Intratumoral metabolic heterogeneity of cervical cancer

When to Consider Invasive Lymph Node Staging in Non-Small-Cell Lung Cancer? A Novel Scoring System Utilising Metabolic Parameters in 18F-FDG PET/CT

OBJECTIVE

The maximum standardised uptake value (SUVmax) is a widely utilised metric in positron emission tomography/computed tomography for clinically staging non-small-cell lung cancer (NSCLC), yet the reliability of SUVmax remains controversial. We herein aimed to assess the effectiveness of semi-quantitative parameters, encompassing size, SUVmax, metabolic tumour volume (MTV), total lesion glycolysis (TLG) and heterogeneity factor (HF), in evaluating both primary tumours and lymph nodes (LNs) on positron emission tomography/computed tomography. A novel scoring system was devised to appraise the role of semi-quantitative parameters and visually evaluate LNs for nodal staging.

MATERIALS AND METHODS

Patients with pathological NSCLC, diagnosed between 2014 and 2019 and clinically staged I-III, were enrolled in the study. Patient demographics, including age, sex, tumour location, diameter, tumour-node-metastasis stage, as well as SUVmax, MTV, TLG and HF parameters of primary tumours and LNs, were documented.

RESULTS

The analysis comprised 319 patients and 963 LNs. Patients had a mean age of 61.62 years, with 91.5% being male. Adenocarcinoma exhibited a histological association with LN metastasis (P=0.043). The study findings revealed that tumour size, SUVmax, MTV, TLG and HF did not significantly affect the detection of LN metastasis. Conversely, non-squamous cell carcinoma, LNs exhibiting higher FDG levels than the liver, LN size, SUVmax, MTV and TLG were identified as risk factors (P<0.0001). The identified cut-off values were 1.05cm for LN size, 4.055 for SUVmax, 1.805cm3 for MTV and 5.485 for TLG. The scoring system incorporated these parameters, and visual assessment indicated that a score of ≥3 increased the risk of metastasis by 14.33 times.

CONCLUSION

We devised a novel scoring system and demonstrated that LNs with a score of ≥3 in patients with NSCLC have a high likelihood of metastasis. This innovative scoring system can serve as a valuable tool to mitigate excessive and extreme measures in the assessment of invasive pathological staging.

Utility of pre-treatment 18 F-fluorodeoxyglucose PET radiomic analysis in assessing nodal involvement in cervical cancer

OBJECTIVE

Intratumor heterogeneity has prognostic value in cervical cancer, which can be depicted on 18 F-fluorodeoxyglucose ( 18 F-FDG) PET/computed tomography (PET/CT) and then quantitatively characterized by texture features. This study aimed to evaluate the discriminative performance and predictive ability of the texture features in determining lymph node involvement in cervical cancer.

METHODS

A total of 101 patients with newly diagnosed cervical cancer, who underwent pre-treatment whole-body 18 F-FDG PET/CT imaging were retrospectively recruited. Patients were categorized based on their nodal status. Thirty-five radiomic features together with the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary cervical tumors were extracted. Conventional indices were used to build logistic regression model and texture features were used to build random forest model. The performances for differentiating nodal status were assessed by receiver operating characteristic analysis.

RESULTS

Conventional PET indices were significantly higher in patients with nodal involvement compared to those without: SUVmax = 14.22 vs. 10.05; MTV = 57.02 vs. 28.73; TLG = 492.8 vs. 188.8 ( P  < 0.05). Nineteen radiomic features describing regional heterogeneity were significantly different between nodal involvements. Area under the curves of the models with conventional indices and PET texture features for discriminating nodal status were 0.72 and 0.76, respectively.

CONCLUSION

PET-derived radiomic features had moderate performance in discriminating nodal involvement in cervical cancer; and they did not outperform model based on conventional indices.

Current Update on PET/MRI in Gynecological Malignancies-A Review of the Literature

Early detection of gynecological malignancies is vital for patient management and prolonging the patient's survival. Molecular imaging, such as positron emission tomography (PET)/computed tomography, has been increasingly utilized in gynecological malignancies. PET/magnetic resonance imaging (MRI) enables the assessment of gynecological malignancies by combining the metabolic information of PET with the anatomical and functional information from MRI. This article will review the updated applications of PET/MRI in gynecological malignancies.

Temporal Heterogeneity of HER2 Expression and Spatial Heterogeneity of 18F-FDG Uptake Predicts Treatment Outcome of Pyrotinib in Patients with HER2-Positive Metastatic Breast Cancer

Background: This study aimed to evaluate tumor heterogeneity of metastatic breast cancer (MBC) and investigate its impact on the efficacy of pyrotinib in patients with HER2-positive MBC. Methods: MBC patients who underwent 18F-FDG PET/CT before pyrotinib treatment were included. Temporal and spatial tumor heterogeneity was evaluated by the discordance between primary and metastatic immunohistochemistry (IHC) results and baseline 18F-FDG uptake heterogeneity (intertumoral and intratumoral heterogeneity indexes: HI-inter and HI-intra), respectively. Progression-free survival (PFS) was estimated by the Kaplan−Meier method and compared by a log-rank test. Results: A total of 572 patients were screened and 51 patients were included. In 36 patients with matched IHC results, 25% of them had HER2 status conversion. Patients with homogenous HER2 positivity had the longest PFS, followed by patients with gained HER2 positivity, while patients with HER2 negative conversion could not benefit from pyrotinib (16.8 vs. 13.7 vs. 3.6 months, p < 0.0001). In terms of spatial heterogeneity, patients with high HI-intra and HI-inter had significantly worse PFS compared to those with low heterogeneity (10.6 vs. 25.3 months, p = 0.023; 11.2 vs. 25.3 months, p = 0.040). Conclusions: Temporal heterogeneity of HER2 status and spatial heterogeneity of 18F-FDG uptake could predict the treatment outcome of pyrotinib in patients with HER2-positive MBC, which provide practically applicable methods to assess tumor heterogeneity and guidance for treatment decisions.

Imaging to optimize gynecological radiation oncology

Gynecological cancers have particularly benefited from the increasing use of imaging to guide radiation treatment planning for both external beam radiation and brachytherapy. While the different gynecological cancers have varying use of imaging, certain trends predominate. CT represents an economical choice for evaluating initial disease extent or potential metastasis at follow-up, particularly for endometrial and ovarian cancers. F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT is particularly useful for assessing the initial disease extent and longer term treatment response of squamous predominant cancers, including cervical, vaginal, and vulvar cancers. With its excellent pelvic soft tissue discrimination, MRI provides the greatest assistance in evaluating the local extent of gynecological tumors, including initial evaluation for non-operative endometrial and vulvar cancer, and assessment before, after and during brachytherapy for cervix, locally recurrent endometrial, and primary vaginal cancers. With more limited availability of MRI, ultrasound can also help guide brachytherapy, particularly during procedures. The benefits of using imaging to better spare bone marrow or earlier assessment of treatment response are topics still being explored, in particular for cervical cancer. As imaging along with radiation oncology technologies continue to evolve and develop, such as with MRI-linacs and ultra high dose rate (FLASH) radiation, we may continue to see increasing use of imaging for advancing gynecological radiation oncology.

