORTEC-3 (log-rank p<0 & BULL;0001). The ten patients with aggressive p53abn endometrial cancer that was predicted as MMRd showed inflammatory morphology and appeared to have a better prognosis than patients with correctly predicted p53abn endometrial cancer (p=0 & BULL;30). The four patients with NSMP endometrial cancer that was predicted as p53abn showed higher nuclear atypia and appeared to have a worse prognosis than patients with correctly predicted NSMP (p=0 & BULL;13). Patients with MMRd endometrial cancer predicted as POLEmut had an excellent prognosis, as do those with true POLEmut endometrial cancer. Interpretation We present the first interpretable deep learning model, im4MEC, for haematoxylin and eosin-based prediction of molecular endometrial cancer classification. im4MEC robustly identified morpho-molecular correlates and could enable further prognostic refinement of patients with endometrial cancer. Copyright & COPY; 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Show less
Background: Risk-assessment of endometrial cancer (EC) is based on clinicopathological factors and molecular subgroup. It is unclear whether adding hormone receptor expression, L1CAM expression or... Show moreBackground: Risk-assessment of endometrial cancer (EC) is based on clinicopathological factors and molecular subgroup. It is unclear whether adding hormone receptor expression, L1CAM expression or CTNNB1 status yields prognostic refinement. Methods: Paraffin-embedded tumour samples of women with high-risk EC (HR-EC) from the PORTEC-3 trial (n = 424), and a Dutch prospective clinical cohort called MST (n = 256), were used. All cases were molecularly classified. Expression of L1CAM, ER and PR were analysed by whole-slide immunohistochemistry and CTNNB1 mutations were assessed with a next-generation sequencing. Kaplan-Meier method, log-rank tests and Cox's proportional hazard models were used for survival analysis. Results: In total, 648 HR-EC were included. No independent prognostic value of ER, PR, L1CAM, and CTNNB1 was found, while age, stage, and adjuvant chemotherapy had an independent impact on risk of recurrence. Subgroup-analysis showed that only in NSMP HR-EC, ER-positivity was independently associated with a reduced risk of recurrence (HR 0.33, 95%CI 0.15-0.75). Conclusions: We confirmed the prognostic impact of the molecular classification, age, stage, and adjuvant CTRT in a large cohort of high-risk EC. ER-positivity is a strong favourable prognostic factor in NSMP HR-EC and identifies a homogeneous subgroup of NSMP tumours. Assessment of ER status in high-risk NSMP EC is feasible in clinical practice and could improve risk stratification and treatment. Show less
Randomized controlled trials (RCTs) are considered the gold standard for testing causal hypotheses in the clinical domain; however, the investigation of prognostic variables of patient outcome in a... Show moreRandomized controlled trials (RCTs) are considered the gold standard for testing causal hypotheses in the clinical domain; however, the investigation of prognostic variables of patient outcome in a hypothesized cause-effect route is not feasible using standard statistical methods. Here we propose a new automated causal inference method (AutoCI) built on the invariant causal prediction (ICP) framework for the causal reinterpretation of clinical trial data. Compared with existing methods, we show that the proposed AutoCI allows one to clearly determine the causal variables of two real-world RCTs of patients with endometrial cancer with mature outcome and extensive clinicopathological and molecular data. This is achieved via suppressing the causal probability of non-causal variables by a wide margin. In ablation studies, we further demonstrate that the assignment of causal probabilities by AutoCI remains consistent in the presence of confounders. In conclusion, these results confirm the robustness and feasibility of AutoCI for future applications in real-world clinical analysis.The invariant causal prediction (ICP) framework tries to determine the causal variables given an outcome variable, but considerable effort is needed to adapt existing ICP methods to the clinical domain. The authors propose an automated causal inference method that could potentially address the challenges of applying the ICP framework to complex clinical datasets. Show less
Objective: Microcystic, elongated fragmented (MELF) pattern of myometrial invasion is a distinct histologic feature occasionally seen in low-grade endometrial carcinomas (EC). The prognostic... Show moreObjective: Microcystic, elongated fragmented (MELF) pattern of myometrial invasion is a distinct histologic feature occasionally seen in low-grade endometrial carcinomas (EC). The prognostic relevance of MELF invasion was uncertain due to conflicting data, and it had not yet appropriately been studied in the context of the molecular EC classification. We aimed to determine the relation of MELF invasion with clinicopathological and molecular characteristics, and define its prognostic relevance in early-stage low/intermediate risk EC. Methods: Single whole tumor slides of 979 (85.8%) out of 1141 (high)intermediate-risk EC of women who participated in the PORTEC-1/−2 trials were available for review. Clinicopathological and molecular features were compared between MELF invasion positive and negative cases. Time-to-event analyses were done by Kaplan-Meier method, log-rank tests and Cox’ proportional hazards models. Results: MELF invasion was found in 128 (13.1%) cases, and associated with grade 1–2 histology, deep myometrial invasion and substantial lymph-vascular space invasion (LVSI). 85.6% of MELF invasion positive tumors were no-specific-molecular-profile (NSMP) EC. NSMP EC with MELF invasion were CTNNB1 wild type in 92.2% and KRAS mutated in 24.4% of cases. Risk of recurrence was lower for MELF invasion positive as compared to MELF invasion negative cases (4.9% vs. 12.7%, p = 0.026). However, MELF invasion had no independent impact on risk of recurrence (HR 0.65, p = 0.30) after correction for clinicopathological and molecular factors. Conclusions: MELF invasion has no independent impact on risk of recurrence in early-stage EC, and is frequently observed in low-grade NSMP tumors. Routine assessment of MELF invasion has no clinical implications and is not recommended. Show less
