Combining imaging- and gene-based hypoxia biomarkers in cervical cancer improves prediction of chemoradiotherapy failure independent of intratumour heterogeneity

A novel lineage-tracing tool reveals that hypoxic tumor cells drive tumor relapse after radiotherapy

PURPOSE

Tumor hypoxia imposes a main obstacle to the efficacy of anti-cancer therapy. Understanding the cellular dynamics of individual hypoxic cells before, during and post-treatment has been hampered by the technical inability to identify and trace these cells over time.

METHODS AND MATERIALS

Here, we present a novel lineage-tracing reporter for hypoxic cells based on the conditional expression of a HIF1a-CreERT2-UnaG biosensor that can visualize hypoxic cells in a time-dependent manner and trace the fate of hypoxic cells over time. We combine this system with multiphoton microscopy, flow cytometry, and immunofluorescence to characterize the role of hypoxic cells in tumor relapse after irradiation in H1299 tumor spheroids and in vivo xenografts.

RESULTS

We validate the reporter in monolayer cultures and we show that tagged cells colocalize in spheroids and human tumor xenografts with the hypoxic marker pimonidazole. We found that irradiation of H1299-HIFcreUnaG spheroids leads to preferential outgrowth of cells from the hypoxic core. Similarly, in xenografts tumors, although initially UnaG-positive-cells coincide with pimonidazole-positive tumor areas and they are merely quiescent, upon irradiation UnaG-positive cells enrich in regrowing tumors and are mainly proliferative.

CONCLUSIONS

Collectively, our data provide clear evidence that the hypoxic cells drive tumor relapse after irradiation.

Genetic overlap between breast cancer and sarcopenia: exploring the prognostic implications of SLC38A1 gene expression

BACKGROUND

Sarcopenia, an age-related syndrome characterized by a decline in muscle mass, not only affects patients' quality of life but may also increase the risk of breast cancer recurrence and reduce survival rates. Therefore, investigating the genetic mechanisms shared between breast cancer and sarcopenia is significant for the prevention, diagnosis, and treatment of breast cancer.

METHODS

This study downloaded gene expression datasets and clinical data related to breast cancer and skeletal muscle aging from the GEO database. Data preprocessing, integration, differential gene identification, functional enrichment analysis, and construction of protein-protein interaction networks were performed using R language. Subsequently, COX proportional hazards model analysis and survival analysis were conducted, and survival curves and nomograms were generated. The expression levels of genes in tissues were detected using qRT-PCR, and the Radiant DICOM viewer software was used to delineate the pectoralis major muscle area in CT images.

RESULTS

We identified 152 differentially expressed genes (P < .05) and 226 sarcopenia-related genes (r > .4) associated with skeletal muscle aging. The TCGA-BRCA dataset revealed 106 genes associated with breast cancer (P < .05, logFC = 1). Functional enrichment analysis indicated significant enrichment in cell proliferation and growth pathways. The PPI network identified critical molecules involved in muscle aging and tumor progression. After dimensionality reduction, a strong correlation was observed between the expression of the muscle aging-related gene set and the prognosis of breast cancer patients (P < .01). The expression of SLC38A1 identified through multivariate COX analysis was significantly associated with poor prognosis in breast cancer patients (P = .03). Incorporating SLC38A1 expression, the prognostic model precisely forecasted breast cancer survival (P < .01). External validation confirmed the higher expression of the SLC38A1 gene in breast cancer tissues compared to adjacent non-cancerous tissues (P < .01). The SLC38A1 index, calculated in combination with the patient's age and BMI, can optimize the prognostic prediction model, providing a powerful tool for personalized treatment of breast cancer.

CONCLUSION

High SLC38A1 gene expression was significantly associated with poor prognosis in breast cancer patients. The combination of SLC38A1 expression and the pectoralis major muscle area provided an optimized prognostic prediction model, offering a potential tool for personalized breast cancer treatment.

