Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer.

Cervical cancer (CC) is a major global health problem with 570,000 new cases and 266,000 deaths annually. Prognosis is poor for advanced stage disease, and few effective treatments exist. Preoperative diagnostic imaging is common in high-income countries and MRI measured tumor size routinely guides treatment allocation of cervical cancer patients. Recently, the role of MRI radiomics has been recognized. However, its potential to independently predict survival and treatment response requires further clarification. This retrospective cohort study demonstrates how non-invasive, preoperative, MRI radiomic profiling may improve prognostication and tailoring of treatments and follow-ups for cervical cancer patients. By unsupervised clustering based on 293 radiomic features from 132 patients, we identify three distinct clusters comprising patients with significantly different risk profiles, also when adjusting for FIGO stage and age. By linking their radiomic profiles to genomic alterations, we identify putative treatment targets for the different patient clusters (e.g., immunotherapy, CDK4/6 and YAP-TEAD inhibitors and p53 pathway targeting treatments).

Clinicopathological and radiological stratification within FIGO 2018 stages improves risk-prediction in cervical cancer.

OBJECTIVE: Assess the added prognostic value of the updated International Federation of Gynecology and Obstetrics (FIGO) 2018 staging system, and to identify clinicopathological and radiological biomarkers for improved FIGO 2018 prognostication. METHODS: Patient data were retrieved from a prospectively collected patient cohort including all consenting patients with cervical cancer diagnosed and treated at Haukeland University Hospital during 2001-2022 (n = 948). All patients were staged according to the FIGO 2009 and FIGO 2018 guidelines based on available data for individual patients. MRI-assessed maximum tumor diameter and stromal tumor invasion, as well as histopathologically assessed lymphovascular space invasion were applied to categorize patients according to the Sedlis criteria. RESULTS: FIGO 2018 stage yielded the highest area under the receiver operating characteristic (ROC) curve (AUC) (0.86 versus 0.81 for FIGO 2009) for predicting disease-specific survival. The most common stage migration in FIGO 2018 versus FIGO 2009 was upstaging from stages IB/II to stage IIIC due to suspicious lymph nodes identified by PET/CT and/or MRI. In FIGO 2018 stage III patients, extent and size of primary tumor (p = 0.04), as well as its histological type (p = 0.003) were highly prognostic. Sedlis criteria were prognostic within FIGO 2018 IB patients (p = 0.04). CONCLUSIONS: Incorporation of cross-sectional imaging increases prognostic precision, as suggested by the FIGO 2018 guidelines. The 2018 FIGO IIIC stage could be refined by including the size and extent of primary tumor and histological type. The FIGO IB risk prediction could be improved by applying MRI-assessed tumor size and stromal invasion.

Visceral fat percentage for prediction of outcome in uterine cervical cancer.

OBJECTIVE: The prognostic role of adiposity in uterine cervical cancer (CC) is largely unknown. Abdominal fat distribution may better reflect obesity than body mass index. This study aims to describe computed tomography (CT)-assessed abdominal fat distribution in relation to clinicopathologic characteristics, survival, and tumor gene expression in CC. METHODS: The study included 316 CC patients diagnosed during 2004-2017 who had pre-treatment abdominal CT. CT-based 3D segmentation of total-, subcutaneous- and visceral abdominal fat volumes (TAV, SAV and VAV) allowed for calculation of visceral fat percentage (VAV% = VAV/TAV). Liver density (LD) and waist circumference (at L3/L4-level) were also measured. Associations between CT-derived adiposity markers, clinicopathologic characteristics and disease-specific survival (DSS) were explored. Gene set enrichment of primary tumors were examined in relation to fat distribution in a subset of 108 CC patients. RESULTS: High TAV, VAV and VAV% and low LD were associated with higher age (≥44 yrs.; p ≤ 0.017) and high International Federation of Gynecology and Obstetrics (FIGO) (2018) stage (p ≤ 0.01). High VAV% was the only CT-marker predicting high-grade histology (p = 0.028), large tumor size (p = 0.016) and poor DSS (HR 1.07, p < 0.001). Patients with high VAV% had CC tumors that exhibited increased inflammatory signaling (false discovery rate [FDR] < 5%). CONCLUSIONS: High VAV% is associated with high-risk clinical features and predicts reduced DSS in CC patients. Furthermore, patients with high VAV% had upregulated inflammatory tumor signaling, suggesting that the metabolic environment induced by visceral adiposity contributes to tumor progression in CC.

Preoperative pelvic MRI and 2-[18F]FDG PET/CT for lymph node staging and prognostication in endometrial cancer-time to revisit current imaging guidelines?