BAIRDA: a novel in vitro setup to quantify radiobiological parameters for cervical cancer brachytherapy dose estimations

Objective. Brachytherapy (BT) dose prescriptions for locally advanced cervical cancer are made with account for the radiobiological parameters, α/β ratio and halftime of repair (T 1/2 ). However, a wide range of parameter values has been reported which can challenge commonly held equivalencies between dose prescriptions. This is the first reported study that aims to develop an in vitro experimental technique using clinical high-dose-rate (HDR) and pulsed-dose-rate (PDR) Ir-192 brachytherapy afterloaders to quantify these parameters in vitro and to contextualize findings within contemporary practice. Approach. To efficiently quantify α/β and T 1/2 , in vitro experiments more reflective of clinical BT practice than traditional clonogenic survival assays were developed and applied to four squamous cell carcinoma cell lines (CaSki, C-33A, SiHa, and SW756). Radiation was delivered using single acute and fractionated dose treatments with a conventional irradiator and clinical HDR and PDR BT afterloaders. For the latter, a novel brachytherapy afterloader in vitro radiation delivery apparatus (BAIRDA) was developed. Main Results. The α/β and T 1/2 values determined using BAIRDA and the conventional irradiator showed close agreement, validating the novel apparatus and technique. For CaSki, C-33A, SiHa, and SW756, the BAIRDA-measured α/β ratios (5.2 [4.6–5.8], 5.6 [4.5–6.6], 6.3 [4.9–7.7], and 5.3 [4.7–6.0] Gy, respectively) were consistently smaller, while the T 1/2 (3.3 [2.7–3.9], 2.7 [2.0–3.3], 2.8 (2.4–3.1], and 4.8 [4.1–5.4] hours) larger, than the widely accepted values in clinical practice (α/β = 10 Gy; T 1/2  = 1.5 h). Significance. In vitro experiments using BAIRDA provided evidence for differences between the conventionally selected and experimentally determined α/β ratio and T 1/2 . Treatment regimens using HDR-BT and PDR-BT, designed to deliver equivalent radiobiological doses based on conventional values, were shown to differ by up to 27 Gy EQD2 – an effect that could impact treatment outcomes in cervical cancer. Furthermore, with BAIRDA, we have developed a novel method for radiobiological research in BT.

Gynecologic Cancer, Cancer Stem Cells, and Possible Targeted Therapies

Gynecologic cancer is one of the main causes of death in women. In this type of cancer, several molecules (oncogenes or tumor suppressor genes) contribute to the tumorigenic process, invasion, metastasis, and resistance to treatment. Based on recent evidence, the detection of molecular changes in these genes could have clinical importance for the early detection and evaluation of tumor grade, as well as the selection of targeted treatment. Researchers have recently focused on cancer stem cells (CSCs) in the treatment of gynecologic cancer because of their ability to induce progression and recurrence of malignancy. This has highlighted the importance of a better understanding of the molecular basis of CSCs. The purpose of this review is to focus on the molecular mechanism of gynecologic cancer and the role of CSCs to discover more specific therapeutic approaches to gynecologic cancer treatment.

The value of metabolic parameters and textural analysis in predicting prognosis in locally advanced cervical cancer treated with chemoradiotherapy

Objective

The aim of the study was to assess the impact of clinical and metabolic parameters derived from ¹⁸F-FDG PET/CT (positron emission tomography–computed tomography) in patients with locally advanced cervical cancer (LACC) on prognosis.

Methods

Patients with LACC of stage IB2-IVA treated by primary radiochemotherapy followed by brachytherapy were enrolled in this retrospective study. Indexes derived from standardized uptake value (SUV), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and textural features of the primary tumor were measured for each patient. Overall survival (OS) and recurrence-free survival (RFS) rates were calculated according to Kaplan–Meier and survival curves were compared using the log-rank test. Uni- and multivariate analyses were performed using the Cox regression model.

Results

A total of 116 patients were included. Median follow-up was 58 months (range: 1–129). A total of 36 (31%) patients died. Five-year OS and RFS rates were 69 and 60%, respectively. Univariate analyses indicated that FIGO stage, the presence of hydronephrosis, high CYFRA 21.1 levels, and textural features had a significant impact on OS and RFS. MTV as well as SCC-Ag concentration were also significantly associated with OS. On multivariate analysis, the presence of hydronephrosis, CYFRA 21.1, and sphericity were independent prognostics factors for OS and RFS. Also, SCC-Ag level, MTV, and GLZLM (gray-level zone length matrix) ZLNU (zone length non-uniformity) were significantly associated with OS.

Conclusion

Classical prognostic factors and tumor heterogeneity on pretreatment PET/CT were significantly associated with prognosis in patients with LACC.

MRI-based peritumoral radiomics analysis for preoperative prediction of lymph node metastasis in early-stage cervical cancer: A multi-center study

PURPOSE

To evaluate intra- and preitumoral radiomics on the contrast-enhanced T1-weighted (CE-T1) and T2-weighted (T2W) MRI for predicting the LNM, and develop a nomogram for potential clinical uses.

METHODS

We enrolled 169 cervical cancer cases who underwent CE-T1 and T2W MR scans from two hospitals between Dec. 2015 and Sep. 2021. Intra- and peritumoral features were extracted separately and selected by the least absolute shrinkage and selection operator (LASSO) regression. Radiomics signatures were built using the selected features from different regions. Clinical parameters were evaluated by statistical analysis. The nomogram was developed combining the multi-regional radiomics signature and the most predictive clinical parameters.

RESULTS

Five radiomics features were finally selected from the peritumoral regions with 1 and 3 mm distances in the CE-T1 and T2W MRI, respectively. The nomogram incorporating multi-regional combined radiomics signature, MR-reported LN status and tumor diameter achieved the highest AUCs in the training (nomogram vs. combined radiomics signature vs. clinical model, 0.891 vs. 0.830 vs. 0.812), internal validation (nomogram vs. combined radiomics signature vs. clinical model, 0.863 vs. 0.853 vs. 0.816) and external validation (nomogram vs. combined radiomics signature vs. clinical model, 0.804 vs. 0.701 vs. 0.787) cohort. DCA suggested good clinical usefulness of our developed models.

CONCLUSION

The current work suggested clinical potential for intra- and peritumoral radiomics with multi-modal MRI for preoperative predicting LNM.

Cell line-directed breast cancer research based on glucose metabolism status

Metabolic reprogramming is a potential hallmark of tumor cells to support continuous proliferation. Metabolic heterogeneity in breast cancer patients has been highlighted as the driving cause of tumor progression and resistance to anticancer drugs. Studying and identifying distinct metabolic alterations in breast cancer subtypes could offer new perspectives for faster diagnosis and treatment. Given cancer cell dependency on glycolysis, the primary energy source, this enzymatic pathway will play a critical role in targeting therapies. Knowledge about the specific metabolic dependencies of tumors for growth and proliferation can be promising for novel targeted and cell-based therapies. Here, the metabolic status with emphasis on glycolysis of breast cancer cell lines according to their classification was reviewed.