Aims: To investigate whether the Geriatric 8 (G8) score and the Timed Get Up and Go Test (TGUGT), together with clinical and demographic patient characteristics, are associated with survival and... Show moreAims: To investigate whether the Geriatric 8 (G8) score and the Timed Get Up and Go Test (TGUGT), together with clinical and demographic patient characteristics, are associated with survival and late toxicity after (chemo)radiation therapy, administered with curative intent in older patients with cancer.Materials and methods: Four hundred and two patients aged similar to 65 years (median age 72 years, range 65-96 years), diagnosed with either breast, non-small cell lung, prostate, head and neck, rectal or oesophageal cancer, and referred for curative (chemo)radiation therapy, took part in a multicentre prospective cohort study in eight radiotherapy centres in the Netherlands. The G8 and TGUGT scores were assessed before starting treatment. Other potential predictors and late toxicity were also recorded. Survival status and date of death, if applicable, were ascertained at the Dutch national death registry.Results: After 2.5 years, the overall survival was 83%. Survival was 87% for patients with high G8 scores and 55% for patients with low G8 scores (Log-rank P value < 0.0001). Survival was 77% for patients with good TGUGT results and 50% for patients with poor TGUGT results (Log-rank P value < 0.001). In multi-variable analysis, in addition to age and type of primary tumour, the association of the G8 score with overall survival remained, with a hazard ratio of 2.1 (95% confidence interval 1.2-3.8) for low versus high scores.Conclusions: G8 was associated with overall survival in older patients with cancer irradiated with curative intent. This association was independent of the predictive value of age and primary tumour. (C) 2020 The Royal College of Radiologists. Published by Elsevier Ltd. Show less
Optimum risk stratification in early-stage endometrial cancer combines clinicopathologic factors and the molecular endometrial cancer classification defined by The Cancer Genome Atlas (TCGA). It is... Show moreOptimum risk stratification in early-stage endometrial cancer combines clinicopathologic factors and the molecular endometrial cancer classification defined by The Cancer Genome Atlas (TCGA). It is unclear whether analysis of intratumoral immune infiltrate improves this. We developed a machine-learning, image-based algorithm to quantify density of CD8(+) and CD103(+) immune cells in tumor epithelium and stroma in 695 stage I endometrioid endometrial cancers from the PORTEC-1 and -2 trials. The relationship between immune cell density and clinicopathologic/molecular factors was analyzed by hierarchical clustering and multiple regression. The prognostic value of immune infiltrate by cell type and location was analyzed by univariable and multivariable Cox regression, incorporating the molecular endometrial cancer classification. Tumor-infiltrating immune cell density varied substantially between cases, and more modestly by immune cell type and location. Clustering revealed three groups with high, intermediate, and low densities, with highly significant variation in the proportion of molecular endometrial cancer subgroups between them. Univariable analysis revealed intraepithelial CD8(+) cell density as the strongest predictor of endometrial cancer recurrence; multivariable analysis confirmed this was independent of pathologic factors and molecular subgroup. Exploratory analysis suggested this association was not uniform across molecular subgroups, but greatest in tumors with mutant p53 and absent in DNA mismatch repair-deficient cancers. Thus, this work identified that quantification of intraepithelial CD8thorn cells improved upon the prognostic utility of the molecular endometrial cancer classification in early-stage endometrial cancer. Show less
Objective: To investigate the effects of different types of surgery on breast cancer prognosis in germline BRCA1/BRCA2 mutation carriers compared with noncarriers.Summary of Background Data:... Show moreObjective: To investigate the effects of different types of surgery on breast cancer prognosis in germline BRCA1/BRCA2 mutation carriers compared with noncarriers.Summary of Background Data: Although breast-conserving therapy (breast-conserving surgery followed by radiotherapy) has been associated with more local recurrences than mastectomy, no differences in overall survival have been found in randomized trials performed in the general breast cancer population. Whether breast-conservation can be safely offered to BRCA1/2 mutation carriers is debatable.Methods: The study comprised a cohort of women with invasive breast cancer diagnosed <50 years and treated between 1970 and 2003 in 10 Dutch centers. Germline DNA for BRCA1/2 testing of most-prevalent mutations covering similar to 61%) was mainly derived from paraffin-blocks. Survival analyses were performed taking into account competing risks.Results: In noncarriers (N = 5820), as well as in BRCA1 (N = 191) and BRCA2 (N = 70) mutation carriers, approximately half of the patients received breast-conserving therapy. Patients receiving mastectomy followed by radiotherapy had prognostically worse tumor characteristics and more often received systemic therapy. After adjustment for these potential confounders, patients who received breast-conserving therapy had a similar overall survival compared with patients who received mastectomy, both in noncarriers (hazard ratio [HR] = 0.95, confidence interval [CI] = 0.85-1.07, P = 0.41) and BRCA1 mutation carriers (HR = 0.80, CI = 0.42-1.51, P = 0.50). Numbers for BRCA2 were insufficient to draw conclusions. The rate of local recurrences after breast-conserving therapy did not differ between BRCA1 carriers (10-year risk = 7.3%) and noncarriers (10-year risk = 7.9%).Conclusion: Our results, together with the available literature, provide reassurance that breast-conserving therapy is a safe local treatment option to offer to BRCA1 mutation carriers with invasive breast cancer. Show less