OBJECTIVE: This study presents the diagnostic performance of four different preoperative imaging workups (IWs) for prediction of lymph node metastases (LNMs) in endometrial cancer (EC): pelvic MRI alone (IW1), MRI and [18F]FDG-PET/CT in all patients (IW2), MRI with selective [18F]FDG-PET/CT if high-risk preoperative histology (IW3), and MRI with selective [18F]FDG-PET/CT if MRI indicates FIGO stage ≥ 1B (IW4). METHODS: In 361 EC patients, preoperative staging parameters from both pelvic MRI and [18F]FDG-PET/CT were recorded. Area under receiver operating characteristic curves (ROC AUC) compared the diagnostic performance for the different imaging parameters and workups for predicting surgicopathological FIGO stage. Survival data were assessed using Kaplan-Meier estimator with log-rank test. RESULTS: MRI and [18F]FDG-PET/CT staging parameters yielded similar AUCs for predicting corresponding FIGO staging parameters in low-risk versus high-risk histology groups (p ≥ 0.16). The sensitivities, specificities, and AUCs for LNM prediction were as follows: IW1-33% [9/27], 95% [185/193], and 0.64; IW2-56% [15/27], 90% [174/193], and 0.73 (p = 0.04 vs. IW1); IW3-44% [12/27], 94% [181/193], and 0.69 (p = 0.13 vs. IW1); and IW4-52% [14/27], 91% [176/193], and 0.72 (p = 0.06 vs. IW1). IW3 and IW4 selected 34% [121/361] and 54% [194/361] to [18F]FDG-PET/CT, respectively. Employing IW4 identified three distinct patient risk groups that exhibited increasing FIGO stage (p < 0.001) and stepwise reductions in survival (p ≤ 0.002). CONCLUSION: Selective [18F]FDG-PET/CT in patients with high-risk MRI findings yields better detection of LNM than MRI alone, and similar diagnostic performance to that of MRI and [18F]FDG-PET/CT in all. KEY POINTS: • Imaging by MRI and [18F]FDG PET/CT yields similar diagnostic performance in low- and high-risk histology groups for predicting central FIGO staging parameters. • Utilizing a stepwise imaging workup with MRI in all patients and [18F]FDG-PET/CT in selected patients based on MRI findings identifies preoperative risk groups exhibiting significantly different survival. • The proposed imaging workup selecting ~54% of the patients to [18F]FDG-PET/CT yield better detection of LNMs than MRI alone, and similar LNM detection to that of MRI and [18F]FDG-PET/CT in all.

What MRI-based tumor size measurement is best for predicting long-term survival in uterine cervical cancer?

BACKGROUND: Tumor size assessment by MRI is central for staging uterine cervical cancer. However, the optimal role of MRI-derived tumor measurements for prognostication is still unclear. MATERIAL AND METHODS: This retrospective cohort study included 416 women (median age: 43 years) diagnosed with cervical cancer during 2002-2017 who underwent pretreatment pelvic MRI. The MRIs were independently read by three radiologists, measuring maximum tumor diameters in three orthogonal planes and maximum diameter irrespective of plane (MAXimaging). Inter-reader agreement for tumor size measurements was assessed by intraclass correlation coefficients (ICCs). Size was analyzed in relation to age, International Federation of Gynecology and Obstetrics (FIGO) (2018) stage, histopathological markers, and disease-specific survival using Kaplan-Meier-, Cox regression-, and time-dependent receiver operating characteristics (tdROC) analyses. RESULTS: All MRI tumor size variables (cm) yielded high areas under the tdROC curves (AUCs) for predicting survival (AUC 0.81-0.84) at 5 years after diagnosis and predicted outcome (hazard ratios [HRs] of 1.42-1.76, p < 0.001 for all). Only MAXimaging independently predicted survival (HR = 1.51, p = 0.03) in the model including all size variables. The optimal cutoff for maximum tumor diameter (≥ 4.0 cm) yielded sensitivity (specificity) of 83% (73%) for predicting disease-specific death after 5 years. Inter-reader agreement for MRI-based primary tumor size measurements was excellent, with ICCs of 0.83-0.85. CONCLUSION: Among all MRI-derived tumor size measurements, MAXimaging was the only independent predictor of survival. MAXimaging ≥ 4.0 cm represents the optimal cutoff for predicting long-term disease-specific survival in cervical cancer. Inter-reader agreement for MRI-based tumor size measurements was excellent.

Interobserver agreement and prognostic impact for MRI-based 2018 FIGO staging parameters in uterine cervical cancer.