The impact of HPV infection on human glycogen and lipid metabolism - a review

Reinterpretation of the Wartburg effect leads to understanding aerobic glycolysis as a process that provides considerable amount of molecular precursors for the production of lipids, nucleotides and amino acids that are necessary for continuous growth and rapid proliferation characteristic for cancer cells. Human papilloma virus (HPV) is a number one cause of cervical carcinoma with 99% of the cervical cancer patients being HPV positive. This tight link between HPV and cancer raises the question if and how HPV impact cells to reprogram their metabolism? Focusing on early phase proteins E1, E2, E5, E6 and E7 we demonstrate that HPV activates plethora of metabolic pathways and directly influences enzymes of the glycolysis pathway to promote the Warburg effect by increasing glucose uptake, activating glycolysis and pentose phosphate pathway, increasing the level of lactate dehydrogenase A synthesis and inhibiting β-oxidation. Our considerations lead to conclusion that HPV is substantially involved in metabolic cell reprogramming toward neoplastic phenotype and its metabolic activity is the fundamental reason of its oncogenicity.

Metabolism-Relevant Molecular Classification Identifies Tumor Immune Microenvironment Characterization and Immunotherapeutic Effect in Cervical Cancer

Cervical cancer (CESC) is a gynecologic malignant tumor associated with high incidence and mortality rates because of its distinctive management complexity. Herein, we characterized the molecular features of CESC based on the metabolic gene expression profile by establishing a novel classification system and a scoring system termed as METAscore. Integrative analysis was performed on human CESC samples from TCGA dataset. Unsupervised clustering of RNA sequencing data on 2,752 formerly described metabolic genes identified three METAclusters. These METAclusters for overall survival time, immune characteristics, metabolic features, transcriptome features, and immunotherapeutic effectiveness existed distinct differences. Then we analyzed 207 DEGs among the three METAclusters and as well identified three geneclusters. Correspondingly, these three geneclusters also differently expressed among the aforementioned features, supporting the reliability of the metabolism-relevant molecular classification. Finally METAscore was constructed which emerged as an independent prognostic biomarker, related to CESC transcriptome features, metabolic features, immune characteristics, and linked to the sensitivity of immunotherapy for individual patient. These findings depicted a new classification and a scoring system in CESC based on the metabolic pattern, thereby furthering the understanding of CESC genetic signatures and aiding in the prediction of the effectiveness to anticancer immunotherapies.

Metabolic Classification and Intervention Opportunities for Tumor Energy Dysfunction

A comprehensive view of cell metabolism provides a new vision of cancer, conceptualized as tissue with cellular-altered metabolism and energetic dysfunction, which can shed light on pathophysiological mechanisms. Cancer is now considered a heterogeneous ecosystem, formed by tumor cells and the microenvironment, which is molecularly, phenotypically, and metabolically reprogrammable. A wealth of evidence confirms metabolic reprogramming activity as the minimum common denominator of cancer, grouping together a wide variety of aberrations that can affect any of the different metabolic pathways involved in cell physiology. This forms the basis for a new proposed classification of cancer according to the altered metabolic pathway(s) and degree of energy dysfunction. Enhanced understanding of the metabolic reprogramming pathways of fatty acids, amino acids, carbohydrates, hypoxia, and acidosis can bring about new therapeutic intervention possibilities from a metabolic perspective of cancer.

LRP1B mutation is associated with tumor HPV status and promotes poor disease outcomes with a higher mutation count in HPV-related cervical carcinoma and head & neck squamous cell carcinoma

Human papillomavirus (HPV) infection and gene mutations were reputed as key factors in cervical carcinoma (CC) and head and neck squamous cell carcinoma (HNSCC). However, the associations of HPV status and gene mutations remain to be determined. This study aims to identify molecular patterns of LRP1B mutation and HPV status via rewiring tumor samples of HNSCC (n=1478) and CC (n=178) from the TCGA dataset. Here, we found that LRP1B mutation was associated with HPV status in CC (P=0.040) and HNSCC (P=0.044), especially in HPV 16 integrated CC (P=0.036). Cancer survival analysis demonstrated that samples with LRP1B mutation showed poor disease outcomes in CC (P=0.013) and HNSCC (P=0.0124). In addition, the expression status of LPR1B was more favorable for prediction than TP53 or RB1 in CC and HNSCC. Mutation clustering analysis showed that samples with LRP1B mutation showed higher mutation count in CC (P=1.76e-67) and HNSCC (P<10e-10). Further analysis identified 289 co-occurrence genes in these two cancer types, which were enriched in PI3K signaling, cell division process, and chromosome segregation process, et al. The 289-co-occurrence gene signature identified a cluster of patients with a higher portion of copy number variation (CNV) lost in the genome, different tumor HPV status (P<10e-10), higher mutation count (P<10e-10), higher fraction genome altered value (P=2.078e-4), higher aneuploidy score (P=3.362e-4), and earlier started the smoking year (P=2.572e-4), which were associated with shorter overall survival (P=0.0103) in CC and HNSCC samples. Overall, LRP1B mutation was associated with tumor HPV status and was an unfavorable prognostic biomarker for CC and HNSCC.

EANM/SNMMI practice guideline for [18F]FDG PET/CT external beam radiotherapy treatment planning in uterine cervical cancer v1.0

PURPOSE

The aim of this EANM / SNMMI Practice Guideline with ESTRO endorsement is to provide general information and specific considerations about [18F]FDG PET/CT in advanced uterine cervical cancer for external beam radiotherapy planning with emphasis on staging and target definition, mostly in FIGO stages IB3-IVA and IVB, treated with curative intention.

METHODS

Guidelines from related fields, relevant literature and leading experts have been consulted during the development of this guideline. As this field is rapidly evolving, this guideline cannot be seen as definitive, nor is it a summary of all existing protocols. Local variations should be taken into consideration when applying this guideline.

CONCLUSION

The background, common clinical indications, qualifications and responsibilities of personnel, procedure / specifications of the examination, documentation / reporting and equipment specifications, quality control and radiation safety in imaging is discussed with an emphasis on the multidisciplinary approach.

miR-326 inhibits the cell proliferation and cancer stem cell-like property of cervical cancer in vitro and oncogenesis in vivo via targeting TCF4

Background

Cervical cancer ranks as one of the most prevalent female malignancies globally, and its treatment with new targets has been the focus of current research. The present study set out to investigate the function of microRNA-326 (miR-326) in vitro and in vivo and to verify the direct targeting of transcription factor 4 (TCF4) by miR-326.

Methods

The detection of messenger RNA (mRNA) expressing miR-326 and TCF4 in cervical cancer cell lines and tumor samples was conducted using quantitative real-time polymerase chain (qRT-PCR). A dual-luciferase reporter assay was carried out to detect the target relationship of miR-326 with TCF4. A Cell Counting Kit-8 (CCK-8) assay was employed to detect the effect of miR-326 on CasKi cell viability. Flow cytometry and western blotting were employed to examine the effects of miR-326 on cancer stem cell (CSC)-like property. Tumor weight was measured in orthotopic xenograft mouse models. Immunohistochemistry was employed to analyze the protein expression levels of Ki-67, proliferating cell nuclear antigen (PCNA), CD44, and SRY-box 4 (SOX4).

Result

Downregulation of the mRNA expression levels of miR-326 was observed in cervical cancer cell lines and tumor tissue, while the levels of TCF4 were upregulated. The dual-luciferase reporter assay revealed binding of miR-326 to the three prime untranslated region (3'-UTR) of TCF4. In vitro assays demonstrated that miR-326 inhibited CasKi cell proliferation through regulating TCF4. miR-326 also suppressed the CSC-like property of CasKi cells by targeting TCF4. Furthermore, the protein expression levels of cyclin D1, β-catenin, and c-Myc were decreased when miR-326 was added to TCF4-transfected cells. In vivo assays demonstrated that miR-326 inhibited tumor weight, growth, and the protein expression levels of Ki-67, PCNA, CD44, SOX4, and β-catenin.