JAK2/ULK1 axis promotes cervical cancer progression by autophagy induction and SRPK1 phosphorylation

Cervical cancer is the most common gynecologic cancer. Autophagy is involved in the progression of CCa. ULK1 is a crucial kinase in autophagy initiation. However, few studies have investigated the role of ULK1 phosphorylation at tyrosine residues in the progression of CCa, and the underlying mechanism remains elusive. In this study, we demonstrated that JAK2 is a novel upstream kinase that phosphorylates ULK1 at the tyrosine site. JAK2 interacts with and phosphorylates ULK1 at Tyr1007. The phosphorylation of ULK1 at Y1007 increases its activity and stability, activates autophagy, and promotes the progression of CCa. We further showed that the phosphorylation of ULK1 at Y1007 is a predictive marker of CCa patient outcome. Furthermore, we identified SRPK1 as a potential downstream substrate of ULK1 to promote the progression of CCa. Our research sheds light on the molecular mechanism of CCa progression, through JAK2/ULK1 axis, and emphasizes the phosphorylation of ULK1 at Y1007 as a predictor of CCa.

MRI-guided dynamic risk assessment in cervical cancer based on tumor hypoxia at diagnosis and volume response at brachytherapy

BACKGROUND AND PURPOSE

Improvements in treatment outcome for patients with locally advanced cervical cancer (LACC) require a better classification of patients according to their risk of recurrence. We investigated whether an imaging-based approach, combining pretreatment hypoxia and tumor response during therapy, could improve risk classification.

MATERIAL AND METHODS

Ninety-three LACC patients with T2-weigthed (T2W)-, dynamic contrast enhanced (DCE)- and diffusion weighted (DW)-magnetic resonance (MR) images acquired before treatment, and T2W- and, for 64 patients, DW-MR images, acquired at brachytherapy, were collected. Pretreatment hypoxic fraction (HFpre) was determined from DCE- and DW-MR images using the consumption and supply-based hypoxia (CSH)-imaging method. Volume regression at brachytherapy was assessed from T2W-MR images and combined with HFpre. In 17 patients with adequate DW-MR images at brachytherapy, the apparent diffusion coefficient (ADC), reflecting tumor cell density, was calculated. Change in ADC during therapy was combined with volume regression yielding functional regression as explorative response measure. Endpoint was disease free survival (DFS).

RESULTS

HFpre was the strongest predictor of DFS, but a significant correlation with outcome was found also for volume regression. The combination of HFpre and volume regression showed a stronger association with DFS than HFpre alone. Patients with disease recurrence were selected to either the intermediate- or high-risk group with a 100 % accuracy. Functional regression showed a stronger correlation to HFpre than volume regression.

CONCLUSION

The combination of pretreatment hypoxia and volume regression at brachytherapy improved patient risk classification. Integration of ADC with volume regression showed promise as a new tumor response parameter.

Hypoxia as a potential inducer of immune tolerance, tumor plasticity and a driver of tumor mutational burden: Impact on cancer immunotherapy

In cancer patients, immune cells are often functionally compromised due to the immunosuppressive features of the tumor microenvironment (TME) which contribute to the failures in cancer therapies. Clinical and experimental evidence indicates that developing tumors adapt to the immunological environment and create a local microenvironment that impairs immune function by inducing immune tolerance and invasion. In this context, microenvironmental hypoxia, which is an established hallmark of solid tumors, significantly contributes to tumor aggressiveness and therapy resistance through the induction of tumor plasticity/heterogeneity and, more importantly, through the differentiation and expansion of immune-suppressive stromal cells. We and others have provided evidence indicating that hypoxia also drives genomic instability in cancer cells and interferes with DNA damage response and repair suggesting that hypoxia could be a potential driver of tumor mutational burden. Here, we reviewed the current knowledge on how hypoxic stress in the TME impacts tumor angiogenesis, heterogeneity, plasticity, and immune resistance, with a special interest in tumor immunogenicity and hypoxia targeting. An integrated understanding of the complexity of the effect of hypoxia on the immune and microenvironmental components could lead to the identification of better adapted and more effective combinational strategies in cancer immunotherapy. Clearly, the discovery and validation of therapeutic targets derived from the hypoxic tumor microenvironment is of major importance and the identification of critical hypoxia-associated pathways could generate targets that are undeniably attractive for combined cancer immunotherapy approaches.

