Glucose metabolism in NSCLC is histology-specific and diverges the prognostic potential of 18FDG-PET for adenocarcinoma and squamous cell carcinoma

Global transcriptomic network analysis of the crosstalk between microbiota and cancer-related cells in the oral-gut-lung axis

Background

The diagnosis and treatment of lung, colon, and gastric cancer through the histologic characteristics and genomic biomarkers have not had a strong impact on the mortality rates of the top three global causes of death by cancer.

Methods

Twenty-five transcriptomic analyses (10 lung cancer, 10 gastric cancer, and 5 colon cancer datasets) followed our own bioinformatic pipeline based on the utilization of specialized libraries from the R language and DAVID´s gene enrichment analyses to identify a regulatory metafirm network of transcription factors and target genes common in every type of cancer, with experimental evidence that supports its relationship with the unlocking of cell phenotypic plasticity for the acquisition of the hallmarks of cancer during the tumoral process. The network's regulatory functional and signaling pathways might depend on the constant crosstalk with the microbiome network established in the oral-gut-lung axis.

Results

The global transcriptomic network analysis highlighted the impact of transcription factors (SOX4, TCF3, TEAD4, ETV4, and FOXM1) that might be related to stem cell programming and cancer progression through the regulation of the expression of genes, such as cancer-cell membrane receptors, that interact with several microorganisms, including human T-cell leukemia virus 1 (HTLV-1), the human papilloma virus (HPV), the Epstein-Barr virus (EBV), and SARS-CoV-2. These interactions can trigger the MAPK, non-canonical WNT, and IFN signaling pathways, which regulate key transcription factor overexpression during the establishment and progression of lung, colon, and gastric cancer, respectively, along with the formation of the microbiome network.

Conclusion

The global transcriptomic network analysis highlights the important interaction between key transcription factors in lung, colon, and gastric cancer, which regulates the expression of cancer-cell membrane receptors for the interaction with the microbiome network during the tumorigenic process.

Differential Diagnosis of Pathological Type of Peripheral Lung Cancer with Multimodal Contrast-Enhanced Ultrasound

OBJECTIVE

The goal of the work described here was to investigate the role of multimodal contrast-enhanced ultrasound in the differential diagnosis of peripheral lung cancer.

METHODS

From April 2017 to July 2021, 109 patients with confirmed pulmonary malignant lesions who underwent CEUS examination were involved in our study. Seven patients were excluded because of the short duration of CEUS video or unsatisfactory imaging. Finally,102 patients with peripheral lung cancer were enrolled in this study. The maximum diameter of the lesions ranged from 1.6 to 13.0 cm (mean 6.2 ± 2.3 cm). On the basis of the pathological results, the patients were divided into the small cell lung cancer (SCLC) group and non-small cell lung cancer (NSCLC) group (including adenocarcinoma, lung squamous cell carcinoma and large cell neuroendocrine carcinoma). A Logiq E9 ultrasonic machine equipped with a 3.5 to 5.0 MHz C5-1 probe was used. Patient clinical information, CEUS features, CPI patterns and TIC parameters were analyzed and compared between different groups. Statistical analyses were performed with SPSS software and MedCalc software. The receiver operating characteristic curve was plotted.

RESULTS

In the differential diagnosis of SCLC and NSCLC, color parametric imaging indicated great performance. NSCLC exhibited a centripetal enhancement pattern more frequently (72.7%), while SCLC exhibited an eccentric enhancement pattern more frequently (92.9%) (p < 0.001). In the differential diagnosis of adenocarcinoma and squamous cell carcinoma, logistic regression analysis revealed that patient age of onset ≤60 y, difference in arrival time between lung and tumor ≤3.8 s, drop time of the time-intensity curve >23.2 s and absence of internal necrosis on CEUS were independent predictors for adenocarcinoma (area under the curve = 0.861).

CONCLUSION

In our study, multimodal contrast-enhanced ultrasound provided useful information in the differential diagnosis between small cell lung cancer and non-small cell lung cancer, especially between adenocarcinoma and squamous cell carcinoma.

Spatial Architecture of Myeloid and T Cells Orchestrates Immune Evasion and Clinical Outcome in Lung Cancer

Understanding the role of the tumor microenvironment (TME) in lung cancer is critical to improving patient outcomes. We identified four histology-independent archetype TMEs in treatment-naïve early-stage lung cancer using imaging mass cytometry in the TRACERx study (n = 81 patients/198 samples/2.3 million cells). In immune-hot adenocarcinomas, spatial niches of T cells and macrophages increased with clonal neoantigen burden, whereas such an increase was observed for niches of plasma and B cells in immune-excluded squamous cell carcinomas (LUSC). Immune-low TMEs were associated with fibroblast barriers to immune infiltration. The fourth archetype, characterized by sparse lymphocytes and high tumor-associated neutrophil (TAN) infiltration, had tumor cells spatially separated from vasculature and exhibited low spatial intratumor heterogeneity. TAN-high LUSC had frequent PIK3CA mutations. TAN-high tumors harbored recently expanded and metastasis-seeding subclones and had a shorter disease-free survival independent of stage. These findings delineate genomic, immune, and physical barriers to immune surveillance and implicate neutrophil-rich TMEs in metastasis.

SIGNIFICANCE

This study provides novel insights into the spatial organization of the lung cancer TME in the context of tumor immunogenicity, tumor heterogeneity, and cancer evolution. Pairing the tumor evolutionary history with the spatially resolved TME suggests mechanistic hypotheses for tumor progression and metastasis with implications for patient outcome and treatment. This article is featured in Selected Articles from This Issue, p. 897.

Histology-driven hypofractionated radiation therapy schemes for early-stage lung adenocarcinoma and squamous cell carcinoma

BACKGROUND AND PURPOSE

Histology was found to be an important prognostic factor for local tumor control probability (TCP) after stereotactic body radiotherapy (SBRT) of early-stage non-small-cell lung cancer (NSCLC). A histology-driven SBRT approach has not been explored in routine clinical practice and histology-dependent fractionation schemes remain unknown. Here, we analyzed pooled histologic TCP data as a function of biologically effective dose (BED) to determine histology-driven fractionation schemes for SBRT and hypofractionated radiotherapy of two predominant early-stage NSCLC histologic subtypes adenocarcinoma (ADC) and squamous cell carcinoma (SCC).

MATERIAL AND METHODS

The least-χ2 method was used to fit the collected histologic TCP data of 8510 early-stage NSCLC patients to determine parameters for a well-developed radiobiological model per the Hypofractionated Treatment Effects in the Clinic (HyTEC) initiative.

RESULTS

A fit to the histologic TCP data yielded independent radiobiological parameter sets for radiotherapy of early-stage lung ADC and SCC. TCP increases steeply with BED and reaches an asymptotic maximal plateau, allowing us to determine model-independent optimal fractionation schemes of least doses in 1-30 fractions to achieve maximal tumor control for early-stage lung ADC and SCC, e.g., 30, 44, 48, and 51 Gy for ADC, and 32, 48, 54, and 58 Gy for SCC in 1, 3, 4, and 5 fractions, respectively.

CONCLUSION

We presented the first determination of histology-dependent radiobiological parameters and model-independent histology-driven optimal SBRT and hypofractionated radiation therapy schemes for early-stage lung ADC and SCC. SCC requires substantially higher radiation doses to maximize tumor control than ADC, plausibly attributed to tumor genetic diversity and microenvironment. The determined optimal SBRT schemes agree well with clinical practice for early-stage lung ADC. These proposed optimal fractionation schemes provide first insights for histology-based personalized radiotherapy of two predominant early-stage NSCLC subtypes ADC and SCC, which require further validation with large-scale histologic TCP data.