OBJECTIVES: To evaluate the interobserver agreement for MRI-based 2018 International Federation of Gynecology and Obstetrics (FIGO) staging parameters in patients with cervical cancer and assess the prognostic value of these MRI parameters in relation to other clinicopathological markers. METHODS: This retrospective study included 416 women with histologically confirmed cervical cancer who underwent pretreatment pelvic MRI from May 2002 to December 2017. Three radiologists independently recorded MRI-derived staging parameters incorporated in the 2018 FIGO staging system. Kappa coefficients (κ) for interobserver agreement were calculated. The predictive and prognostic values of the MRI parameters were explored using ROC analyses and Kaplan-Meier with log-rank tests, and analyzed in relation to clinicopathological patient characteristics. RESULTS: Overall agreement was substantial for the staging parameters: tumor size > 2 cm (κ = 0.80), tumor size > 4 cm (κ = 0.76), tumor size categories (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) (κ = 0.78), parametrial invasion (κ = 0.63), vaginal invasion (κ = 0.61), and enlarged lymph nodes (κ = 0.63). Higher MRI-derived tumor size category (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) was associated with a stepwise reduction in survival (p ≤ 0.001 for all). Tumor size > 4 cm and parametrial invasion at MRI were associated with aggressive clinicopathological features, and the incorporation of these MRI-based staging parameters improved risk stratification when compared to corresponding clinical assessments alone. CONCLUSION: The interobserver agreement for central MRI-derived 2018 FIGO staging parameters was substantial. MRI improved the identification of patients with aggressive clinicopathological features and poor survival, demonstrating the potential impact of MRI enabling better prognostication and treatment tailoring in cervical cancer. KEY POINTS: • The overall interobserver agreement was substantial (κ values 0.61-0.80) for central MRI staging parameters in the 2018 FIGO system. • Higher MRI-derived tumor size category was linked to a stepwise reduction in survival (p ≤ 0.001 for all). • MRI-derived tumor size > 4 cm and parametrial invasion were associated with aggressive clinicopathological features, and the incorporation of these MRI-derived staging parameters improved risk stratification when compared to clinical assessments alone.

Longitudinal effects of adjuvant chemotherapy and lymph node staging on patient-reported outcomes in endometrial cancer survivors: a prospective cohort study.

BACKGROUND: Most patients with endometrial cancer with localized disease are effectively treated and survive for a long time. The primary treatment is hysterectomy, to which surgical staging procedures may be added to assess the need for adjuvant therapy. Longitudinal data on patient-reported outcomes comparing different levels of primary treatment are lacking, especially when adjuvant radiotherapy is omitted. OBJECTIVE: We assessed the impact of lymphadenectomy and adjuvant chemotherapy on patient-reported symptoms, function, and quality of life. We hypothesized that these treatment modalities would substantially affect patient-reported outcomes at follow-up. STUDY DESIGN: We prospectively included patients with endometrial cancer enrolled in the ongoing MoMaTEC2 study (ClinicalTrials.gov Identifier: NCT02543710). Patients were asked to complete the patient-reported outcome questionnaires European Organization for Research and Treatment of Cancer Quality of Life Questionnaire C30 and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire EN24 preoperatively and at 1 and 2 years of follow-up. Functional domains and symptoms were analyzed for the whole cohort and by treatment received. To assess the effect of the individual treatment modifications, we used mixed regression models. RESULTS: Baseline data were available for 448 patients. Of these patients, 339 and 219 had reached 1-year follow-up and 2-year follow-up, respectively. Treatment included hysterectomy (plus bilateral salpingo-oophorectomy) alone (n=177), hysterectomy and lymph node staging without adjuvant therapy (n=133), or adjuvant chemotherapy irrespective of staging procedure (n=138). Overall, patients reported improved global health status and quality of life (+9 units; P<.001), increased emotional and social functioning, and increased sexual interest and activity (P<.001 for all) from baseline to year 1, and these outcomes remained stable at year 2. Means of functional scales and quality of life were similar to age- and sex-weighted reference cohorts. Mean tingling and numbness and lymphedema increased after treatment. The group who received adjuvant chemotherapy had a larger mean reduction in physical functioning (-6 vs +2; P=.002) at year 1, more neuropathy (+30 vs +5; P<.001; year 1) at years 1 and 2, and more lymphedema at year 1 (+11 vs +2; P=.007) than the group treated with hysterectomy and salpingo-oophorectomy only. In patients not receiving adjuvant chemotherapy, patient-reported outcomes were similar regardless of lymph node staging procedures. Adjuvant chemotherapy independently increased fatigue, lymphedema, and neuropathy in mixed regression models. CONCLUSION: Patients with endometrial cancer receiving adjuvant chemotherapy reported significantly reduced functioning and more symptoms up to 2 years after treatment. For patients treated by surgery alone, surgical staging did not seem to affect the quality of life or symptoms to a measurable degree at follow-up. Therefore, subjecting patients to lymph node removal to tailor adjuvant therapy seems justified from the patient's viewpoint; however, efforts should increase to find alternatives to traditional chemotherapy.