Conclusions

miR-326 acted in a tumor-suppressive manner through its regulation of TCF4, and has potential as a biomarker or therapeutic target for cervical cancer.

The Intratumoral Heterogeneity of Cancer Metabolism

Cancer is one of the deadliest diseases in the world, causing over half a million deaths a year in the USA alone. Despite recent advances made in the field of cancer biology and the therapies that have been developed [1, 2], it is clear that more advances are necessary for us to classify cancer as curable. The logical question that arises is simple: Why, despite all the technologies and medical innovations of our time, has a complete cure eluded us? This chapter sheds light on one of cancer's most impactful attributes: its heterogeneity and, more specifically, the intratumoral heterogeneity of cancer metabolism. Simply put, what makes cancer one of the deadliest diseases is its ability to change and adapt. Cancer cells' rapid evolution, coupled with their irrepressible ability to divide, gives most of them the advantage over our immune systems. In this chapter, we delve into the complexities of this adaptability and the vital role that metabolism plays in the rise and progression of this heterogeneity.

Mining of prognosis-related genes in cervical squamous cell carcinoma immune microenvironment

Purpose

The aim of this study was to explore the effective immune scoring method and mine the novel and potential immune microenvironment-related diagnostic and prognostic markers for cervical squamous cell carcinoma (CSSC).

Materials and Methods

The Cancer Genome Atlas (TCGA) data was downloaded and multiple data analysis approaches were initially used to search for the immune-related scoring system on the basis of Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) algorithm. Afterwards, the representative genes in the gene modules correlated with immune-related scores based on ESTIMATE algorithm were further screened using Weighted Gene Co-expression Network Analysis (WGCNA) and network topology analysis. Gene functions were mined through enrichment analysis, followed by exploration of the correlation between these genes and immune checkpoint genes. Finally, survival analysis was applied to search for genes with significant association with overall survival and external database was employed for further validation.

Results

The immune-related scores based on ESTIMATE algorithm was closely associated with other categories of scores, the HPV infection status, prognosis and the mutation levels of multiple CSCC-related genes (HLA and TP53). Eighteen new representative immune microenvironment-related genes were finally screened closely associated with patient prognosis and were further validated by the independent dataset GSE44001.

Conclusion

Our present study suggested that the immune-related scores based on ESTIMATE algorithm can help to screen out novel immune-related diagnostic indicators, therapeutic targets and prognostic predictors in CSCC.

Imaging Mass Spectrometry Reveals Tumor Metabolic Heterogeneity

Malignant tumors exhibit high degrees of genomic heterogeneity at the cellular level, leading to the view that subpopulations of tumor cells drive growth and treatment resistance. To examine the degree to which tumors also exhibit metabolic heterogeneity at the level of individual cells, we employed multi-isotope imaging mass spectrometry (MIMS) to quantify utilization of stable isotopes of glucose and glutamine along with a label for cell division. Mouse models of melanoma and malignant peripheral nerve sheath tumors (MPNSTs) exhibited striking heterogeneity of substrate utilization, evident in both proliferating and non-proliferating cells. We identified a correlation between metabolic heterogeneity, proliferation, and therapeutic resistance. Heterogeneity in metabolic substrate usage as revealed by incorporation of glucose and glutamine tracers is thus a marker for tumor proliferation. Collectively, our data demonstrate that MIMS provides a powerful tool with which to dissect metabolic functions of individual cells within the native tumor environment.

Differentiation of soft tissue and bone sarcomas from benign lesions utilizing 18F-FDG PET/CT-derived parameters

Background

Accurate differentiation between malignant and benign changes in soft tissue and bone lesions is essential for the prevention of unnecessary biopsies and surgical resection. Nevertheless, it remains a challenge and a standard diagnosis modality is urgently needed. The objective of this study was to evaluate the usefulness of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET/CT-derived parameters to differentiate soft tissue sarcoma (STS) and bone sarcoma (BS) from benign lesions.

Methods

Patients who had undergone pre-treatment ¹⁸F-FDG PET/CT imaging and subsequent pathological diagnoses to confirm malignant (STS and BS, n = 37) and benign (n = 33) soft tissue and bone lesions were retrospectively reviewed. The tumor size, PET and low-dose CT visual characteristics, maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and heterogeneous factor (HF) of each lesion were measured. Univariate and multivariate logistic regression analyses were conducted to determine the significant risk factors to distinguish sarcoma from benign lesions. To establish a regression model based on independent risk factors, and the receiver operating characteristic curves (ROCs) of individual parameters and their combination were plotted and compared. Conventional imaging scans were re-analyzed, and the diagnostic performance compared with the regression model.

Results

Univariate analysis results revealed that tumor size, SUVmax, MTV, TLG, and HF of ¹⁸F-FDG PET/CT imaging in the STS and BS group were all higher than in the benign lesions group (all P values were < 0.01). The differences in the visual characteristics between the two groups were also all statistically significant (P < 0.05). However, the multivariate regression model only included SUVmax and HF as independent risk factors, for which the odds ratios were 1.135 (95%CI: 1.026 ~ 1.256, P = 0.014) and 7.869 (95%CI: 2.119 ~ 29.230, P = 0.002), respectively. The regression model was constructed using the following expression: Logit (P) = − 2.461 + 0.127SUVmax + 2.063HF. The area under the ROC was 0.860, which was higher than SUVmax (0.744) and HF (0.790). The diagnostic performance of the regression model was superior to those of individual parameters and conventional imaging.

Conclusion

The regression model including SUVmax and HF based on ¹⁸F-FDG PET/CT imaging may be useful for differentiating STS and BS from benign lesions.

Parallel comparison and combining effect of radiomic and emerging genomic data for prognostic stratification of non-small cell lung carcinoma patients

BACKGROUND

A single institution retrospective analysis of 124 non-small cell lung carcinoma (NSCLC) patients was performed to identify whether disease-free survival (DFS) achieves incremental values when radiomic and genomic data are combined with clinical information.

METHODS

Using the least absolute shrinkage and selection operator (LASSO) Cox regression method, radiomic and genetic features were reduced in number for selection of the most useful prognostic feature. We created four models using only baseline clinical data, clinical data with selected genetic features, clinical data with selected radiomic features, and clinical data with selected genetic and radiomic features together. Multivariate Cox proportional hazards analysis was performed to determine predictors of DFS. Receiver operating characteristic (ROC) calculation was made to compare the discriminative performance for DFS prediction by four constructed models at the five-year time point.

RESULTS

On precontrast scan, improved discrimination performance was obtained in a merging of selected radiomics and genetics (AUC = 0.8638), compared with clinical data only (AUC = 0.7990), selected genetic features (AUC = 0.8497), and selected radiomic features (AUC = 0.8355). On post-contrast scan, discrimination performance was improved (AUC = 0.8672) compared with the clinical variables (AUC = 0.7913), and selected genetic features (AUC = 0.8376) and selected radiomic features (AUC = 0.8399) were considered.