Early radiologic and metabolic tumour response assessment during combined chemo-radiotherapy for locally advanced NSCLC

Background

The role of early treatment response for patients with locally advanced non-small cell lung cancer (LA-NSCLC) treated with concurrent chemo-radiotherapy (cCRT) is unclear. The study aims to investigate the predictive value of response to induction chemotherapy (iCX) and the correlation with pattern of failure (PoF).

Materials and methods

Patients with LA-NSCLC treated with cCRT were included for analyses (n = 276). Target delineations were registered from radiotherapy planning PET/CT to diagnostic PET/CT, in between which patients received iCX. Volume, sphericity, and SUVpeak were extracted from each scan. First site of failure was categorised as loco-regional (LR), distant (DM), or simultaneous LR+M (LR+M). Fine and Gray models for PoF were performed: a baseline model (including performance status (PS), stage, and histology), an image model for squamous cell carcinoma (SCC), and an image model for non-SCC. Parameters included PS, volume (VOL) of tumour, VOL of lymph nodes, ΔVOL, sphericity, SUVpeak, ΔSUVpeak, and oligometastatic disease.

Results

Median follow-up was 7.6 years. SCC had higher sub-distribution hazard ratio (sHR) for LRF (sHR = 2.771 [1.577:4.87], p < 0.01) and decreased sHR for DM (sHR = 0.247 [0.125:0.485], p  <  0.01). For both image models, high diagnostic SUVpeak increased risk of LRF (sHR = 1.059 [1.05:1.106], p < 0.01 for SCC, sHR = 1.12 [1.03:1.21], p < 0.01 for non-SCC). Patients with SCC and less decrease in VOL had higher sHR for DM (sHR = 1.025[1.001:1.048] pr. % increase, p = 0.038).

Conclusion

Poor response in disease volume was correlated with higher sHR of DM for SCC, no other clear correlation of response and PoF was observed. Histology significantly correlated with PoF with SCC prone to LRF and non-SCC prone to DM as first site of failure. High SUVpeak at diagnosis increased the risk of LRF for both histologies.

Survival difference between patients with single versus multiple metastatic lymph nodes and the role of histology in pathological stage II-N1 non-small cell lung cancer

BACKGROUND

Previous studies investigating whether metastatic lymph node count is a relevant prognostic factor in pathological N1 non-small cell lung cancer (NSCLC), showed conflicting results. Hypothesizing that outcome may also be related to histological features, we determined the prognostic impact of single versus multiple metastatic lymph nodes in different histological subtypes for patients with stage II-N1 NSCLC.

METHODS

We performed a retrospective cohort study using data from the Netherlands Cancer Registry, including patients treated with a surgical resection for stage II-N1 NSCLC (TNM 7th edition) in 2010-2016. Overall survival (OS) was assessed for patients with single (pN1a) and multiple (pN1b) metastatic nodes. Using multivariable analysis, we compared OS between pN1a and pN1b in different histological subtypes.

RESULTS

After complete resection of histologically proven stage II-N1 NSCLC, 1309 patients were analyzed, comprising 871 patients with pN1a and 438 with pN1b. The median number of pathologically examined nodes (N1 + N2) was 9 (interquartile range 6-13). Five-year OS was 53% for pN1a versus 51% for pN1b. In multivariable analysis, OS was significantly different between pN1a and pN1b (HR 1.19, 95% CI 1.01-1.40). When stratifying for histology, the prognostic impact of pN1a/b was only observed in adenocarcinoma patients (HR 1.44, 95% CI 1.15-1.81).

CONCLUSION

Among patients with stage II-N1 adenocarcinoma, the presence of multiple metastatic nodes had a significant impact on survival, which was not observed for other histological subtypes. If further refinement as to lymph node count will be considered for incorporation into a new staging system, evaluation of the role of histology is recommended.

Diagnostic value of FDG PET-CT in differentiating lung adenocarcinoma from squamous cell carcinoma

BACKGROUND

Lung cancer is the leading cause of cancer-related deaths worldwide. The combination of fluorine-18 fluorodeoxyglucose positron emission tomography (18F-FDG PET) and computed tomography (CT) has a major impact on the diagnosis, staging, treatment planning and follow-up of lung cancer patients. The maximum standardized uptake value (SUVmax) is an easily performed and most widely used semi-quantitative index for the analysis of FDG PET images and estimation of metabolic activity. This study aimed to investigate the role of PET/CT in differentiating adenocarcinoma (ADC), the most common lung cancer, from squamous cell carcinoma (SCC) by comparing FDG uptake measured as SUVmax.

RESULTS

Between 2019 and 2022, 76 patients diagnosed with non-small cell lung cancer (NSCLC) at the Department of Pathology, Atatürk University Faculty of Medicine, with histopathologic evidence of adenocarcinoma or squamous cell carcinoma, underwent retrospective analysis using PET/CT scanning to measure PET parameters of the lesions and compare them with histopathology. Among 76 NSCLC patients included in the study, 43 (57%) were histopathologically diagnosed as ADC and 33 (43%) as SCC. SUVmax, SUVmean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) values of lesions in patients with SCC were statistically significantly higher than those in patients with ADC (p values 0.007, 0.009, 0.003 and 0.04, respectively).

CONCLUSIONS

Lung SCC has higher metabolic uptake values than ADC, and PET/CT can be used to differentiate them.

Associations between detectable circulating tumor DNA and tumor glucose uptake measured by 18F-FDG PET/CT in early-stage non-small cell lung cancer

BACKGROUND

The low level of circulating tumor DNA (ctDNA) in the blood is a well-known challenge for the application of liquid biopsies in early-stage non-small cell lung cancer (NSCLC) management. Studies of metastatic NSCLC indicate that ctDNA levels are associated with tumor metabolic activity as measured by ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET/CT). This study investigated this association in NSCLC patients considered for potentially curative treatment and explored whether the two methods provide independent prognostic information.

METHOD

Patients with stage I-III NSCLC who had routinely undergone an ¹⁸F-FDG PET/CT scan and exploratory ctDNA analyses were included. Tumor glucose uptake was measured by maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) from the ¹⁸F-FDG PET/CT scans. ctDNA detectability and quantity, using variant allele frequency, were estimated by tumor-informed ctDNA analyses.

RESULTS

In total, 63 patients (median age 70 years, 60% women, and 90% adenocarcinoma) were included. The tumor glucose uptake (SUVmax, MTV, and TLG) was significantly higher in patients with detectable ctDNA (n = 19, p < 0.001). The ctDNA quantity correlated with MTV (Spearman's ρ = 0.53, p = 0.021) and TLG (Spearman's ρ = 0.56, p = 0.013) but not with SUVmax (Spearman's ρ = 0.034, p = 0.15). ctDNA detection was associated with shorter OS independent of MTV (HR: 2.70, 95% CI: 1.07-6.82, p = 0.035) and TLG (HR: 2.63, 95% CI: 1.06-6.51, p = 0.036). Patients with high tumor glucose uptake and detectable ctDNA had shorter overall survival and progression-free survival than those without detectable ctDNA, though these associations were not statistically significant (p > 0.05).

CONCLUSION

There was a positive correlation between plasma ctDNA quantity and MTV and TLG in early-stage NSCLC patients. Despite the correlation, the results indicated that ctDNA detection was a negative prognostic factor independent of MTV and TLG.

[18F]FDG-PET-Based Personalized Radiotherapy Dose Prescription

PET imaging with 2'-deoxy-2'-[18F]fluoro-D-glucose ([18F]FDG) has become one of the pillars in the management of malignant diseases. It has proven value in diagnostic workup, treatment policy, follow-up, and as prognosticator for outcome. [18F]FDG is widely available and standards have been developed for PET acquisition protocols and quantitative analyses. More recently, [18F]FDG-PET is also starting to be appreciated as a decision aid for treatment personalization. This review focuses on the potential of [18F]FDG-PET for individualized radiotherapy dose prescription. This includes dose painting, gradient dose prescription, and [18F]FDG-PET guided response-adapted dose prescription. The current status, progress, and future expectations of these developments for various tumor types are discussed.

