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.publishedVersio

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

Genomic characterization and therapeutic targeting of HPV undetected cervical carcinomas

Cervical cancer tumors with undetectable HPV (HP

Single-cell profiling of low-stage endometrial cancers identifies low epithelial vimentin expression as a marker of recurrent diseaseResearch in context

Summary: Background: Identification of aggressive low-stage endometrial cancers is challenging. So far, studies have failed to pinpoint robust features or biomarkers associated with risk of recurrence for these patients. Methods: Imaging mass cytometry was used to examine single-cell expression of 23 proteins in 36 primary FIGO IB endometrial cancers, of which 17 recurred. Single-cell information was extracted for each tumor and unsupervised clustering was used to identify cellular phenotypes. Distinct phenotypes and cellular neighborhoods were compared in relation to recurrence. Cellular differences were validated in a separate gene expression dataset and the TCGA EC dataset. Vimentin protein expression was evaluated by IHC in pre-operative samples from 518 patients to validate its robustness as a prognostic marker. Findings: The abundance of epithelial, immune or stromal cell types did not associate with recurrence. Clustering of patients based on tumor single cell marker expression revealed distinct patient clusters associated with outcome. A cell population neighboring CD8+ T cells, defined by vimentin, ER, and PR expressing epithelial cells, was more prevalent in non-recurrent tumors. Importantly, lower epithelial vimentin expression and lower gene expression of VIM associated with worse recurrence-free survival. Loss and low expression of vimentin was validated by IHC as a robust marker for recurrence in FIGO I stage disease and predicted poor prognosis also when including all patients and in endometrioid patients only. Interpretation: This study reveals distinct characteristics in low-stage tumors and points to vimentin as a clinically relevant marker that may aid in identifying a here to unidentified subgroup of high-risk patients. Funding: A full list of funding that contributed to this study can be found in the Acknowledgements section

The prognostic value of preoperative FDG-PET/CT metabolic parameters in cervical cancer patients

Abstract Background To explore quantitative metabolic and microstructural primary tumour parameters at pretreatment FDG-PET/CT and diffusion-weighted-magnetic resonance imaging (DW-MRI) in relation to clinical FIGO stage and outcome in uterine cervical cancer patients. Methods Fifty three patients with histopathologically verified cervical carcinoma with clinical FIGO stage IB1-IVA were subjected to FDG-PET/CT and subgroup also DW-MRI (n = 30) prior to treatment. Measurements from the FDG-PET/CT comprised lesion maximum-standardised uptake value (SUVmax), total lesion glycolysis (TLG) and metabolic tumour volume (MTV). In MR images longest-tumour-diameter (MRI-LD), tumour volume (MRI-TV) and mean tumour apparent-diffusion-coefficient (ADCmean) value were measured. FDG-PET/CT parameters were explored in relation to clinical prognostic factors at diagnosis and progression/recurrence free survival, and compared with the MRI parameters. Results The metabolic tumour parameters TLG and MTV were highly positively correlated to MRI-LD and MRI-TV (rs = 072–0.82; p < 0.001 for all), whereas tumour SUVmax was only moderately correlated to MRI-LD (rs = 0.29; p ≤ 0.04) and MRI-TV (rs = 0.36; p ≤ 0.01). High tumour TLG, MTV, MRI-LD and MRI-TV predicted advanced FIGO stage, whereas high tumour SUVmax did not. No significant correlations were observed between tumour ADCmean and the other imaging parameters or FIGO stage. High primary tumour MTV (≥56.7 mL), high TLG (≥412 g) and large MRI-TV (≥36 mL) predicted reduced progression/recurrence free survival yielding corresponding hazard ratios [HR] of 7.8 (P  =  0.002), 6.9 (P  =  0.004) and 4.6 (P  =  0.022), respectively. Also advanced FIGO stage (≥IIIA) was associated with reduced progression/recurrence free survival with HR of 6.9 (P  =  0.004). In multivariable analysis, advanced FIGO stage (≥IIIA) and high MTV (≥56.7 mL) were independent prognostic factors with adjusted HRs of 5.5 (P  =  0.020) and 7.8 (P  =  0.025), respectively. Conclusion High MTV at pre-treatment FDG-PET/CT and high clinical FIGO stage independently predict reduced progression/recurrence free survival in cervical cancer patients

Impact of MRI radiomic feature normalization for prognostic modelling in uterine endometrial and cervical cancers

