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.

MRI-based radiomic signatures for pretreatment prognostication in cervical cancer.

BACKGROUND: Accurate pretherapeutic prognostication is important for tailoring treatment in cervical cancer (CC). PURPOSE: To investigate whether pretreatment MRI-based radiomic signatures predict disease-specific survival (DSS) in CC. STUDY TYPE: Retrospective. POPULATION: CC patients (n = 133) allocated into training(T) (nT = 89)/validation(V) (nV = 44) cohorts. FIELD STRENGTH/SEQUENCE: T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) at 1.5T or 3.0T. ASSESSMENT: Radiomic features from segmented tumors were extracted from T2WI and DWI (high b-value DWI and apparent diffusion coefficient (ADC) maps). STATISTICAL TESTS: Radiomic signatures for prediction of DSS from T2WI (T2rad ) and T2WI with DWI (T2 + DWIrad ) were constructed by least absolute shrinkage and selection operator (LASSO) Cox regression. Area under time-dependent receiver operating characteristics curves (AUC) were used to evaluate and compare the prognostic performance of the radiomic signatures, MRI-derived maximum tumor size ≤/> 4 cm (MAXsize ), and 2018 International Federation of Gynecology and Obstetrics (FIGO) stage (I-II/III-IV). Survival was analyzed using Cox model estimating hazard ratios (HR) and Kaplan-Meier method with log-rank tests. RESULTS: The radiomic signatures T2rad and T2 + DWIrad yielded AUCT /AUCV of 0.80/0.62 and 0.81/0.75, respectively, for predicting 5-year DSS. Both signatures yielded better or equal prognostic performance to that of MAXsize (AUCT /AUCV : 0.69/0.65) and FIGO (AUCT /AUCV : 0.77/0.64) and were significant predictors of DSS after adjusting for FIGO (HRT /HRV for T2rad : 4.0/2.5 and T2 + DWIrad : 4.8/2.1). Adding T2rad and T2 + DWIrad to FIGO significantly improved DSS prediction compared to FIGO alone in cohort(T) (AUCT 0.86 and 0.88 vs. 0.77), and FIGO with T2 + DWIrad tended to the same in cohort(V) (AUCV 0.75 vs. 0.64, p = 0.07). High radiomic score for T2 + DWIrad was significantly associated with reduced DSS in both cohorts. DATA CONCLUSION: Radiomic signatures from T2WI and T2WI with DWI may provide added value for pretreatment risk assessment and for guiding tailored treatment strategies in CC.

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.

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.

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.

Genomic alterations associated with mutational signatures, DNA damage repair and chromatin remodeling pathways in cervical carcinoma.

Despite recent advances in the prevention of cervical cancer, the disease remains a leading cause of cancer-related deaths in women worldwide. By applying the GISTIC2.0 and/or the MutSig2CV algorithms on 430 whole-exome-sequenced cervical carcinomas, we identified previously unreported significantly mutated genes (SMGs) (including MSN, GPX1, SPRED3, FAS, and KRT8), amplifications (including NFIA, GNL1, TGIF1, and WDR87) and deletions (including MIR562, PVRL1, and NTM). Subset analyses of 327 squamous cell carcinomas and 86 non-squamous cell carcinomas revealed previously unreported SMGs in BAP1 and IL28A, respectively. Distinctive copy number alterations related to tumors predominantly enriched for *CpG- and Tp*C mutations were observed. CD274, GRB2, KRAS, and EGFR were uniquely significantly amplified within the Tp*C-enriched tumors. A high frequency of aberrations within DNA damage repair and chromatin remodeling genes were detected. Facilitated by the large sample size derived from combining multiple datasets, this study reveals potential targets and prognostic markers for cervical cancer.

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.

Clinicopathologic and molecular markers in cervical carcinoma: a prospective cohort study.