The Effect of GLUT1 and HIF-1α Expressions on Glucose Uptake and Patient Survival in Non-Small-Cell Lung Carcinoma

Lung cancer is the second-most-common cancer while being the leading cause of cancer deaths worldwide. It has been found that glucose transporter 1 (GLUT1) and hypoxia-inducible factor 1α (HIF-1α) are overexpressed in various malignancies and that they correlate with the maximum standard uptake values (SUVmax) on 18F-fluorodeoxyglucose-positron emission tomography/computed tomography (18F-FDG PET/CT) and poor prognosis. In this study, we aim to evaluate the relationship between the SUVmax, GLUT1, and HIF-1α expression with primary tumor size, histological type, lymph node metastases, and patient survival. Of the 48 patients with non-small-cell lung cancer, those with squamous cell carcinomas (SCCs) had significantly higher GLUT1 and HIF-1α immunohistochemical expressions in comparison to adenocarcinomas (ACs), while there was no statistically significant difference in FDG accumulation between them. No significant correlation was noted between either GLUT1 or HIF-1α protein expression and FDG uptake and overall survival. However, an analysis of tumor transcriptomics showed a significant difference in overall survival depending on mRNA expression; patients with SCC and high HIF-1α levels survived longer compared to those with low HIF-1α levels, while patients with AC and low GLUT1 levels had a higher average survival time than those with high GLUT1 levels. Further studies are needed to determine the prognostic value of the expression of these factors depending on the histologic type.

Hypoxia Changes Energy Metabolism and Growth Rate in Non-Small Cell Lung Cancer Cells

Hypoxia occurs in 80% of non-small cell lung carcinoma (NSCLC) cases, leading to treatment resistance. Hypoxia's effects on NSCLC energetics are not well-characterized. We evaluated changes in glucose uptake and lactate production in two NSCLC cell lines under hypoxia in conjunction with growth rate and cell cycle phase distribution. The cell lines A549 (p53 wt) and H358 (p53 null) were incubated under hypoxia (0.1% and 1% O₂) or normoxia (20% O₂). Glucose and lactate concentrations in supernatants were measured using luminescence assays. Growth kinetics were followed over seven days. Cell nuclei were stained with DAPI and nuclear DNA content was determined by flow cytometry to determine cell cycle phase. Gene expression under hypoxia was determined by RNA sequencing. Glucose uptake and lactate production under hypoxia were greater than under normoxia. They were also significantly greater in A549 compared to H358 cells. Faster energy metabolism in A549 cells was associated with a higher growth rate in comparison to H358 cells under both normoxia and hypoxia. In both cell lines, hypoxia significantly slowed down the growth rate compared to proliferation under normoxic conditions. Hypoxia led to redistribution of cells in the different cycle phases: cells in G1 increased and the G2 population decreased. Glucose uptake and lactate production increase under hypoxia in NSCLC cells indicated greater shunting of glucose into glycolysis rather than into oxidative phosphorylation compared to normoxia, making adenosine triphosphate (ATP) production less efficient. This may explain the redistribution of hypoxic cells in the G1 cell cycle phase and the time increase for cell doubling. Energy metabolism changes were more prominent in faster-growing A549 cells compared to slower-growing H358 cells, indicating possible roles for the p53 status and inherent growth rate of different cancer cells. In both cell lines, genes associated with cell motility, locomotion and migration were upregulated under chronic hypoxia, indicating a strong stimulus to escape hypoxic conditions.

GLUT1 and PKM2 may be useful prognostic predictors in patients with non‑small cell lung cancer following curative R0 resection

Lung cancer has a poor prognosis despite recent progresses being made regarding its treatment. In addition, there is a paucity of reliable and independent prognostic predictors for non-small cell lung cancer (NSCLC) following curative resection. Glycolysis is associated with the malignancy and proliferation of cancer cells. Glucose transporter 1 (GLUT1) promotes glucose uptake, whereas pyruvate kinase M2 (PKM2) promotes anaerobic glycolysis. The present study aimed to evaluate the relationship between the expression of GLUT1 and PKM2 and the clinicopathological features of patients with NSCLC, and to identify a reliable prognostic factor for NSCLC following curative resection. Patients with NSCLC who underwent curative surgery were retrospectively enrolled to the present study. GLUT1 and PKM2 expression was assessed using immunohistochemistry. Subsequently, the association between the clinicopathological features of patients with NSCLC and the expression of GLUT1 and PKM2 was assessed. Of the 445 patients with NSCLC included in the present study, 65 (15%) were positive for both GLUT1 and PKM2 expression (G+/P+ group). GLUT1 and PKM2 positivity was significantly associated with sex, absence of adenocarcinoma, lymphatic invasion and pleural invasion. Furthermore, patients with NSCLC in the G+/P+ group presented significantly poorer survival rates than those expressing other markers. G+/P+ expression was significantly associated with poor disease-free survival. In conclusion, the findings of the present study indicated that the combination of GLUT1 and PKM2 may be considered a reliable prognostic factor for patients with NSCLC following curative resection, especially in patients with stage I NSCLC.

Prognostic role of baseline 18F-FDG pet/CT in stage I and stage ii non-small cell lung cancer

OBJECTIVE

investigate the prognostic role of baseline ¹⁸F-FDG PET/CT in stage I-II NSCLC.

MATERIAL AND METHODS

296 patients were included. Clinicopathological features and PET/CT semiquantitative parameters [standardized uptake value (SUV) body weight max (SUVmax), SUV body weight mean (SUVmean), SUV lean body mass (SUVlbm), SUV body surface area (SUVbsa), metabolic tumor volume (MTV), total lesion glycolysis (TLG), ratio SUVmax/liver (S-L) and ratio SUVmax/blood-pool (S-BP) were extracted]. Anova and Kruskall-Wallis tests were used to assess the relationship between these parameters. Kaplan-Meier, univariate and multivariate analysis were performed to search independent prognostic factors for progression free (PFS), overall survival (OS) and disease specific survival (DSS).

RESULTS

Correlation between PET/CT semiquantitative parameters and histology, stage, size, grading and presence of nodal metastasis were reported. Mean PFS was 28.1 months, relapse/progression of disease occurred in 85 patients (28.7%). Mean OS was 33.3 months, death occurred in 43 patients (14.5%); specific death by NSCLC occurred in 26 subjects (8.8%). Kaplan-Meier analyses revealed most of semiquantitative parameters as predictive for PFS, OS and DSS. For DSS, this was confirmed when dividing between patients with surgery and surgery with other therapies. SUVmax, SUVmean, SUVlbm, SUVbsa and S-L revealed to be independent prognosticators for OS and DSS. S-BP was an independent prognosticator for DSS. SUVmax, SUVmean, SUVlbm, S-L and S-BP were confirmed as independent prognosticators for DSS in the group of patients treated with surgery and subsequent adjuvant therapy.

CONCLUSION

Baseline ¹⁸F-FDG PET/CT semiquantitative parameters are confirmed as prognostic tools for stage I-II NSCLC, in particular for DSS.

Preoperative PET-SUVmax and volume based PET parameters of the primary tumor fail to predict nodal upstaging in early-stage lung cancer

OBJECTIVES

Accurate nodal staging is of utmost importance in patients with lung cancer. FDG-PET/CT imaging is now part of the routine staging. Despite thorough preoperative staging nodal upstaging still occurs in early-stage lung cancer. However, the predictive value of preoperative PET metrics of the primary tumor on nodal upstaging remains to be unexplored. Our aim was to assess the association of these preoperative PET-parameters with nodal upstaging in histologically confirmed lung adenocarcinoma and squamous cell carcinoma.