Prediction of prostate tumour hypoxia using pre-treatment MRI-derived radiomics: preliminary findings

PURPOSE

To develop a machine learning (ML) model based on radiomic features (RF) extracted from whole prostate gland magnetic resonance imaging (MRI) for prediction of tumour hypoxia pre-radiotherapy.

MATERIAL AND METHODS

Consecutive patients with high-grade prostate cancer and pre-treatment MRI treated with radiotherapy between 01/12/2007 and 1/08/2013 at two cancer centres were included. Cancers were dichotomised as normoxic or hypoxic using a biopsy-based 32-gene hypoxia signature (Ragnum signature). Prostate segmentation was performed on axial T2-weighted (T2w) sequences using RayStation (v9.1). Histogram standardisation was applied prior to RF extraction. PyRadiomics (v3.0.1) was used to extract RFs for analysis. The cohort was split 80:20 into training and test sets. Six different ML classifiers for distinguishing hypoxia were trained and tuned using five different feature selection models and fivefold cross-validation with 20 repeats. The model with the highest mean validation area under the curve (AUC) receiver operating characteristic (ROC) curve was tested on the unseen set, and AUCs were compared via DeLong test with 95% confidence interval (CI).

RESULTS

195 patients were included with 97 (49.7%) having hypoxic tumours. The hypoxia prediction model with best performance was derived using ridge regression and had a test AUC of 0.69 (95% CI: 0.14). The test AUC for the clinical-only model was lower (0.57), but this was not statistically significant (p = 0.35). The five selected RFs included textural and wavelet-transformed features.

CONCLUSION

Whole prostate MRI-radiomics has the potential to non-invasively predict tumour hypoxia prior to radiotherapy which may be helpful for individualised treatment optimisation.

ROS-Triggered Self-Assembled Nanoparticles Based on a Chemo-Sonodynamic Combinational Therapy Strategy for the Noninvasive Elimination of Hypoxic Tumors

The hypopermeability and hypoxia in the tumor milieu are important factors that limit multiple treatments. Herein, the reactive oxygen species (ROS)-triggered self-assembled nanoparticles (RP-NPs) was constructed. The natural small molecule Rhein (Rh) was encapsulated into RP-NPs as a sonosensitizer highly accumulated at the tumor site. Then highly tissue-permeable ultrasound (US) irradiation induced apoptosis of tumor cells through the excitation of Rh and acoustic cavitation, which prompted the rapid production of large amounts of ROS in the hypoxic tumor microenvironment. In addition, the thioketal bond structures in the innovatively designed prodrug LA-GEM were triggered and broken by ROS to achieve rapid targeted release of the gemcitabine (GEM). Sonodynamic therapy (SDT) increased the tissue permeability of solid tumors and actively disrupted redox homeostasis via mitochondrial pathways to kill hypoxic tumor cells, and the triggered response mechanism to GEM synergistically amplified the effect of chemotherapy. The chemo-sonodynamic combinational treatment approach is highly effective and noninvasive, with promising applications for hypoxic tumor elimination, such as in cervical cancer (CCa) patients who want to maintain their reproductive function.

Risk of recurrence after chemoradiotherapy identified by multimodal MRI and 18F-FDG-PET/CT in locally advanced cervical cancer

BACKGROUND AND PURPOSE

MRI, applying dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) sequences, and 18F-fluorodeoxyglucose (18F-FDG) PET/CT provide information about tumor aggressiveness that is unexploited in treatment of locally advanced cervical cancer (LACC). We investigated the potential of a multimodal combination of imaging parameters for classifying patients according to their risk of recurrence.