Abstract Widespread clinical use of MRI radiomic tumor profiling for prognostication and treatment planning in cancers faces major obstacles due to limitations in standardization of radiomic features. The purpose of the current work was to assess the impact of different MRI scanning- and normalization protocols for the statistical analyses of tumor radiomic data in two patient cohorts with uterine endometrial-(EC) (n = 136) and cervical (CC) (n = 132) cancer. 1.5 T and 3 T, T1-weighted MRI 2 min post-contrast injection, T2-weighted turbo spin echo imaging, and diffusion-weighted imaging were acquired. Radiomic features were extracted from within manually segmented tumors in 3D and normalized either using z-score normalization or a linear regression model (LRM) accounting for linear dependencies with MRI acquisition parameters. Patients were clustered into two groups based on radiomic profile. Impact of MRI scanning parameters on cluster composition and prognostication were analyzed using Kruskal–Wallis tests, Kaplan–Meier plots, log-rank test, random survival forests and LASSO Cox regression with time-dependent area under curve (tdAUC) (α = 0.05). A large proportion of the radiomic features was statistically associated with MRI scanning protocol in both cohorts (EC: 162/385 [42%]; CC: 180/292 [62%]). A substantial number of EC (49/136 [36%]) and CC (50/132 [38%]) patients changed cluster when clustering was performed after z-score-versus LRM normalization. Prognostic modeling based on cluster groups yielded similar outputs for the two normalization methods in the EC/CC cohorts (log-rank test; z-score: p = 0.02/0.33; LRM: p = 0.01/0.45). Mean tdAUC for prognostic modeling of disease-specific survival (DSS) by the radiomic features in EC/CC was similar for the two normalization methods (random survival forests; z-score: mean tdAUC = 0.77/0.78; LRM: mean tdAUC = 0.80/0.75; LASSO Cox; z-score: mean tdAUC = 0.64/0.76; LRM: mean tdAUC = 0.76/0.75). Severe biases in tumor radiomics data due to MRI scanning parameters exist. Z-score normalization does not eliminate these biases, whereas LRM normalization effectively does. Still, radiomic cluster groups after z-score- and LRM normalization were similarly associated with DSS in EC and CC patients

Blood Metabolites Associate with Prognosis in Endometrial Cancer

Endometrial cancer has a high prevalence among post-menopausal women in developed countries. We aimed to explore whether certain metabolic patterns could be related to the characteristics of aggressive disease and poorer survival among endometrial cancer patients in Western Norway. Patients with endometrial cancer with short survival (n = 20) were matched according to FIGO (International Federation of Gynecology and Obstetrics, 2009 criteria) stage, histology, and grade, with patients with long survival (n = 20). Plasma metabolites were measured on a multiplex system including 183 metabolites, which were subsequently determined using liquid chromatography-mass spectrometry. Partial least square discriminant analysis, together with hierarchical clustering, was used to identify patterns which distinguished short from long survival. A proposed signature of metabolites related to survival was suggested, and a multivariate receiver operating characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.820–0.965 (p ≤ 0.001). Methionine sulfoxide seems to be particularly strongly associated with poor survival rates in these patients. In a subgroup with preoperative contrast-enhanced computed tomography data, selected metabolites correlated with the estimated abdominal fat distribution parameters. Metabolic signatures may predict prognosis and be promising supplements when evaluating phenotypes and exploring metabolic pathways related to the progression of endometrial cancer. In the future, this may serve as a useful tool in cancer management.publishedVersio

MRI‐based radiomic signatures for pretreatment prognostication in cervical cancer

Abstract 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

Genomic characterization and therapeutic targeting of HPV undetected cervical carcinomas

Cervical cancer tumors with undetectable HPV (HPVU) have been underappreciated in clinical decision making. In this study, two independent CC datasets were used to characterize the largest cohort of HPVU tumors to date (HPVU = 35, HPV+ = 430). Genomic and transcriptome tumor profiles and patient survival outcomes were compared between HPV+ and HPVU tumors. In vitro analyses were done to determine efficacy of the selective CDK4/6 inhibitor palbociclib on HPVU cancer cell lines. Patients with HPVU CC tumors had worse progression-free and overall survival outcomes compared to HPV+ patients. TP53, ARID1A, PTEN, ARID5B, CTNNB1, CTCF, and CCND1 were identified as significantly mutated genes (SMGs) enriched in HPVU tumors, with converging functional roles in cell cycle progression. In vitro HPVU, but not HPV+, cancer cell lines with wild type RB1 were sensitive to palbociclib monotherapy. These results indicate that HPVU status can be translated into the clinic as a predictive biomarker of poor patient response to standard of care treatments. We suggest primary cervix tumors be routinely tested for HPV prior to treatment to identify patients who will benefit from more aggressive precision-driven therapy. Our results identify palbociclib as a lead candidate as an alternative treatment strategy for HPVU CC patients

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