METHODS

From January 2016 to November 2018, 500 patients with pT1-T2/cN0 lung cancer received an anatomical resection with curative intent. 171 patients with adenocarcinoma and squamous cell carcinoma and available PET-CTs were retrospectively included. We analyzed the the association of nodal upstaging with preoperative PET-SUVmax and metabolic PET metrics including total lesion glycolysis (TLG) and metabolic tumor volume (MTV) with different defined thresholds.

RESULTS

High values of preoperative PET-SUVmax of the primary tumor were associated with squamous cell carcinoma (p < 0.0001) and with larger tumors (p < 0.0001). Increased preoperative C-reactive protein levels (<1mg/dL) correlated significantly with high preoperative PET-SUVmax values (p < 0.0001). No significant relationship between PET-SUVmax and lactate dehydrogenase activity (p = 0.6818), white blood cell count (p = 0.7681), gender (p = 0.1115) or age (p = 0.9284) was observed. Nodal upstaging rate was 14.0 % with 8.8 % N1 and 5.3 % N2 upstaging. Tumor size (p = 0.0468) and number of removed lymph nodes (p = 0.0461) were significant predictors of nodal upstaging but no significant association was found with histology or PET parameters. Of note, increased MTV - regardless of the threshold - tended to associate with nodal upstaging.

CONCLUSION

Early-stage lung cancer patients with squamous histology and T2 tumors presented increased preoperative PET-SUVmax values. Nevertheless, beyond tumor size and number of removed lymph nodes neither SUVmax nor metabolic PET parameters MTV and TLG were significant predictors of nodal upstaging.

Pacritinib inhibits glucose consumption in squamous cell lung cancer cells by targeting FLT3

Squamous cell lung cancer maintains its growth through elevated glucose consumption, but selective glucose consumption inhibitors are lacking. Here, we discovered using a high-throughput screen new compounds that block glucose consumption in three squamous cell lung cancer cell lines and identified 79 compounds that block glucose consumption in one or more of these cell lines. Based on its ability to block glucose consumption in all three cell lines, pacritinib, an inhibitor of FMS Related Receptor Tyrosine Kinase 3 (FLT3) and Janus Kinase 2 (JAK2), was further studied. Pacritinib decreased glucose consumption in squamous cell lung cancer cells in cell culture and in vivo without affecting glucose consumption in healthy tissues. Pacritinib blocked hexokinase activity, and Hexokinase 1 and 2 mRNA and protein expression. Overexpression of Hexokinase 1 blocked the ability of pacritinib to inhibit glucose consumption in squamous cell lung cancer cells. Overexpression of FLT3 but not JAK2 significantly increased glucose consumption and blocked the ability of pacritinib to inhibit glucose consumption in squamous cell lung cancer cells. Additional FLT3 inhibitors blocked glucose consumption in squamous cell lung cancer cells. Our study identifies FLT3 inhibitors as a new class of inhibitors that can block glucose consumption in squamous cell lung cancer.

Metabolic classification of non-small cell lung cancer patient-derived xenografts by a digital pathology approach: A pilot study

Introduction

Genetically characterized patient-derived tumor xenografts (PDX) are a valuable resource to understand the biological complexity of cancer and to investigate new therapeutic approaches. Previous studies, however, lack information about metabolic features of PDXs, which may limit testing of metabolism targeting drugs.

Methods

In this pilot study, we investigated by immunohistochemistry (IHC) expression of five essential metabolism-associated markers in a set of lung adenocarcinoma PDX samples previously established and characterized. We exploited digital pathology to quantify expression of the markers and correlated results with tumor cell proliferation, angiogenesis and time of PDX growth in mice.

Results

Our results indicate that the majority of the analyzed PDX models rely on oxidative phosphorylation (OXPHOS) metabolism, either alone or in combination with glucose metabolism. Double IHC enabled us to describe spatial expression of the glycolysis-associated monocarboxylate transporter 4 (MCT4) marker and the OXPHOS-associated glutaminase (GLS) marker. GLS expression was associated with cell proliferation and with expression of liver-kinase B1 (LKB1), a tumor suppressor involved in the regulation of multiple metabolic pathways. Acetyl CoA carboxylase (ACC) was associated with the kinetics of PDX growth.

Conclusion

Albeit limited by the small number of samples and markers analyzed, metabolic classification of existing collections of PDX by this mini panel will be useful to inform pre-clinical testing of metabolism-targeting drugs.

A multi-classification model for non-small cell lung cancer subtypes based on independent subtask learning

PURPOSE

The non-small cell lung cancer (NSCLC) can be divided into adenocarcinoma (ADC), squamous cell carcinoma (SCC), large cell carcinoma (LCC), and not otherwise specified (NOS), which is crucial for clinical decision-making. However, current related researches are rare for the complex multi-classification of NSCLC, mainly due to the serious data imbalance, the difficulty to unify the feature space, and the complicated decision boundary among multiple subtypes. The machine learning method of traditional "one-vs-one" (OVO) is difficult to solve these problems and achieve good results.

METHODS

To this end, we propose a novel independent subtask learning (ISTL) method to better carry out the multi-classification task. Specifically, it includes four pertinent strategies: (1) independent data expansion; (2) independent feature selection (IFS); (3) independent model construction; and (4) a novel voting strategy: majority voting combined with Bayesian prior. We performed experiments using 1036 CT scans (ADC:SCC:LCC:NOS = 600:268:105:63) collected from eight international databases, and the data acquisition was highly complex and diverse.

RESULTS

The experimental results showed that the ISTL method obtained an accuracy of 0.812 on the independent test cohort, which significantly improved the performance of multi-classification compared with the traditional OVO-support vector machine (0.691) and OVO-random forest (0.710) models. After the IFS, six selected feature sets of six binary tasks are obviously different, indicating that the ISTL method has better interpretability to distinguish the multiple NSCLC subtypes. The results of a further auxiliary contrast experiment showed that four pertinent strategies were all effective.

CONCLUSION

Our work indicates that the ISTL method can effectively perform multi-classification of NSCLC subtypes with better interpretability for clinical computer-aided detection and has the potential to be applied in a wide range of multi-classification studies.

[18F]FDG Uptake and Expression of Immunohistochemical Markers Related to Glycolysis, Hypoxia, and Proliferation in Indeterminate Thyroid Nodules

PURPOSE

The current study explored the association between 2-[¹⁸F]fluoro-2-deoxy-D-glucose ([¹⁸F]FDG) uptake and the quantitative expression of immunohistochemical markers related to glucose metabolism, hypoxia, and cell proliferation in benign and malignant thyroid nodules of indeterminate cytology.

PROCEDURES

Using a case-control design, 24 patients were selected from participants of a randomized controlled multicenter trial (NCT02208544) in which [¹⁸F]FDG-PET/CT and thyroid surgery were performed for Bethesda III and IV nodules. Three equally sized groups of [¹⁸F]FDG-positive malignant, [¹⁸F]FDG-positive benign, and [¹⁸F]FDG-negative benign nodules were included. Immunohistochemical staining was performed for glucose transporters (GLUT) 1, 3, and 4; hexokinases (HK) 1 and 2; hypoxia-inducible factor-1 alpha (HIF1α; monocarboxylate transporter 4 (MCT4); carbonic anhydrase IX (CA-IX); vascular endothelial growth factor (VEGF); sodium-iodide symporter (NIS); and Ki-67. Marker expression was scored using an immunoreactive score. Unsupervised cluster analysis was performed. The immunoreactive score was correlated to the maximum and peak standardized uptake values (SUV_max, SUV_peak) and SUV_max ratio (SUV_max of nodule/background SUV_max of contralateral, normal thyroid) of the [¹⁸F]FDG-PET/CT using the Spearman's rank correlation coefficient and compared between the three groups using Kruskal-Wallis tests.