MATERIALS AND METHODS

Eighty-two LACC patients with diagnostic MRI and FDG-PET/CT, treated with chemoradiotherapy, were collected. Thirty-eight patients with MRI only were included for validation of MRI results. Endpoints were survival (disease-free, cancer-specific, overall) and tumor control (local, locoregional, distant). K^trans, reflecting vascular function, apparent diffusion coefficient (ADC), reflecting cellularity, and standardized uptake value (SUV), reflecting glucose uptake, were extracted from DCE-MR, DW-MR and FDG-PET images, respectively. By applying an oxygen consumption and supply-based method, ADC and K^trans parametric maps were voxel-wise combined into hypoxia images that were used to determine hypoxic fraction (HF).

RESULTS

HF showed a stronger association with outcome than the single modality parameters. This association was confirmed in the validation cohort. Low HF identified low-risk patients with 95% precision. Based on the 50th SUV-percentile (SUV₅₀), patients with high HF were divided into an intermediate- and high-risk group with high and low SUV₅₀, respectively. This defined a multimodality biomarker, HF/SUV₅₀. HF/SUV₅₀ increased the precision of detecting high-risk patients from 41% (HF alone) to 57% and showed prognostic significance in multivariable analysis for all endpoints.

CONCLUSION

Multimodal combination of MR- and FDG-PET/CT-images improves classification of LACC patients compared to single modality images and clinical factors.

The Role of Imaging Biomarkers to Guide Pharmacological Interventions Targeting Tumor Hypoxia

Hypoxia is a common feature of solid tumors that contributes to angiogenesis, invasiveness, metastasis, altered metabolism and genomic instability. As hypoxia is a major actor in tumor progression and resistance to radiotherapy, chemotherapy and immunotherapy, multiple approaches have emerged to target tumor hypoxia. It includes among others pharmacological interventions designed to alleviate tumor hypoxia at the time of radiation therapy, prodrugs that are selectively activated in hypoxic cells or inhibitors of molecular targets involved in hypoxic cell survival (i.e., hypoxia inducible factors HIFs, PI3K/AKT/mTOR pathway, unfolded protein response). While numerous strategies were successful in pre-clinical models, their translation in the clinical practice has been disappointing so far. This therapeutic failure often results from the absence of appropriate stratification of patients that could benefit from targeted interventions. Companion diagnostics may help at different levels of the research and development, and in matching a patient to a specific intervention targeting hypoxia. In this review, we discuss the relative merits of the existing hypoxia biomarkers, their current status and the challenges for their future validation as companion diagnostics adapted to the nature of the intervention.

A prognostic hypoxia gene signature with low heterogeneity within the dominant tumour lesion in prostate cancer patients

BACKGROUND

Gene signatures measured in a biopsy have been proposed as hypoxia biomarkers in prostate cancer. We assessed a previously developed signature, and aimed to determine its relationship to hypoxia and its heterogeneity within the dominant (index) lesion of prostate cancer.

METHODS

The 32-gene signature was assessed from gene expression data of 141 biopsies from the index lesion of 94 patients treated with prostatectomy. A gene score calculated from the expression levels was applied in the analyses. Hypoxic fraction from pimonidazole immunostained whole-mount and biopsy sections was used as reference standard for hypoxia.

RESULTS

The gene score was correlated with pimonidazole-defined hypoxic fraction in whole-mount sections, and the two parameters showed almost equal association with clinical markers of tumour aggressiveness. Based on the gene score, incorrect classification according to hypoxic fraction in whole-mount sections was seen in one third of the patients. The incorrect classifications were apparently not due to intra-tumour heterogeneity, since the score had low heterogeneity compared to pimonidazole-defined hypoxic fraction in biopsies. The score showed prognostic significance in uni-and multivariate analysis in independent cohorts.