CONCLUSIONS

The combination of selected radiomic and genomic features improved stratification of NSCLC patients upon survival. Thus, integrating clinicopathologic model with radiomic and genomic features may lead to improved prognostic accuracy compared to conventional clinicopathological data alone.

KEY POINTS

SIGNIFICANT FINDINGS OF THE STUDY: Receiver operating characteristic (ROC) calculation was made to compare the discriminative performance for disease-free survival (DFS). The discriminative performance for DFS was better when combining radiomic and genetic features compared to clinical data only, selected genetic features, and selected radiomic features.

WHAT THIS STUDY ADDS

The combination of selected radiomic and genomic features improved stratification of NSCLC patients upon survival. Thus, integrating a clinicopathological model with radiomic and genomic features may lead to improved prognostic accuracy compared to conventional clinicopathological data alone.

LOXL2 Expression Status Is Correlated With Molecular Characterizations of Cervical Carcinoma and Associated With Poor Cancer Survival via Epithelial-Mesenchymal Transition (EMT) Phenotype

As molecular analyses based on high-throughput sequencing have developed, the molecular classification of cancer has facilitated clinical work. The aim of the present study was to identify a new potential therapeutic target for cervical carcinoma by molecular analyses. We firstly tested the LOXL2 expression pattern in 50 paired normal cervix and cervical carcinoma via qPCR and immunohistochemistry, and the LOXL2 expression pattern was found to be in accordance with public datasets from Gene Expression Omnibus (GEO). Then, we comprehensively rewired the 176 cervical carcinoma samples from The Cancer Genome Atlas (TCGA), subsequently clustered the samples into two groups corresponding to LOXL2 expression to determined the associations between LOXL2 expression status and molecular characterizations of cervical carcinoma. In vitro assays for further verifying the correlations in SiHa-shLOXL2 and HeLa-shLOXL2 cell lines. In this study, we found that LOXL2 highly expressed in carcinoma tissue, with 14 CpG islands of LOXL2 promoter that were significantly and negatively associated with its expression in cervical carcinoma. And there were notable correlations among LOXL2 expression status and molecular characterizations of cervical carcinoma, including diagnostic age, HPV A7 types, mRNA molecular clusters, miRNA molecular clusters, and DNA methylation molecular clusters et al. In addition, high LOXL2 expression was negatively correlated with lower tumor mutation density, especially in EP300, ERBB2, EGFR and NOTCH2, and was negatively correlated with lower expression of APOBEC3 family genes, such as APOBEC3A, APOBEC3B, APOBEC3D, and APOBEC3G. Furthermore, high LOXL2 expression was associated with poor overall (OS) and poor disease-free survival (DFS) in cervical carcinoma, and was associated with higher epithelial-mesenchymal transition (EMT) score, enrichment of extracellular matrix (ECM) signaling, the phenotype that was found to be associated with poor prognosis in cervical carcinoma from TCGA. Conversely, the ability of cell proliferation and cell migration were reversed in LOXL2 knock-down cervical cell lines via regulating the genes' expression of EMT phenotype in vitro. Overall, we demonstrated the correlation between LOXL2 expression status and cancer molecular characterizations of cervical carcinoma, and identified LOXL2 may serve as a therapeutic target for such carcinoma.

Untargeted Tumor Metabolomics with Liquid Chromatography-Surface-Enhanced Raman Spectroscopy

Metabolomics is a powerful systems biology approach that monitors changes in biomolecule concentrations to diagnose and monitor health and disease. However, leading metabolomics technologies, such as NMR and mass spectrometry (MS), access only a small portion of the metabolome. Now an approach is presented that uses the high sensitivity and chemical specificity of surface-enhanced Raman scattering (SERS) for online detection of metabolites from tumor lysates following liquid chromatography (LC). The results demonstrate that this LC-SERS approach has metabolite detection capabilities comparable to the state-of-art LC-MS but suggest a selectivity for the detection of a different subset of metabolites. Analysis of replicate LC-SERS experiments exhibit reproducible metabolite patterns that can be converted into barcodes, which can differentiate different tumor models. Our work demonstrates the potential of LC-SERS technology for metabolomics-based diagnosis and treatment of cancer.

Modeling Tumor Evolutionary Dynamics to Predict Clinical Outcomes for Patients with Metastatic Colorectal Cancer: A Retrospective Analysis

Over 50% of colorectal cancer patients develop resistance after a transient response to therapy. Understanding tumor resistance from an evolutionary perspective leads to better predictions of treatment outcomes. The objectives of this study were to develop a computational framework to analyze tumor longitudinal measurements and recapitulate the individual evolutionary dynamics in metastatic colorectal cancer (mCRC) patients. A stochastic modeling framework was developed to depict the whole spectrum of tumor evolution prior to diagnosis and during and after therapy. The evolutionary model was optimized using a nonlinear mixed effect (NLME) method based on the longitudinal measurements of liver metastatic lesions from 599 mCRC patients. The deterministic limits in the NLME model were applied to optimize the stochastic model for each patient. Cox proportional hazards models coupled with the least absolute shrinkage and selection operator (LASSO) algorithm were applied to predict patients' progression-free survival (PFS) and overall survival (OS). The stochastic evolutionary model well described the longitudinal profiles of tumor sizes. The evolutionary parameters optimized for each patient indicated substantial interpatient variability. The number of resistant subclones at diagnosis was found to be a significant predictor to survival, and the hazard ratios with 95% CI were 1.09 (0.79-1.49) and 1.54 (1.01-2.34) for patients with three or more resistant subclones. Coupled with several patient characteristics, evolutionary parameters strongly predict patients' PFS and OS. A stochastic computational framework was successfully developed to recapitulate individual patient evolutionary dynamics, which could predict clinical survival outcomes in mCRC patients. SIGNIFICANCE: A data analysis framework depicts the individual evolutionary dynamics of mCRC patients and can be generalized to project patient survival outcomes.

A systematic flux analysis approach to identify metabolic vulnerabilities in human breast cancer cell lines

Background

Increased flux through both glycolytic and oxidative metabolic pathways is a hallmark of breast cancer cells and is critical for their growth and survival. As such, targeting this metabolic reprograming has received much attention as a potential treatment approach. However, the heterogeneity of breast cancer cell metabolism, even within classifications, suggests a necessity for an individualised approach to treatment in breast cancer patients.

Methods

The metabolic phenotypes of a diverse panel of human breast cancer cell lines representing the major breast cancer classifications were assessed using real-time metabolic flux analysis. Flux linked to ATP production, pathway reserve capacities and specific macromolecule oxidation rates were quantified. Suspected metabolic vulnerabilities were targeted with specific pathway inhibitors, and relative cell viability was assessed using the crystal violet assay. Measures of AMPK and mTORC1 activity were analysed through immunoblotting.

Results

Breast cancer cells displayed heterogeneous energy requirements and utilisation of non-oxidative and oxidative energy-producing pathways. Quantification of basal glycolytic and oxidative reserve capacities identified cell lines that were highly dependent on individual pathways, while assessment of substrate oxidation relative to total oxidative capacity revealed cell lines that were highly dependent on individual macromolecules. Based on these findings, mild mitochondrial inhibition in ESH-172 cells, including with the anti-diabetic drug metformin, and mild glycolytic inhibition in Hs578T cells reduced relative viability, which did not occur in non-transformed MCF10a cells. The effects on viability were associated with AMPK activation and inhibition of mTORC1 signalling. Hs578T were also found to be highly dependent on glutamine oxidation and inhibition of this process also impacted viability.