RESULTS

The expression of GLUT1, GLUT3, HK2, and MCT4 was strongly positively correlated with the SUV_max, SUV_peak, and SUV_max ratio. The expression of GLUT1 (p = 0.009), HK2 (p = 0.02), MCT4 (p = 0.01), and VEGF (p = 0.007) was statistically significantly different between [¹⁸F]FDG-positive benign nodules, [¹⁸F]FDG-positive thyroid carcinomas, and [¹⁸F]FDG-negative benign nodules. In both [¹⁸F]FDG-positive benign nodules and [¹⁸F]FDG-positive thyroid carcinomas, the expression of GLUT1, HK2, and MCT4 was increased as compared to [¹⁸F]FDG-negative benign nodules. VEGF expression was higher in [¹⁸F]FDG-positive thyroid carcinomas as compared to [¹⁸F]FDG-negative and [¹⁸F]FDG-positive benign nodules.

CONCLUSIONS

Our results suggest that [¹⁸F]FDG-positive benign thyroid nodules undergo changes in protein expression similar to those in thyroid carcinomas. To expand the understanding of the metabolic changes in benign and malignant thyroid nodules, further research is required, including correlation with underlying genetic alterations.

FDG PET and CT radiomics in diagnosis and prognosis of non-small-cell lung cancer

BACKGROUND

18F-FDG PET and CT radiomics has been the object of a wide research for over 20 years but its contribution to clinical practice remains not yet well established. We have investigated its impact versus that of only histo-clinical data, for the routine management of non-small-cell lung cancer (NSCLC).

METHODS

Our patients were retrospectively considered. They all had a FDG PET-CT and immuno-histo-chemistry (IHC) to assess PD-L1 expression at the beginning of the disease. A prognosis univariate and multivariate Cox survival analyses was performed for overall survival (OS) and progression free survival (PFS) prediction, including a training/testing procedure. Two sets of 47 PET and 47 CT radiomics features (RFs) were extracted. Difference between RFs according to PD-L1 expression, the histology status and the stage level were tested using suited non parametric statistical tests and the receiver operating characteristics (ROC) curve and the area under curve (AUC).

RESULTS

From 2017 to 2019, 212 NSCLC patients treated in our institution were included. The main conventional prognostic variables were stage and gender with a low added prognostic value in the models including PET and CT RFs. Neither PET nor CT RFs were significant to separate the different levels of PD-L1 expression. Several RFs differ between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) tumours and a large number of PET and CT RFs are significantly linked to patient stage.

CONCLUSIONS

In our population, PET and CT RFs show their intrinsic power to predict survival but do not significantly improve OS and PFS prediction in the different multivariate models, in comparison to conventional data. It would seem necessary to carry out one's own survival analysis before determining a radiomics signature.

Monocarboxylate Transporter 4 in Cancer-Associated Fibroblasts Is a Driver of Aggressiveness in Aerodigestive Tract Cancers

The most common cancers of the aerodigestive tract (ADT) are non-small cell lung cancer (NSCLC) and head and neck squamous cell carcinoma (HNSCC). The tumor stroma plays an important role in ADT cancer development and progression, and contributes to the metabolic heterogeneity of tumors. Cancer-associated fibroblasts (CAFs) are the most abundant cell type in the tumor stroma of ADT cancers and exert pro-tumorigenic functions. Metabolically, glycolytic CAFs support the energy needs of oxidative (OXPHOS) carcinoma cells. Upregulation of the monocarboxylate transporter 4 (MCT4) and downregulation of isocitrate dehydrogenase 3α (IDH3α) are markers of glycolysis in CAFs, and upregulation of the monocarboxylate transporter 1 (MCT1) and the translocase of the outer mitochondrial membrane 20 (TOMM20) are markers of OXPHOS in carcinoma cells. It is unknown if glycolytic metabolism in CAFs is a driver of ADT cancer aggressiveness. In this study, co-cultures in vitro and co-injections in mice of ADT carcinoma cells with fibroblasts were used as experimental models to study the effects of fibroblasts on metabolic compartmentalization, oxidative stress, carcinoma cell proliferation and apoptosis, and overall tumor growth. Glycolytic metabolism in fibroblasts was modulated using the HIF-1α inhibitor BAY 87-2243, the antioxidant N-acetyl cysteine, and genetic depletion of MCT4. We found that ADT human tumors express markers of metabolic compartmentalization and that co-culture models of ADT cancers recapitulate human metabolic compartmentalization, have high levels of oxidative stress, and promote carcinoma cell proliferation and survival. In these models, BAY 87-2243 rescues IDH3α expression and NAC reduces MCT4 expression in fibroblasts, and these treatments decrease ADT carcinoma cell proliferation and increase cell death. Genetic depletion of fibroblast MCT4 decreases proliferation and survival of ADT carcinoma cells in co-culture. Moreover, co-injection of ADT carcinoma cells with fibroblasts lacking MCT4 reduces tumor growth and decreases the expression of markers of metabolic compartmentalization in tumors. In conclusion, metabolic compartmentalization with high expression of MCT4 in CAFs drives aggressiveness in ADT cancers.

A Nomogram Combined Radiomics and Clinical Features as Imaging Biomarkers for Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma

Objectives

To develop and validate a nomogram model based on radiomics features for preoperative prediction of visceral pleural invasion (VPI) in patients with lung adenocarcinoma.

Methods

A total of 659 patients with surgically pathologically confirmed lung adenocarcinoma underwent CT examination. All cases were divided into a training cohort (n = 466) and a validation cohort (n = 193). CT features were analyzed by two chest radiologists. CT radiomics features were extracted from CT images. LASSO regression analysis was applied to determine the most useful radiomics features and construct radiomics score (radscore). A nomogram model was developed by combining the optimal clinical and CT features and the radscore. The model performance was evaluated using ROC analysis, calibration curve and decision curve analysis (DCA).

Results

A total of 1316 radiomics features were extracted. A radiomics signature model with a selection of the six optimal features was developed to identify patients with or without VPI. There was a significant difference in the radscore between the two groups of patients. Five clinical features were retained and contributed as clinical feature models. The nomogram combining clinical features and radiomics features showed improved accuracy, specificity, positive predictive value, and AUC for predicting VPI, compared to the radiomics model alone (specificity: training cohort: 0.89, validation cohort: 0.88, accuracy: training cohort: 0.84, validation cohort: 0.83, AUC: training cohort: 0.89, validation cohort: 0.89). The calibration curve and decision curve analyses suggested that the nomogram with clinical features is beyond the traditional clinical and radiomics features.

Conclusion

A nomogram model combining radiomics and clinical features is effective in non-invasively prediction of VPI in patients with lung adenocarcinoma.

CT Combined with Multiparameter MRI in Differentiating Pathological Subtypes of Non-Small-Cell Lung Cancer before Surgery

Objective

To investigate the diagnostic value of computed tomography (CT) combined with multiparametric magnetic resonance imaging (mpMRI) for preoperative differentiation of non-small-cell lung cancer (NSCLC).

Methods

CT and MRI imaging data were collected from all patients with squamous lung cancer and adenocarcinoma admitted to our hospital from June 2019 to December 2020 (286 cases). ROC curves were plotted to evaluate the performance of CT, mpMRI, and CT combined with mpMRI to differentiate pathological subtypes of NSCLC. Univariate and multivariate regression were used to be independent predictors of pathological subtypes of NSCLC.