A Gene Signature Identifying CIN3 Regression and Cervical Cancer Survival.

The purpose of this study was to establish a gene signature that may predict CIN3 regression and that may aid in selecting patients who may safely refrain from conization. Oncomine mRNA data including 398 immune-related genes from 21 lesions with confirmed regression and 28 with persistent CIN3 were compared. L1000 mRNA data from a cervical cancer cohort was available for validation (n = 239). Transcriptomic analyses identified TDO2 (p = 0.004), CCL5 (p < 0.001), CCL3 (p = 0.04), CD38 (p = 0.02), and PRF1 (p = 0.005) as upregulated, and LCK downregulated (p = 0.01) in CIN3 regression as compared to persistent CIN3 lesions. From these, a gene signature predicting CIN3 regression with a sensitivity of 91% (AUC = 0.85) was established. Transcriptomic analyses revealed proliferation as significantly linked to persistent CIN3. Within the cancer cohort, high regression signature score associated with immune activation by Gene Set enrichment Analyses (GSEA) and immune cell infiltration by histopathological evaluation (p < 0.001). Low signature score was associated with poor survival (p = 0.007) and large tumors (p = 0.01). In conclusion, the proposed six-gene signature predicts CIN regression and favorable cervical cancer prognosis and points to common drivers in precursors and cervical cancer lesions.

Risk Stratification of Endometrial Cancer Patients: FIGO Stage, Biomarkers and Molecular Classification.

Endometrial cancer (EC) is the most common gynaecologic malignancy in developed countries. The main challenge in EC management is to correctly estimate the risk of metastases at diagnosis and the risk to develop recurrences in the future. Risk stratification determines the need for surgical staging and adjuvant treatment. Detection of occult, microscopic metastases upstages patients, provides important prognostic information and guides adjuvant treatment. The molecular classification subdivides EC into four prognostic subgroups: POLE ultramutated; mismatch repair deficient (MMRd); nonspecific molecular profile (NSMP); and TP53 mutated (p53abn). How surgical staging should be adjusted based on preoperative molecular profiling is currently unknown. Moreover, little is known whether and how other known prognostic biomarkers affect prognosis prediction independent of or in addition to these molecular subgroups. This review summarizes the factors incorporated in surgical staging (i.e., peritoneal washing, lymph node dissection, omentectomy and peritoneal biopsies), and its impact on prognosis and adjuvant treatment decisions in an era of molecular classification of EC. Moreover, the relation between FIGO stage and molecular classification is evaluated including the current gaps in knowledge and future perspectives.

Impact of hormonal biomarkers on response to hormonal therapy in advanced and recurrent endometrial cancer.

BACKGROUND: Approximately 20% of women with endometrial cancer have advanced-stage disease or suffer from a recurrence. For these women, prognosis is poor, and palliative treatment options include hormonal therapy and chemotherapy. Lack of predictive biomarkers and suboptimal use of existing markers for response to hormonal therapy have resulted in overall limited efficacy. OBJECTIVE: This study aimed to improve the efficacy of hormonal therapy by relating immunohistochemical expression of estrogen and progesterone receptors and estrogen receptor pathway activity scores to response to hormonal therapy. STUDY DESIGN: Patients with advanced or recurrent endometrial cancer and available biopsies taken before the start of hormonal therapy were identified in 16 centers within the European Network for Individualized Treatment in Endometrial Cancer and the Dutch Gynecologic Oncology Group. Tumor tissue was analyzed for estrogen and progesterone receptor expressions and estrogen receptor pathway activity using a quantitative polymerase chain reaction-based messenger RNA model to measure the activity of estrogen receptor-related target genes in tumor RNA. The primary endpoint was response rate defined as complete and partial response using the Response Evaluation Criteria in Solid Tumors. The secondary endpoints were clinical benefit rate and progression-free survival. RESULTS: Pretreatment biopsies with sufficient endometrial cancer tissue and complete response evaluation were available in 81 of 105 eligible cases. Here, 22 of 81 patients (27.2%) with a response had estrogen and progesterone receptor expressions of >50%, resulting in a response rate of 32.3% (95% confidence interval, 20.9-43.7) for an estrogen receptor expression of >50% and 50.0% (95% confidence interval, 35.2-64.8) for a progesterone receptor expression of >50%. Clinical benefit rate was 56.9% for an estrogen receptor expression of >50% (95% confidence interval, 44.9-68.9) and 75.0% (95% confidence interval, 62.2-87.8) for a progesterone receptor expression of >50%. The application of the estrogen receptor pathway test to cases with a progesterone receptor expression of >50% resulted in a response rate of 57.6% (95% confidence interval, 42.1-73.1). After 2 years of follow-up, 34.3% of cases (95% confidence interval, 20-48) with a progesterone receptor expression of >50% and 35.8% of cases (95% confidence interval, 20-52) with an estrogen receptor pathway activity score of >15 had not progressed. CONCLUSION: The prediction of response to hormonal treatment in endometrial cancer improves substantially with a 50% cutoff level for progesterone receptor immunohistochemical expression and by applying a sequential test algorithm using progesterone receptor immunohistochemical expression and estrogen receptor pathway activity scores. However, results need to be validated in the prospective Prediction of Response to Hormonal Therapy in Advanced and Recurrent Endometrial Cancer (PROMOTE) study.