Conclusions

Together, these data highlight that systematic flux analysis in breast cancer cells can identify targetable metabolic vulnerabilities, despite heterogeneity in metabolic profiles between individual cancer cell lines.

Prognostic Significance of Metabolic Parameters and Textural Features on 18F-FDG PET/CT in Invasive Ductal Carcinoma of Breast

To investigate the prognostic significance of metabolic parameters and texture analysis on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) in patients with breast invasive ductal carcinoma (IDC), from August 2005 to May 2015, IDC patients who had undergone pre-treatment FDG PET/CT were enrolled. The metabolic parameters, including maximal standardized uptake value of breast tumor (SUVbt) and ipsilateral axillary lymph node (SUVln), metabolic tumor volume (MTVbt) and total lesion glycolysis (TLGbt) of breast tumor, whole-body MTV (MTVwb) and whole-body TLG (TLGwb) were recorded. Nine textural features of tumor (four co-occurrence matrices and five SUV-based statistics) were measured. The prognostic significance of above parameters and clinical factors was assessed by univariate and multivariate analyses. Thirty-five patients were enrolled. Patients with low and high MTVwb had 5-year progression-free survival (PFS) of 81.0 and 14.3% (p < 0.0001). The 5-year overall survival for low and high MTVwb was 88.5% and 43.6% (p = 0.0005). Multivariate analyses showed MTVwb was an independent prognostic factor for PFS (HR: 8.29, 95% CI: 2.17–31.64, p = 0.0020). The SUV, TLG and textural features were not independently predictive. Elevated MTVwb was an independent predictor for shorter PFS in patients with breast IDC.

Drugging cancer metabolism: Expectations vs. reality

As compared to their normal counterparts, neoplastic cells exhibit a variety of metabolic changes that reflect not only genetic and epigenetic defects underlying malignant transformation, but also the nutritional and immunobiological conditions of the tumor microenvironment. Such alterations, including the so-called Warburg effect (an increase in glucose uptake largely feeding anabolic and antioxidant metabolism), have attracted considerable attention as potential targets for the development of novel anticancer therapeutics. However, very few drugs specifically conceived to target bioenergetic cancer metabolism are currently approved by regulatory agencies for use in humans. This reflects the elevated degree of heterogeneity and redundancy in the metabolic circuitries exploited by neoplastic cells from different tumors (even of the same type), as well as the resemblance of such metabolic pathways to those employed by highly proliferating normal cells. Here, we summarize the major metabolic alterations that accompany oncogenesis, the potential of targeting bioenergetic metabolism for cancer therapy, and the obstacles that still prevent the clinical translation of such a promising therapeutic paradigm.

Prediction of occult lymph node metastasis using SUV, volumetric parameters and intratumoral heterogeneity of the primary tumor in T1-2N0M0 lung cancer patients staged by PET/CT

OBJECTIVE

The aim of this study was to identify whether PET/CT-related metabolic parameters of the primary tumor could predict occult lymph node metastasis (OLM) in patients with T1-2N0M0 NSCLC staged by ¹⁸F-FDG PET/CT.

METHODS

215 patients with clinical T1-2N0M0 (cT1-2N0M0) NSCLC who underwent both preoperative FDG PET/CT and surgical resection with the systematic lymph node dissection were included in the retrospective study. Heterogeneity factor (HF) was obtained by finding the derivative of the volume-threshold function from 40 to 80% of the maximum standardized uptake value (SUVmax). Univariate and multivariate stepwise logistic regression analyses were used to identify these PET parameters and clinicopathological variables associated with OLM.

RESULTS

Statistically significant differences were detected in sex, tumor site, SUVmax, mean SUV (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis and HF between patients with adenocarcinoma (ADC) and squamous cell carcinoma (SQCC). OLM was detected in 36 (16.7%) of 215 patients (ADC, 27/152 = 17.8% vs. SQCC, 9/63 = 14.3%). In multivariate analysis, MTV (OR = 1.671, P = 0.044) in ADC and HF (OR = 8.799, P = 0.023) in SQCC were potent associated factors for the prediction of OLM. The optimal cutoff values of 5.12 cm³ for MTV in ADC, and 0.198 for HF in SQCC were determined using receiver operating characteristic curve analysis.

CONCLUSIONS

In conclusion, MTV was an independent predictor of OLM in cT1-2N0M0 ADC patients, while HF might be the most powerful predictor for OLM in SQCC. These findings would be helpful in selecting patients who might be considered as candidates for sublobar resection or new stereotactic ablative radiotherapy.

Prediction of local relapse and distant metastasis in patients with definitive chemoradiotherapy-treated cervical cancer by deep learning from [18F]-fluorodeoxyglucose positron emission tomography/computed tomography

BACKGROUND

We designed a deep learning model for assessing ¹⁸F-FDG PET/CT for early prediction of local and distant failures for patients with locally advanced cervical cancer.

METHODS

All 142 patients with cervical cancer underwent ¹⁸F-FDG PET/CT for pretreatment staging and received allocated treatment. To augment the amount of image data, each tumor was represented as 11 slice sets each of which contains 3 2D orthogonal slices to acquire a total of 1562 slice sets. In each round of k-fold cross-validation, a well-trained proposed model and a slice-based optimal threshold were derived from a training set and used to classify each slice set in the test set into the categories of with or without local or distant failure. The classification results of each tumor were aggregated to summarize a tumor-based prediction result.

RESULTS

In total, 21 and 26 patients experienced local and distant failures, respectively. Regarding local recurrence, the tumor-based prediction result summarized from all test sets demonstrated that the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 71%, 93%, 63%, 95%, and 89%, respectively. The corresponding values for distant metastasis were 77%, 90%, 63%, 95%, and 87%, respectively.

CONCLUSION

This is the first study to use deep learning model for assessing ¹⁸F-FDG PET/CT images which is capable of predicting treatment outcomes in cervical cancer patients.

KEY POINTS

• This is the first study to use deep learning model for assessing ¹⁸ F-FDG PET/CT images which is capable of predicting treatment outcomes in cervical cancer patients. • All 142 patients with cervical cancer underwent ¹⁸ F-FDG PET/CT for pretreatment staging and received allocated treatment. To augment the amount of image data, each tumor was represented as 11 slice sets each of which contains 3 2D orthogonal slices to acquire a total of 1562 slice sets. • For local recurrence, all test sets demonstrated that the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 71%, 93%, 63%, 95%, and 89%, respectively. The corresponding values for distant metastasis were 77%, 90%, 63%, 95%, and 87%, respectively.

Chemoradiotherapy for locally advanced cervix cancer without aortic lymph node involvement: can we consider metabolic parameters of pretherapeutic FDG-PET/CT for treatment tailoring?

PURPOSE

Aim of the study was to assess impact of pretherapeutic FDG-PET/CT metabolic parameters on response to chemoradiotherapy (CRT) and survival in locally advanced cervical cancer (LACC) patients without paraaortic lymph node involvement.