CONCLUSIONS

Our signature from the index lesion reflects tumour hypoxia and predicts prognosis in prostate cancer, independent of intra-tumour heterogeneity in pimonidazole-defined hypoxia.

A promising prognostic signature for lung adenocarcinoma (LUAD) patients basing on 6 hypoxia-related genes

BACKGROUND

Hypoxia signaling plays a critical role in the development of lung adenocarcinoma (LUAD). We herein aimed to explore the prognostic value of hypoxia-related genes and construct the hypoxia-related prognostic signature for LUAD patients.

METHODS

A total of 26 hypoxia-related genes were collected. Five hundred thirteen and 246 LUAD samples were obtained from the Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. Univariate Cox regression and LASSO Cox regression analyses were conducted to screen the hypoxia-related genes associated with the prognosis of LUAD patients, which would be used for constructing prognosis predictive model for LUAD patients. Multivariate Cox regression analysis was done to determine the independent prognostic factors. The Nomogram model was constructed to predict the prognosis of LUAD patients.

RESULTS

Based on 26 hypoxia-related genes, LUAD samples could be divided into 4 clusters with different prognoses. Among which, 6 genes were included to construct the Risk Score and the LUAD patients with higher Risk Score had worse prognosis. Besides, the Nomogram based on all the independent risk factors could relatively reliably predict the survival probability. And 9 types of immune cells' infiltration was significantly differential between high and low risk LUAD patients.

CONCLUSION

The Risk Score model based on the 6 crucial hypoxia-related genes could relatively reliably predict the prognosis of LUAD patients.

Predicting Response to Chemotherapy in Patients With Newly Diagnosed High-Risk Neuroblastoma: A Report From the International Neuroblastoma Risk Group

PURPOSE

Metaiodobenzylguanidine (MIBG) scans are a radionucleotide imaging modality that undergo Curie scoring to semiquantitatively assess neuroblastoma burden, which can be used as a marker of therapy response. We hypothesized that a convolutional neural network (CNN) could be developed that uses diagnostic MIBG scans to predict response to induction chemotherapy.

METHODS

We analyzed MIBG scans housed in the International Neuroblastoma Risk Group Data Commons from patients enrolled in the Children's Oncology Group high-risk neuroblastoma study ANBL12P1. The primary outcome was response to upfront chemotherapy, defined as a Curie score ≤ 2 after four cycles of induction chemotherapy. We derived and validated a CNN using two-dimensional whole-body MIBG scans from diagnosis and evaluated model performance using area under the receiver operating characteristic curve (AUC). We also developed a clinical classification model to predict response on the basis of age, stage, and MYCN amplification.

RESULTS

Among 103 patients with high-risk neuroblastoma included in the final cohort, 67 (65%) were responders. Performance in predicting response to upfront chemotherapy was equivalent using the CNN and the clinical model. Class-activation heatmaps verified that the CNN used areas of disease within the MIBG scans to make predictions. Furthermore, integrating predictions using a geometric mean approach improved detection of responders to upfront chemotherapy (geometric mean AUC 0.73 v CNN AUC 0.63, P < .05; v clinical model AUC 0.65, P < .05).

CONCLUSION

We demonstrate feasibility in using machine learning of diagnostic MIBG scans to predict response to induction chemotherapy for patients with high-risk neuroblastoma. We highlight improvements when clinical risk factors are also integrated, laying the foundation for using a multimodal approach to guiding treatment decisions for patients with high-risk neuroblastoma.