BACKGROUND: Cervical cancer is a major health problem worldwide. Identification of effective clinicopathologic and molecular markers is vital to improve treatment stratification. OBJECTIVES: The purpose of this study was to validate a set of well-defined clinicopathologic features in a large population-based, prospectively collected cervical cancer cohort to support their use in the clinic. Further, we explored p53 and human epidermal growth factor receptor 2 as potential prognostic markers in cervical cancer. STUDY DESIGN: Tissue was collected from 401 patients with cervical cancer. Clinical data that included follow-up evaluations were collected from patient journals. Histopathologic data were evaluated and revised by an expert pathologist. The prognostic impact of selected clinicopathologic variables was analyzed in the whole cohort. Tissue microarrays were prepared from 292 carcinomas, and p53 and human epidermal growth factor receptor 2 protein levels were evaluated by immunohistochemistry. Fresh frozen samples from overlapping cervical carcinomas previously were subjected to human papilloma virus typing (n=94), whole exome (n=100) and RNA (n=79) sequencing; the results were available for our analyses. RESULTS: Among the clinicopathologic variables, vascular space invasion, histologic type, and tumor size were verified as strong independent prognostic markers. High p53 protein levels were associated significantly with markers for aggressive phenotype and survival, also in multivariate survival analysis, but did not reflect TP53 mutational status. High human epidermal growth factor receptor 2 protein levels were identified in 21% of all tumors. ERBB2 amplification was associated with poor outcome (P=.003); human epidermal growth factor receptor 2 protein level was not. CONCLUSIONS: Our findings support that the Féderation Internationale de Gynécologie et d'Obstétrique s guidelines should include vascular space invasion and tumor size 2-4 cm and that careful selection of histologic type is essential for stratification of patient risk groups. High p53 levels independently predict poor survival yet do not reflect mutational status in cervical cancer. Amplified ERBB2 significantly links to poor survival, while HercepTest does not. With optimal stratification, human epidermal growth factor receptor 2-based therapy may improve cervical cancer treatment.

A Selective Biomarker Panel Increases the Reproducibility and the Accuracy in Endometrial Biopsy Diagnosis.

Grading and histologic typing of endometrial cancer in biopsy material has a direct impact on the decision to perform lymphadenectomy and/or omentectomy in many cancer centers. Endometrial biopsies are among the most common general surgical pathology specimens. Multiple studies have shown that biopsy diagnosis suffers from a lack of reproducibility. Although many biomarkers have been proposed, none have been demonstrated to improve the diagnosis in the biopsy setting. In this study, 70 biopsies with endometrial carcinoma were supplemented with a biomarker panel consisting of ER, PR, P53, and DNA ploidy. A representative H&E slide was scanned digitally and made available to 12 gynecologic pathologists in 4 Nordic countries: Finland, Denmark, Sweden, and Norway. Reviewers diagnosed the cases both before and after being provided with the biomarker results. The interobserver percent agreement and Cohen κ improved from 75.8% (κ=0.52, moderate) to 84% (κ=0.68, substantial) with inclusion of the biomarker panel. Agreement with the subsequent hysterectomy diagnosis also improved from 83.6% (κ=0.67) to 88.7% (κ=0.77). There was no statistical improvement between a reflex (84% agreement) and a reflective testing algorithm (82.9% agreement), suggesting that the selective use of biomarkers is appropriate. Difficult cases were almost exclusively high-grade tumors. Finally, a statistical model indicated that only P53 and DNA ploidy, in conjunction with an H&E review, had an impact on the decision to upgrade or downgrade cases.

Ovarian carcinoma histotype determination is highly reproducible, and is improved through the use of immunohistochemistry.

AIMS: To assess the variation in ovarian carcinoma type diagnosis among gynaecological pathologists from Nordic countries, and whether a rationally designed panel of immunohistochemical markers could improve diagnostic reproducibility. METHODS AND RESULTS: Eight pathologists from four countries (Sweden, Denmark, Norway, and Finland) received an educational lecture on the diagnosis of ovarian carcinoma type. All tumour-containing slides from 54 ovarian carcinoma cases were independently reviewed by the participants, who: (i) determined type purely on the basis of histology; (ii) indicated whether they would apply immunohistochemistry in their routine practice; and (iii) determined type after reviewing the staining results. The results for six markers (WT1, p53, p16, HNF-1ß, ARID1A, and progesterone receptor) were determined for all 54 cases, by staining of a tissue microarray. The median concordance with central review diagnosis was 86%, and significantly improved to 90% with the incorporation of immunostaining results (P = 0.0002). The median interobserver agreement was 78%, and significantly improved to 85% with the incorporation of immunostaining results (P = 0.0002). CONCLUSIONS: Use of the immunostaining results significantly improved both diagnostic accuracy and interobserver agreement. These results indicate that ovarian carcinoma type can be reliably diagnosed by pathologists from different countries, and also demonstrate that immunohistochemistry has an important role in improving diagnostic accuracy and agreement between pathologists.