METHODS

LACC patients treated with CRT without macrometastatic involvement after paraaortic surgical staging were included. All patients had received at least 45 Gy radiotherapy and five cycles of platinum-based chemotherapy. High-risk histologies were excluded. Two senior nuclear physician experts in gynaecologic oncology reviewed all PET/CT exams, and extracted tumor SUVmax, MTV, and TLG (standardized uptake value, metabolic tumor volume, and total lesion glycolysis respectively). Response to CRT was assessed with a pelvic MRI done after 45 Gy. Medical charts were reviewed for clinical, pathology, and survival data.

RESULTS

Ninety-three patients were included in the study. The overall survival (OS) rates at 2 and 5 years were 83.0% [95%CI: 72.5-89.8] and 71.2% [57.5-81.2] respectively. The RFS rates at 2 and 5 years were 72.5% [61.5-80.9] and 64.4% [52.3-74.2] respectively. Higher cervical SUVmax and TLG were significantly associated with poor response to CRT. In multivariate analysis, cervical SUVmax was the main predictive factor for OS.

CONCLUSION

Cervical tumor SUVmax was demonstrated to be a non-invasive prognostic biomarker for response to treatment and survival in LACC patients without paraaortic involvement. SUVmax and other PET/CT metabolic parameters require further prospective investigation to help tailoring of local treatment.

A meta-analysis of association of Human Leukocyte Antigens A, B, C, DR and DQ with Human Papillomavirus 16 infection

Human Papillomavirus (HPV) induced cervical cancer (CaCx) is a major health problem in women from both developing and developed regions of the world. This virus accounts for >95% of the CaCx cases with a preponderance of HPV type -16 (65%). Paradoxically HPV-16 is prevalent even in the cervix of healthier women and anti HPV-16 T-cell response is considered critical for the viral clearance. Studies on HLA association with HPV-16 infection and cervical cancer have yielded varied HLA associations in different epidemiological settings. To validate these associations, we performed a meta-analysis of HLA-A, B, C, DR and DQ association with HPV-16 infection. Of the 1409 studies retrieved, 26 qualified for meta-analysis based on stringent inclusion and exclusion criteria. HLA-B*47, B*57, DRB1*10, DRB1*15 and DQB1*0303 were significantly associated with HPV-16 infection (OR = 3.4, 1.8, 1.5, 1.1 and 1.5 respectively). HLA-B*49, B*39, A28 (serotype), C*04 and DRB1*13 were negatively associated with HPV-16 (OR = 0.5, 0.6, 0.7, 0.7, and 0.7 respectively). Certain HLA alleles such as B*07, DRB1*15, DRB1*11 and DRB1*07 showed weakly positive associations. A comprehensive analysis coupling HPV-16 antigenic diversity and the HLA variation in various global populations shall provide further insights into the immunogenetic predisposition to HPV-16 and shall help identify host-parasite co-evolution.

18F-FDG PET/CT in locally advanced cervical cancer: A review

Cervical cancer is the second most common gynecological cancer worldwide. In locally advanced cervical cancer, ¹⁸F-FDG PET/CT has become important in the initial staging, particularly in the detection of nodal and distant metastasis, aspects with treatment implications and prognostic value. The aims of this study were to review the role of ¹⁸F-FDG PET/CT in uterine cervical cancer, according to the guidelines of the main scientific institutions (FIGO, NCCN, SEGO, SEOM, ESGO, and ESMO) and its diagnostic accuracy compared to conventional radiological techniques, as well as to review the acquisition protocol and its utility in radiotherapy planning, response assessment and detection of recurrence.

Methylation-Based Classification of Cervical Squamous Cell Carcinoma into Two New Subclasses Differing in Immune-Related Gene Expression

Cervical cancer is traditionally classified into two major histological subtypes, cervical squamous cell carcinoma (CSCC) and cervical adenocarcinoma (CA). However, heterogeneity exists among patients, comprising possible subpopulations with distinct molecular profiles. We applied consensus clustering to 307 methylation samples with cervical cancer from The Cancer Genome Atlas (TCGA). Fisher’s exact test was used to perform transcription factors (TFs) and genomic region enrichment. Gene expression profiles were downloaded from TCGA to assess expression differences. Immune cell fraction was calculated to quantify the immune cells infiltration. Putative neo-epitopes were predicted from somatic mutations. Three subclasses were identified: Class 1 correlating with the CA subtype and Classes 2 and 3 dividing the CSCC subtype into two subclasses. We found the hypomethylated probes in Class 3 exhibited strong enrichment in promoter region as compared with Class 2. Five TFs significantly enriched in the hypomethylated promoters and their highly expressed target genes in Class 3 functionally involved in the immune pathway. Gene function analysis revealed that immune-related genes were significantly increased in Class 3, and a higher level of immune cell infiltration was estimated. High expression of 24 immune genes exhibited a better overall survival and correlated with neo-epitope burden. Additionally, we found only two immune-related driver genes, CARD11 and JAK3, to be significantly increased in Class 3. Our analyses provide a classification of the largest CSCC subtype into two new subclasses, revealing they harbored differences in immune-related gene expression.

Pretreatment 18F-FDG Uptake Heterogeneity Predicts Treatment Outcome of First-Line Chemotherapy in Patients with Metastatic Triple-Negative Breast Cancer

BACKGROUND

Intratumoral heterogeneity of 18F-fluorodeoxyglucose (18F-FDG) uptake in primary tumor has proven to be a surrogate marker for predicting treatment outcome in various tumors. However, the value of intraindividual heterogeneity in metastatic diseases remains unknown. The aim of this study was to evaluate pretreatment positron emission tomography/computed tomography (PET/CT) 18F-FDG-based heterogeneity for the prediction of first-line treatment outcome in metastatic triple-negative breast cancer (mTNBC).

MATERIALS AND METHODS

mTNBC patients from three clinical trials (NCT00601159, NCT01287624, and NCT02341911) with whole-body 18F-FDG PET/CT scan before first-line gemcitabine/platinum were included. Heterogeneity index (HI) and the maximum of FDG uptake (MAX) across total metastatic lesions (-T) on baseline PET/CT scans were assessed. HI was measured by MAX divided by the minimum FDG uptake across metastatic lesions. Optimal cutoffs were determined by time-dependent receiver operator characteristics (ROC) analysis. Progression-free survival (PFS) and overall survival (OS) were estimated by Kaplan-Meier method and compared by log-rank test.

RESULTS

A total of 42 mTNBC patients were included in this study. The median PFS of patients with high HI-T (>1.9) and high MAX-T (>10.5) was significantly shorter than patients with low HI-T (<1.9; p = .049) and low MAX-T (<10.5; p = .001). In terms of OS, only high MAX-T was significant for poorer outcome (p = .013). ROC curve analysis confirmed the predictive value of MAX and HI in mTNBC patients. Area under the ROC curve for MAX-T and HI-T was 0.75 and 0.65, indicating a higher predictive accuracy than conventional clinical risk factors.

CONCLUSION

HI and MAX measured among metastatic lesions on pretreatment 18F-FDG PET/CT scans could be potential predicators for first-line treatment outcome in patients with mTNBC.