A four immune-related long noncoding RNAs signature as predictors for cervical cancer

The progression, metastasis, and prognosis of cervical cancer (CC) is influenced by the tumor immune microenvironment. Studies proved that long non-coding RNAs (lncRNAs) to engage in cervical cancer development, especially immune-related lncRNAs, have emerged crucial in the tumor immune process. This study was set out to identify an immune-related lncRNA signature. In total, 13,838 lncRNA expression profiles and 328 immune genes were acquired from the clnical data of 306 CC tissues and 3 non-CC tissues. From the 433 identified immune-related lncRNAs, 4 candidate immune-related lncRNAs (SOX21-AS1, AC005332.4, NCK1-DT, LINC01871) were considered independent indicators of cervical cancer prognosis through the univariate and multivariate Cox regression analysis, and they were used to construct a prognostic and survival lncRNA signature model followed by the bootstrap method for further verification. Kaplan-Meier curves illustrated that cervical cancer patients could be divided into high-risk and low-risk groups with significant differences (P = 2.052e - 05), and the discrepancy of immune profiles between these two risk groups was illustrated by principal components analysis. Taken together, the novel survival predictive model created by the four immune-related lncRNAs showed promising clinical prediction value in cervical cancer.

Impact of hypoxia on cervical cancer outcomes

The annual global incidence of cervical cancer is approximately 604 000 cases/342 000 deaths, making it the fourth most common cancer in women. Cervical cancer is a major healthcare problem in low and middle income countries where 85% of new cases and deaths occur. Secondary prevention measures have reduced incidence and mortality in developed countries over the past 30 years, but cervical cancer remains a major cause of cancer deaths in women. For women who present with Fédération Internationale de Gynécologie et d'Obstétrique (FIGO 2018) stages IB3 or upwards, chemoradiation is the established treatment. Despite high rates of local control, overall survival is less than 50%, largely due to distant relapse. Reducing the health burden of cervical cancer requires greater individualization of treatment, identifying those at risk of relapse and progression for modified or intensified treatment. Hypoxia is a well known feature of solid tumors and an established therapeutic target. Low tumorous oxygenation increases the risk of local invasion, metastasis and treatment failure. While meta-analyses show benefit, many individual trials targeting hypoxia failed in part due to not selecting patients most likely to benefit. This review summarizes the available hypoxia-targeted strategies and identifies further research and new treatment paradigms needed to improve patient outcomes. The applications and limitations of hypoxia biomarkers for treatment selection and response monitoring are discussed. Finally, areas of greatest unmet clinical need are identified to measure and target hypoxia and therefore improve cervical cancer outcomes.

Progression Risk Score Estimation Based on Immunostaining Data in Oral Cancer Using Unsupervised Hierarchical Clustering Analysis: A Retrospective Study in Taiwan

This study aimed to investigate whether the progression risk score (PRS) developed from cytoplasmic immunohistochemistry (IHC) biomarkers is available and applicable for assessing risk and prognosis in oral cancer patients. Participants in this retrospective case-control study were diagnosed between 2012 and 2014 and subsequently underwent surgical intervention. The specimens from surgery were stained by IHC for 16 cytoplasmic target markers. We evaluated the results of IHC staining, clinical and pathological features, progression-free survival (PFS), and overall survival (OS) of 102 oral cancer patients using a novel estimation approach with unsupervised hierarchical clustering analysis. Patients were stratified into high-risk (52) and low-risk (50) groups, according to their PRS; a metric consisting of cytoplasmic PLK1, PhosphoMet, SGK2, and SHC1 expression. Moreover, PRS could be extended for use in the Cox proportional hazard regression model to estimate survival outcomes with associated clinical parameters. Our study findings revealed that the high-risk patients had a significantly increased risk in cancer progression compared with low-risk patients (hazard ratio (HR) = 2.20, 95% confidence interval (CI) = 1.10-2.42, p = 0.026). After considering the influences of demographics, risk behaviors, and tumor characteristics, risk estimation with PRS provided distinct PFS groups for patients with oral cancer (p = 0.017, p = 0.019, and p = 0.020). Our findings support that PRS could serve as an ideal biomarker for clinical use in risk stratification and progression assessment in oral cancer.