Results

ROC curves showed that CT combined with mpMRI had the largest area under the curve, followed by mpMRI and CT successively. Univariate regression analysis showed that gender, smoking, tumor size, morphology, marginal lobulation, marginal burr, bronchial truncation sign, and vascular convergence sign were factors influencing the pathological subtype of NSCLC. Multivariate regression analysis suggested the fact that gender, tumor size, morphology, marginal lobulation, bronchial truncation, and vascular convergence sign are likely the independent predictors of NSCLC pathological subtypes.

Conclusions

CT combined with mpMRI can effectively distinguish NSCLC pathological subtypes, which is worthy of clinical application.

Imaging the Rewired Metabolism in Lung Cancer in Relation to Immune Therapy

Metabolic reprogramming is recognized as one of the hallmarks of cancer. Alterations in the micro-environmental metabolic characteristics are recognized as important tools for cancer cells to interact with the resident and infiltrating T-cells within this tumor microenvironment. Cancer-induced metabolic changes in the micro-environment also affect treatment outcomes. In particular, immune therapy efficacy might be blunted because of somatic mutation-driven metabolic determinants of lung cancer such as acidity and oxygenation status. Based on these observations, new onco-immunological treatment strategies increasingly include drugs that interfere with metabolic pathways that consequently affect the composition of the lung cancer tumor microenvironment (TME). Positron emission tomography (PET) imaging has developed a wide array of tracers targeting metabolic pathways, originally intended to improve cancer detection and staging. Paralleling the developments in understanding metabolic reprogramming in cancer cells, as well as its effects on stromal, immune, and endothelial cells, a wave of studies with additional imaging tracers has been published. These tracers are yet underexploited in the perspective of immune therapy. In this review, we provide an overview of currently available PET tracers for clinical studies and discuss their potential roles in the development of effective immune therapeutic strategies, with a focus on lung cancer. We report on ongoing efforts that include PET/CT to understand the outcomes of interactions between cancer cells and T-cells in the lung cancer microenvironment, and we identify areas of research which are yet unchartered. Thereby, we aim to provide a starting point for molecular imaging driven studies to understand and exploit metabolic features of lung cancer to optimize immune therapy.

Pyruvate dehydrogenase E1α represents a reliable prognostic predictor for patients with non-small cell lung cancer resected via curative operation

Background

Lung cancer is associated with a high morbidity and mortality rate worldwide; however, no reliable and independent prognostic predictor for non-small cell lung cancer (NSCLC) after curative surgery is available. Glucose metabolism is correlated with cancer cell proliferation. Pyruvate dehydrogenase E1α (PDH-E1α) catalyzes the conversion of pyruvate to acetyl-CoA and promotes aerobic glucose metabolism. In this study, we examined the relationship between PDH-E1α expression and clinicopathological factors associated with NSCLC to identify a reliable prognostic predictor of NSCLC after curative surgery.

Methods

A total of 445 patients with NSCLC who underwent curative resection were enrolled in this study. PDH-E1α expression was evaluated via immunohistochemistry. We analyzed the correlation between PDH-E1α expression and clinicopathological features of the patients.

Results

In total, 248 (56%) of the 445 patients with NSCLC were PDH-E1α-positive, and 197 patients were PDH-E1α-negative. PDH-E1α positivity was significantly correlated with the presence of adenocarcinoma (P<0.001) compared to the PDH-E1α-negative group. Patients with NSCLC showing PDH-E1α-negative expression had a significantly poorer overall survival rate (P=0.007) than those showing PDH-E1α-positive expression, especially at stage II. Patients with PDH-E1α negative expression also showed a poorer disease-free survival rate (P=0.02). Multivariate analysis revealed that PDH-E1α negativity (P=0.037) and male sex (P<0.001) were significantly correlated with a poor overall survival.

Conclusions

PDH-E1α may represent a reliable prognostic predictor for NSCLC in patients that have recently undergone curative resection, especially at stage II.

Prognostic Radiological Tools for Clinical Stage IA Pure Solid Lung Cancer

In this study, we analyzed prognostic radiological tools and surgical outcomes for radiologically pure solid adenocarcinomas (AD) and squamous cell carcinoma (SQ) in clinical stage IA. We retrospectively investigated 130 patients who underwent surgical resections. We assessed the predictive risk factors for recurrence and pathological lymph node metastasis (LNM). There was no statistical difference in recurrence free survival (RFS) or cancer-specific survival (CSS) between AD and SQ groups (p = 0.642 and p = 0.403, respectively). In the whole cohort, tumor size on lung window and mediastinal settings, and tumor disappearance ratio using high-resolution computed tomography (HRCT) were not prognostic parameters (p = 0.127, 0.066, and 0.082, respectively). The maximal standardized uptake value (SUVmax) using positron emission tomography-CT was associated with recurrence (p = 0.016). According to the receiver operating characteristic curve, the cut-off value of SUVmax for recurrence was 4.6 (p = 0.016). The quantitative continuous variables using any radiological tools were not associated with LNM. However, tumor diameter on mediastinal setting ≥8 mm with SUVmax ≥2.4 could be a risk factor for LNM. Pure solid AD and SQ were equivalent for the RFS and CSS. SUVmax was useful to predict recurrence. The tumor diameter on a mediastinal setting and SUVmax were useful in predicting pathological LNM.

Prognostic significance of preoperative haemoglobin A1c level in patients with lung adenocarcinoma

OBJECTIVES

We investigated the influence of the preoperative haemoglobin A1c (HbA1c) value on the prognosis and pathology of patients with lung adenocarcinoma who underwent surgery.

METHODS

We reviewed the medical records of 400 lung adenocarcinoma patients who underwent lobectomy with mediastinal lymph node dissection between 2009 and 2013 using a prospectively maintained database. We stratified 400 patients into 4 groups according to the preoperative HbA1c value as follows: HbA1c ≤ 5.9 (n = 296), 6.0 ≤ HbA1c ≤ 6.9 (n = 70), 7.0 ≤ HbA1c ≤ 7.9 (n = 21) and HbA1c ≥ 8.0 (n = 12). We compared the recurrence-free survival and overall survival (OS) among these 4 groups. Univariate and multivariate analyses were performed to identify the risk factors for recurrence.

RESULTS

The median follow-up period was 61.2 months. On comparing the recurrence-free survival and OS rates among these 4 groups, we found that these rates among patients in the HbA1c ≥ 8.0 group were significantly poorer compared with the other 3 groups (5-year recurrence-free survival: HbA1c ≤ 5.9, 70.4%; 6.0 ≤ HbA1c ≤ 6.9, 69.7%; 7.0 ≤ HbA1c ≤ 7.9, 70.7%; ≥8.0 HbA1c, 18.8%; P = 0.002; and 5-year OS: HbA1c ≤ 5.9, 88.7%; 6.0 ≤ HbA1c ≤ 6.9, 80.6%; 7.0 ≤ HbA1c ≤ 7.9, 90.2%; ≥8.0 HbA1c, 66.7%; P = 0.046). Patients in the HbA1c ≥ 8.0 group had significantly more tumours with vascular invasion (P = 0.041) and experienced distant metastasis significantly more often (P = 0.028) than those with other values. A multivariate analysis revealed that preoperative HbA1c ≥ 8.0 [hazard ratio (HR) 2.33; P = 0.026] and lymph node metastasis (HR 3.94; P < 0.001) were significant independent prognostic factors for recurrence.

CONCLUSIONS

Our results revealed that preoperative HbA1c ≥ 8.0 is associated to poor prognosis due to the occurrence of distant metastasis and we should carefully follow these patients after surgery.

CLINICAL REGISTRATION NUMBER

Hyogo Cancer Center, G-57.