IMPLICATIONS FOR PRACTICE

Intratumoral heterogeneity of 18F-fluorodeoxyglucose (FDG) uptake in primary tumor has proven to be a robust surrogate predictive marker. A novel positron emission tomography/computed tomography (PET/CT) parameter-heterogeneity index (HI) to quantify the heterogeneous characteristics of metastatic disease is proposed. Triple-negative breast cancer (TNBC) is a highly heterogeneous disease and remains a clinical challenge. The predictive performance of HI, along with the maximum FDG uptake (MAX), measured on pretreatment PET/CT scans in patients with metastatic TNBC was evaluated. Results indicate that HI and MAX may serve as applicable imaging predicators for treatment outcome of metastatic TNBC in clinical practice.

Textural features of cervical cancers on FDG-PET/CT associate with survival and local relapse in patients treated with definitive chemoradiotherapy

We retrospectively reviewed the records of 142 patients with stage IB–IIIB cervical cancer who underwent ¹⁸F-FDG-PET/CT before external beam radiotherapy plus intracavitary brachytherapy and concurrent chemotherapy. The patients were divided into training and validation cohorts to confirm the reliability of predictors for recurrence. Kaplan–Meier analysis was performed and a Cox regression model was used to examine the effects of variables on overall survival (OS), progression-free survival (PFS), distant metastasis-free survival (DMFS), and pelvic relapse-free survival (PRFS). High gray-level run emphasis (HGRE) derived from gray-level run-length matrix most accurately and consistently predicted the presence of pelvic residual or recurrent tumors for both cohorts. In multivariate analysis, stages IIIA–IIIB (P = 0.001, hazard ratio [HR] = 4.07) and a low HGRE (P < 0.0001, HR = 4.34) were prognostic factors for low OS, whereas a low HGRE (P = 0.001, HR = 2.86) and nonsquamous cell histology (P = 0.003, HR = 2.76) were prognostic factors for inferior PFS. The nonsquamous cell histology (P < 0.0001, HR = 9.19) and a low HGRE (P = 0.001, HR = 4.69) were predictors for low PRFS. In cervical cancer patients receiving definitive chemoradiotherapy, pretreatment textural features on ¹⁸F-FDG-PET/CT can supplement the prognostic information.

Pilot study of combined FDG-PET and dynamic contrast-enhanced CT of locally advanced cervical carcinoma before and during concurrent chemoradiotherapy suggests association between changes in tumor blood volume and treatment response

Modern PET/CT radiotherapy simulators offer FDG-PET and dynamic contrast-enhanced (DCE) CT imaging for combined volumetric assessment of tumor metabolism and perfusion. However, the clinical utility of such assessment has not been clearly defined. Thus, in a prospective longitudinal study of primary cervical tumors treated with concurrent chemoradiotherapy (CCRT) we evaluated: (1) whether PET and perfusion parameters correlate or provide complementary information; (2) what imaging changes occur during CCRT; and (3) whether any parameters are predictive of treatment response as assessed by PET/CT 3 months posttherapy. FDG-PET/CT and DCE-CT scans were performed on 21 patients prior to and during CCRT. Coregistered volumetric parametric maps of standardized uptake value (SUV) measures and perfusion parameters blood flow (BF), blood volume (BV), and permeability were generated. Summary statistics for these parameters and their changes were calculated within the metabolic tumor volume (MTV). Correlations between SUV and BF/BV/permeability on local and global bases were assessed with Pearson's coefficient r. MTV, maximum SUV, and mean SUV decreased significantly between the pre- and during-treatment time points, while mean BV and permeability increased significantly. Global correlations between mean BF/BV/permeability and mean SUV values (-.15 < r < .29) were at most moderate. An increase in mean tumor BV during treatment was significantly correlated with complete metabolic response on 3-month posttreatment PET/CT. Weak correlations of SUV and perfusion parameters suggest a complementary role of FDG-PET and DCE-CT for tumor characterization. The association between relative change in mean BV and outcome suggests a potential role for DCE-CT in early evaluation of cervical tumor response to chemoradiotherapy.

Spatial relationship of 2-deoxy-2-[18F]-fluoro-D-glucose positron emission tomography and magnetic resonance diffusion imaging metrics in cervical cancer

Background

This study investigated the spatial relationship of 2-deoxy-2-[¹⁸F]-fluoro-D-glucose positron emission tomography ([¹⁸F]FDG-PET) standardized uptake values (SUVs) and apparent diffusion coefficients (ADCs) derived from magnetic resonance (MR) diffusion imaging on a voxel level using simultaneously acquired PET/MR data.

We performed an institutional retrospective analysis of patients with newly diagnosed cervical cancer who received a pre-treatment simultaneously acquired [¹⁸F]FDG-PET/MR. Voxel SUV and ADC values, and global tumor metrics including maximum SUV (SUV_max), mean ADC (ADC_mean), and mean tumor-to-muscle ADC ratio (ADC_T/M) were compared. The impacts of histology, grade, and tumor volume on the voxel SUV to ADC relationship were also evaluated. The potential prognostic value of the voxel SUV/ADC relationship was evaluated in an exploratory analysis using Kaplan-Meier/log-rank and univariate Cox analysis.

Results

Seventeen patients with PET/MR scans were identified. There was a significant inverse correlation between SUV_max and ADC_mean, and SUV_max and ADC_T/M. In the voxelwise analysis, squamous cell carcinomas (SCCAs) and poorly differentiated tumors showed a consistent significant inverse correlation between voxel SUV and ADC values; adenocarcinomas (AdenoCAs) and well/moderately differentiated tumors did not. The strength of the voxel SUV/ADC correlation varied with metabolic tumor volume (MTV). On log-rank analysis, the correlation between voxel SUV/ADC values was prognostic of disease-free survival (DFS).

Conclusions

In this hypothesis-generating study, a consistent inverse correlation between voxel SUV and ADC values was seen in SCCAs and poorly differentiated tumors. On univariate statistical analysis, correlation between voxel SUV and ADC values was prognostic for DFS.

Electronic supplementary material

The online version of this article (10.1186/s13550-018-0403-7) contains supplementary material, which is available to authorized users.

Cancer stem cells (CSCs), cervical CSCs and targeted therapies

Accumulating evidence has shown that cancer stem cells (CSCs) have a tumour-initiating capacity and play crucial roles in tumour metastasis, relapse and chemo/radio-resistance. As tumour propagation initiators, CSCs are considered to be promising targets for obtaining a better therapeutic outcome. Cervical carcinoma is the most common gynaecological malignancy and has a high cancer mortality rate among females. As a result, the investigation of cervical cancer stem cells (CCSCs) is of great value. However, the numbers of cancer cells and corresponding CSCs in malignancy are dynamically balanced, and CSCs may reside in the CSC niche, about which little is known to date. Therefore, due to their complicated molecular phenotypes and biological behaviours, it remains challenging to obtain “purified” CSCs and continuously culture CSCs for further in vitro studies without the cells losing their stem properties. At present, CSC-related markers and functional assays are used to purify, identify and therapeutically target CSCs both in vitro and in vivo. Nevertheless, CSC-related markers are not universal to all tumour types, although some markers may be valid in multiple tumour types. Additionally, functional identifications based on CSC-specific properties are usually limited in in vivo studies. Furthermore, an optimal method for identifying potential CCSCs in CCSC studies has not been previously published, and these techniques are currently of great importance. This article updates our knowledge on CSCs and CCSCs, reviews potential stem cell markers and functional assays for identifying CCSCs, and describes the potential of targeting CCSCs in the treatment of cervical carcinoma.