Mercury in human brain, blood, muscle and toenails in relation to exposure: an autopsy study.

BACKGROUND: The main forms of mercury (Hg) exposure in the general population are methylmercury (MeHg) from seafood, inorganic mercury (I-Hg) from food, and mercury vapor (Hg0) from dental amalgam restorations. While the distribution of MeHg in the body is described by a one compartment model, the distribution of I-Hg after exposure to elemental mercury is more complex, and there is no biomarker for I-Hg in the brain. The aim of this study was to elucidate the relationships between on the one hand MeHg and I-Hg in human brain and other tissues, including blood, and on the other Hg exposure via dental amalgam in a fish-eating population. In addition, the use of blood and toenails as biological indicator media for inorganic and organic mercury (MeHg) in the tissues was evaluated. METHODS: Samples of blood, brain (occipital lobe cortex), pituitary, thyroid, abdominal muscle and toenails were collected at autopsy of 30 deceased individuals, age from 47 to 91 years of age. Concentrations of total-Hg and I-Hg in blood and brain cortex were determined by cold vapor atomic fluorescence spectrometry and total-Hg in other tissues by sector field inductively coupled plasma-mass spectrometry (ICP-SFMS). RESULTS: The median concentrations of MeHg (total-Hg minus I-Hg) and I-Hg in blood were 2.2 and 1.0 microg/L, and in occipital lobe cortex 4 and 5 microg/kg, respectively. There was a significant correlation between MeHg in blood and occipital cortex. Also, total-Hg in toenails correlated with MeHg in both blood and occipital lobe. I-Hg in both blood and occipital cortex, as well as total-Hg in pituitary and thyroid were strongly associated with the number of dental amalgam surfaces at the time of death. CONCLUSION: In a fish-eating population, intake of MeHg via the diet has a marked impact on the MeHg concentration in the brain, while exposure to dental amalgam restorations increases the I-Hg concentrations in the brain. Discrimination between mercury species is necessary to evaluate the impact on Hg in the brain of various sources of exposure, in particular, dental amalgam exposure.

Molecular analysis of the PI3K-AKT pathway in uterine cervical neoplasia: frequent PIK3CA amplification and AKT phosphorylation.

Uterine cervical carcinogenesis is probably dependent on cellular genetic damage in addition to the integration of high-risk HPV DNA in the epithelial cell genome. Gain of chromosome 3q24-29 is commonly observed in cervical neoplasia. The putative oncogene PIK3CA located in this region encodes a phosphatidylinositol 3-kinase (PI3K). In a process reversed by PTEN, PI3K generates inositol phospholipids that trigger AKT phosphorylation, which in turn effects tumor driving signals. We studied 46 specimens of formalin-fixed, paraffin-embedded cervical neoplastic tissue. The activation state of the PI3K-AKT pathway was assessed immunohistochemically using an antibody with specificity towards serine 473-phosphorylated AKT. AKT phosphorylation was found in 39 out of 46 examined specimens. To examine the possible molecular basis for this activation, we searched for PIK3CA amplification using quantitative real-time polymerase chain reaction. PIK3CA gene copy number was estimated to be 3 or more in 28 out of 40 successfully examined cases. Further, a PTEN mutation analysis of all 9 PTEN exons was carried out, but except for 1 metastasis with an exon 9 V369I heterozygosity, all cases showed normal PTEN sequence. Immunohistochemical staining for PTEN was strong in all lesions. In conclusion, an increased activation state of AKT kinase appears to be present in cervical carcinogenesis, and may be accounted for by PIK3CA amplification, whereas PTEN mutation seems to be of little importance.