Improving the Subtype Classification of Non-small Cell Lung Cancer by Elastic Deformation Based Machine Learning

Non-invasive image-based machine learning models have been used to classify subtypes of non-small cell lung cancer (NSCLC). However, the classification performance is limited by the dataset size, because insufficient data cannot fully represent the characteristics of the tumor lesions. In this work, a data augmentation method named elastic deformation is proposed to artificially enlarge the image dataset of NSCLC patients with two subtypes (squamous cell carcinoma and large cell carcinoma) of 3158 images. Elastic deformation effectively expanded the dataset by generating new images, in which tumor lesions go through elastic shape transformation. To evaluate the proposed method, two classification models were trained on the original and augmented dataset, respectively. Using augmented dataset for training significantly increased classification metrics including area under the curve (AUC) values of receiver operating characteristics (ROC) curves, accuracy, sensitivity, specificity, and f1-score, thus improved the NSCLC subtype classification performance. These results suggest that elastic deformation could be an effective data augmentation method for NSCLC tumor lesion images, and building classification models with the help of elastic deformation has the potential to serve for clinical lung cancer diagnosis and treatment design.

Cancer-associated fibroblasts in non-small cell lung cancer: Recent advances and future perspectives

Non-small cell lung cancer (NSCLC) constitutes the majority of lung cancer, which is the leading cause of cancer-related deaths in the world. Nearly 70% of NSCLC patients were diagnosed at advanced stage with only 15% of five-year survival rate. Cancer-associated fibroblasts (CAFs) are the major component of tumor microenvironment and account for almost 70% of the cells in tumor tissues. By the crosstalk with cancer cells, CAFs reprogrammed cancer cell metabolism, remodeled extracellular matrix (ECM) and created a supportive niche for cancer stem cells. CAFs lead collective invasion of tumor cells and shape tumor immune microenvironment, promoting tumor metastasis and immune escape. In this review, we have summarized the progress of studies regarding CAFs influences on NSCLC in recent five years from the aspects of cell growth, metabolism, therapy resistance, invasion and metastasis and immune suppression. We have discussed the involved mechanisms and implications for the development of anti-NSCLC therapies. The current strategies of CAFs targeting and elimination have also been generalized. Only better understanding of the molecular biology of CAFs may contribute to the development of novel anti-NSCLC strategies.

Radiomics-Based Features for Prediction of Histological Subtypes in Central Lung Cancer

Objectives

To evaluate the effectiveness of radiomic features on classifying histological subtypes of central lung cancer in contrast-enhanced CT (CECT) images.

Materials and Methods

A total of 200 patients with radiologically defined central lung cancer were recruited. All patients underwent dual-phase chest CECT, and the histological subtypes (adenocarcinoma (ADC), squamous cell carcinoma (SCC), small cell lung cancer (SCLC)) were confirmed by histopathological samples. 107 features were used in five machine learning classifiers to perform the predictive analysis among three subtypes. Models were trained and validated in two conditions: using radiomic features alone, and combining clinical features with radiomic features. The performance of the classification models was evaluated by the area under the receiver operating characteristic curve (AUC).

Results

The highest AUCs in classifying ADC vs. SCC, ADC vs. SCLC, and SCC vs. SCLC were 0.879, 0.836, 0.783, respectively by using only radiomic features in a feedforward neural network.

Conclusion

Our study indicates that radiomic features based on the CECT images might be a promising tool for noninvasive prediction of histological subtypes in central lung cancer and the neural network classifier might be well-suited to this task.

Letter to the editor: Hypoxia kinetics and histology in combined radiotherapy and oxidative phosphorylation inhibition effects on antitumor immunity

In response to the recent paper by Chen et al investigating the triple combination of oxidative phosphorylation inhibition, immunotherapy and radiotherapy, we would like to stress that after irradiation, a strong reduction in hypoxia (within 24 hours) can be followed by a strong increase (several days). This is especially the case with larger fraction sizes of radiation therapy, which are often applied in combination with immunotherapy, and is likely to be tumor dependent. All together this may strongly affect the synergistic effect of such a triple combination therapy.

Prognostic impact of maximum standardized uptake value on 18 F-FDG PET/CT imaging of the primary lung lesion on survival in advanced non-small cell lung cancer: A retrospective study

Background

Positron emission tomography/computed tomography (PET/CT) has been recognized for diagnosing and staging lung cancer, but the prognostic value of standardized uptake value (SUV) on ¹⁸F‐FDG PET/CT imaging in patients with advanced non‐small cell lung cancer (NSCLC) remains controversial.

Methods

We performed a retrospective analysis of patients with advanced NSCLC who had undergone ¹⁸F‐FDG PET/CT before systemic treatment between June 2012 and June 2016. The relationship between the maximum SUV (SUVmax) of the pulmonary lesion and lesion size was evaluated via Spearman's correlation analysis. We collected patients' clinical and pathological data. Univariate and multivariate analyses were performed to analyze the factors influencing survival.

Results

We included 157 patients with advanced NSCLC. Among these, 135 died, 13 survived, and nine were lost to follow‐up (median follow‐up period, 69 months). SUVmax was correlated with lesion size and was significantly greater for tumors ≥3 cm than for tumors <3 cm (10.2 ± 5.4 vs. 5.6 ± 3.3, t = −6.709, p = 0.000). Univariate analysis showed that survival was associated with gender, tumor size, epidermal growth factor receptor gene mutation or anaplastic lymphoma kinase rearrangement, SUVmax of the primary lung lesion, and treatment lines. Multivariate analysis showed a significant correlation between SUVmax of the primary lung lesion and survival. The mortality risk of patients with SUVmax ≤6 was 35% lower than that of patients with SUVmax >6 (HR = 0.651, 95% confidence interval, 0.436–0.972; Wald value, 4.400; p = 0.036).

Conclusions

The SUVmax of the primary lung lesion on PET/CT is significantly correlated with survival in treatment‐naive patients with advanced NSCLC.

Acquired deficiency of peroxisomal dicarboxylic acid catabolism is a metabolic vulnerability in hepatoblastoma

Metabolic reprogramming provides transformed cells with proliferative and/or survival advantages. Capitalizing on this therapeutically, however, has been only moderately successful because of the relatively small magnitude of these differences and because cancers may further adapt their metabolism to evade metabolic pathway inhibition. Mice lacking the peroxisomal bifunctional enzyme enoyl-CoA hydratase/3-hydroxyacyl CoA dehydrogenase (Ehhadh) and supplemented with the 12-carbon fatty acid lauric acid (C12) accumulate the toxic metabolite dodecanedioic acid (DDDA), which causes acute hepatocyte necrosis and liver failure. We noted that, in a murine model of pediatric hepatoblastoma (HB) and in primary human HBs, downregulation of Ehhadh occurs in association with the suppression of mitochondrial β- and endosomal/peroxisomal ω-fatty acid oxidation pathways. This suggested that HBs might be more susceptible than normal liver tissue to C12 dietary intervention. Indeed, HB-bearing mice provided with C12- and/or DDDA-supplemented diets survived significantly longer than those on standard diets. In addition, larger tumors developed massive necrosis following short-term DDDA administration. In some HBs, the eventual development of DDDA resistance was associated with 129 transcript differences, ∼90% of which were downregulated, and approximately two-thirds of which correlated with survival in numerous human cancers. These transcripts often encoded extracellular matrix components, suggesting that DDDA resistance arises from reduced Ehhadh uptake. Lower Ehhadh expression was also noted in murine hepatocellular carcinomas and in subsets of certain human cancers, supporting the likely generality of these results. Our results demonstrate the feasibility of C12 or DDDA dietary supplementation that is nontoxic, inexpensive, and likely compatible with more standard chemotherapies.