A 10-gene prognostic signature points to LIMCH1 and HLA-DQB1 as important players in aggressive cervical cancer disease.

BACKGROUND: Advanced cervical cancer carries a particularly poor prognosis, and few treatment options exist. Identification of effective molecular markers is vital to improve the individualisation of treatment. We investigated transcriptional data from cervical carcinomas related to patient survival and recurrence to identify potential molecular drivers for aggressive disease. METHODS: Primary tumour RNA-sequencing profiles from 20 patients with recurrence and 53 patients with cured disease were compared. Protein levels and prognostic impact for selected markers were identified by immunohistochemistry in a population-based patient cohort. RESULTS: Comparison of tumours relative to recurrence status revealed 121 differentially expressed genes. From this gene set, a 10-gene signature with high prognostic significance (p = 0.001) was identified and validated in an independent patient cohort (p = 0.004). Protein levels of two signature genes, HLA-DQB1 (n = 389) and LIMCH1 (LIM and calponin homology domain 1) (n = 410), were independent predictors of survival (hazard ratio 2.50, p = 0.007 for HLA-DQB1 and 3.19, p = 0.007 for LIMCH1) when adjusting for established prognostic markers. HLA-DQB1 protein expression associated with programmed death ligand 1 positivity (p < 0.001). In gene set enrichment analyses, HLA-DQB1high tumours associated with immune activation and response to interferon-γ (IFN-γ). CONCLUSIONS: This study revealed a 10-gene signature with high prognostic power in cervical cancer. HLA-DQB1 and LIMCH1 are potential biomarkers guiding cervical cancer treatment.

Cancer awareness in the general population varies with sex, age and media coverage: A population-based survey with focus on gynecologic cancers.

OBJECTIVES: There is a need for more knowledge about the public awareness and attitudes towards gynecologic cancers. We employed a research-purpose population-based citizen panel to assess how often people recall gynecologic cancers compared to other cancer types and to explore the relative importance of different information channels in relaying cancer information. STUDY DESIGN: We conducted an online survey using the Norwegian Citizen Panel (n = 1441 respondents), exploring associations between demographic factors and frequency of mentioning specific cancer types. We also searched The Norwegian Media Archive to assess the media coverage of different cancer types. Factors affecting likelihood of mentioning different cancers were assessed by multivariate regression. RESULTS: Only 41 % of respondents listed one or more cancers in female genital organs. Of the gynecological cancers, cervical cancer was most frequently mentioned (28 %), followed by ovarian (12 %) and endometrial cancer (11 %). Female responders were more likely to mention cervical (OR 2.47, 95 % CI 2.16-2.78) and ovarian cancer (OR 2.09, 95 % CI 1.60-2.58) than male responders, but not endometrial cancer. Family and friends who have had cancer (50 %) and different types of media coverage (41 %) were reported as the most common sources of cancer information. The three most frequently mentioned cancer types in our survey were breast (77 %), hematologic (76 %) and lung cancer (75 %), which also were the cancer types having most media coverage. CONCLUSIONS: Gynecological cancers are less frequently mentioned by Norwegian citizens when compared to several other cancer types such as breast-, hematologic- and lung cancer. Sex and age are important factors that affect awareness of cancer types. Media is likely to play an important role in what cancer types the public recalls.