Perspectives on Hypoxia Signaling in Tumor Stroma

Hypoxia is a well-known characteristic of solid tumors that contributes to tumor progression and metastasis. Oxygen deprivation due to high demand of proliferating cancer cells and standard of care therapies induce hypoxia. Hypoxia signaling, mainly mediated by the hypoxia-inducible transcription factor (HIF) family, results in tumor cell migration, proliferation, metabolic changes, and resistance to therapy. Additionally, the hypoxic tumor microenvironment impacts multiple cellular and non-cellular compartments in the tumor stroma, including disordered tumor vasculature, homeostasis of ECM. Hypoxia also has a multifaceted and often contradictory influence on immune cell function, which contributes to an immunosuppressive environment. Here, we review the important function of HIF in tumor stromal components and summarize current clinical trials targeting hypoxia. We provide an overview of hypoxia signaling in tumor stroma that might help address some of the challenges associated with hypoxia-targeted therapies.

Pretreatment [18F]FDG PET/CT Prognostic Factors in Patients with Squamous Cell Cervical Carcinoma FIGO IIIC1

PURPOSE

This study aims to determine whether semiquantitative parameters obtained from both the primary tumor and metastatic pelvic lymph nodes (PLN) diagnosed in fluoro-18-deoxy-glucose positron emission tomography (FDG-PET-CT) are associated with disease-free survival (DFS), local control (LC), distant metastasis-free survival (DMFS) and overall survival (OS) in patients with locally advanced squamous cervical cancer (LACC) and metastatic pelvic lymph nodes.

MATERIALS

Retrospective analysis was performed on 93 female patients with FIGO IIIC1. The median age was 53 years (27-75). The PET parameters both in the primary tumor and metastatic pelvic lymph nodes, including SUVmax, SUVmean, TLG, MTV, heterogeneity, along with clinical variables, before radical cisplatin-based radiochemotherapy (RCT) were analyzed. The p-values < 0.05 were considered statistically significant.

RESULTS

Median follow-up was 38 months (4.5-92.6). Three years and five years OS were 75% and 70% respectively. Patients with SUVmax above 12.6, SUVmean above 7.6 and with TLG in tumors >245.7 lived longer (p < 0.05). The higher SUVmax or SUVmean reduced increased DMFS (HR 0.3 95%CI 0.56-0.96 and 0.59 95%CI 0.37-0.93). The clinical factors and other FDG PET CT parameters were not found to be statistically relevant in terms of OS, DFS, DM and LC.

CONCLUSIONS

This study is the first report showing that in LACC patient population with PLN involvement treated with definitive RCT, high SUVmean, SUVmax and TLG of the primary tumor in FDG-PET-CT were linked with longer OS. Lower SUVmean and SUVmax were linked with shorter DMFS. None of the clinical factors and the nodal FDG-PET-CT parameters influenced the outcome.

Tumor Hypoxia Regulates Immune Escape/Invasion: Influence on Angiogenesis and Potential Impact of Hypoxic Biomarkers on Cancer Therapies

The environmental and metabolic pressures in the tumor microenvironment (TME) play a key role in molding tumor development by impacting the stromal and immune cell fractions, TME composition and activation. Hypoxia triggers a cascade of events that promote tumor growth, enhance resistance to the anti-tumor immune response and instigate tumor angiogenesis. During growth, the developing angiogenesis is pathological and gives rise to a haphazardly shaped and leaky tumor vasculature with abnormal properties. Accordingly, aberrantly vascularized TME induces immunosuppression and maintains a continuous hypoxic state. Normalizing the tumor vasculature to restore its vascular integrity, should hence enhance tumor perfusion, relieving hypoxia, and reshaping anti-tumor immunity. Emerging vascular normalization strategies have a great potential in achieving a stable normalization, resulting in mature and functional blood vessels that alleviate tumor hypoxia. Biomarkers enabling the detection and monitoring of tumor hypoxia could be highly advantageous in aiding the translation of novel normalization strategies to clinical application, alone, or in combination with other treatment modalities, such as immunotherapy.