18F-FDG PET/CT Scans Can Identify Sub-Groups of NSCLC Patients with High Glucose Uptake in the Majority of Their Tumor Lesions

Background: Reprogrammed glucose metabolism is a hallmark of cancer making it an attractive therapeutic target, especially in cancers with high glucose uptake such as non-small cell lung cancer (NSCLC). Tools to select patients with high glucose uptake in the majority of tumor lesions are essential in the development of anti-cancer drugs targeting glucose metabolism. Type 2 diabetes mellitus (T2DM) patients may have tumors highly dependent on glucose uptake. Surprisingly, this has not been systematically studied. Therefore, we aimed to determine which patient and tumor characteristics, including concurrent T2DM, are related to high glucose uptake in the majority of tumor lesions in NSCLC patients as measured by 2-deoxy-2-[fluorine-18]fluoro-D-glucose (¹⁸F-FDG) positron emission tomography (PET)/computed tomography (CT) scans.

Methods: Routine primary diagnostic ¹⁸F-FDG PET/CT scans of consecutive NSCLC patients were included. Mean standardized uptake value (SUVmean) of ¹⁸F-FDG was determined for all evaluable tumor lesions and corrected for serum glucose levels according to the European Association of Nuclear Medicine Research Ltd guidelines. Patient characteristics potentially determining degree of tumor lesion glucose uptake in the majority of tumor lesions per patient were investigated.

Results: The cohort consisted of 102 patients, 28 with T2DM and 74 without T2DM. The median SUVmean per patient ranged from 0.8 to 35.2 (median 4.2). T2DM patients had higher median glucose uptake in individual tumor lesions and per patient compared to non-diabetic NSCLC patients (SUVmean 4.3 vs 2.8, P < 0.001 and SUVmean 5.4 vs 3.7, P = 0.009, respectively). However, in multivariable analysis, high tumor lesion glucose uptake was only independently determined by number of tumor lesions ≥1 mL per patient (odds ratio 0.8, 95% confidence interval 0.7-0.9).

Conclusions:¹⁸F-FDG PET/CT scans can identify sub-groups of NSCLC patients with high glucose uptake in the majority of their tumor lesions. T2DM patients had higher tumor lesion glucose uptake than non-diabetic patients. However, this was not independent of other factors such as the histological subtype and number of tumor lesions per patient.

Shining a light on metabolic vulnerabilities in non-small cell lung cancer

Metabolic reprogramming is a hallmark of cancer which contributes to essential processes required for cell survival, growth, and proliferation. Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and its genomic classification has given rise to the design of therapies targeting tumors harboring specific gene alterations that cause aberrant signaling. Lung tumors are characterized with having high glucose and lactate use, and high heterogeneity in their metabolic pathways. Here we review how NSCLC cells with distinct mutations reprogram their metabolic pathways and highlight the potential metabolic vulnerabilities that might lead to the development of novel therapeutic strategies.

Early Loss of Fat Mass During Chemoradiotherapy Predicts Overall Survival in Locally Advanced Squamous Cell Carcinoma of the Lung, but Not in Locally Advanced Squamous Cell Carcinoma of the Head and Neck

Background: Cancer cachexia is highly prevalent in advanced non-small cell lung cancer (NSCLC) and locally advanced head and neck squamous cell carcinoma (LAHNSCC), and compromises treatment tolerance and overall survival (OS). NSCLC and LAHNSCC patients share similar risk factors, and receive comparable anti-cancer treatment regimens. The aim of this study was to determine the predictive value of body composition assessed by bioelectrical impedance analysis (BIA) and handgrip strength (HGS) (baseline and early changes during therapy) on OS in NSCLC and LAHNSCC patients treated with platinum-based chemoradiotherapy (CRT) or cetuximab-based bioradiotherapy (BRT). To elucidate potential underlying determinants of early changes in body composition and HGS, specific (fat and fat free) mass loss patterns of squamous NSCLC (sNSCLC) were compared to human papilloma virus negative (HPV–) LAHNSCC patients treated with CRT.

Methods: Between 2013 and 2016, BIA and HGS were performed at baseline and after 3 weeks of CRT/BRT in LAHNSCC and NSCLC patients treated with curative intent.

Results: Two hundred thirty-three patients were included for baseline measurements. Fat free mass index (FFMI) and HGS<10th percentile of reference values at baseline were both prognostic for poor OS in NSCLC and LAHNSCC [HR 1.64 [95%CI 1.13–2.39], p = 0.01 and HR 2.30 [95%CI 1.33–3.97], p = 0.003, respectively], independent of Charlson Comorbidity Index, cancer site, and gross tumor volume. Early fat mass (FM) loss during CRT was predictive for poor OS in sNSCLC (n = 64) [HR 3.80 [95%CI 1.79–8.06] p ≤ 0.001] but not in HPV– LAHNSCC (n = 61). In patients with significant weight loss (>2%) in the first 3 weeks of CRT (sNSCLC n = 24, HPV– LAHNSCC n = 23), the FM change was −1.4 ± 14.5% and −8.7 ± 9.0% in sNSCLC and HPV– LAHNSCC patients, respectively (p < 0.05). Fat fee mass change was −5.6 ± 6.3% and −4.0 ± 4.3% for sNSCLC and HPV– LAHNSCC, respectively (p = 0.31).

Conclusion: FFMI and HGS<10th percentile at baseline are independent prognostic factors for poor OS in NSCLC and LAHNSCC patients treated with CRT/BRT. The specific composition of mass loss during first 3 weeks of CRT significantly differs between sNSCLC and HPV– LAHNSCC patients. Early FM loss was prognostic in sNSCLC only.

Randomized phase II study of platinum-based chemotherapy plus controlled diet with or without metformin in patients with advanced non-small cell lung cancer

OBJECTIVES

Accumulating evidence indicates anti-diabetic drug metformin has anti-cancer effect by controlling cancer metabolism. We evaluated whether addition of metformin to chemotherapy improved survival of lung cancer patients.

MATERIALS AND METHODS

This randomized phase II study enrolled 164 patients with chemo-native, EGFR-ALK wild-type, stage IIIB/IV non-small-cell lung cancer (NSCLC). Patients were randomized to receive chemotherapy either with metformin (1000 mg twice daily) or alone every 3 weeks for six cycles. The patients received gemcitabine (1000 mg/m²) on days 1 and 8 and carboplatin (5 area under the curve) on day 1. Exploratory studies included serum metabolic panels, positron-emission tomography (PET) imaging, and genetic mutation tests for metabolism-related genes.

RESULTS

Metformin group showed no significant difference in the risk of progression and death compared to control group (progression: hazard ratio [HR] = 1.01 [95% confidence interval (CI) = 0.72 - 1.42], P = 0.935; death: HR = 0.95 [95% CI = 0.67-1.34], P = 0.757). Squamous cell carcinoma (SqCC) had significantly higher fluorodeoxyglucose (FDG) uptake on baseline PET image than non-SqCC NSCLC (P = 0.004). In the SqCC with high FDG uptake, the addition of metformin significantly decreased the risk of progression and death (progression: HR = 0.31 [95% CI = 0.12-0.78], P = 0.013; death: HR = 0.42 [95% CI = 0.18-0.94], P = 0.035). The HDL-cholesterol level was significantly increased after the treatment in metformin group compared to control group (P = 0.011). The metformin group showed no survival benefit in the patients with hyperinsulinemia or patients whose insulin level was decreased after treatment.

CONCLUSIONS

Addition of metformin to chemotherapy provided no survival benefit in unselected NSCLC patients. However, it significantly improved the survival of the selected patients with SqCC showing high FDG uptake. It suggests metformin shows the synergistic anti-tumor effect in the tumor which are highly dependent on glucose metabolism.

The Clinical Significance of SIRT2 in Malignancies: A Tumor Suppressor or an Oncogene?

Sirtuin 2 (SIRT2) is a member of the sirtuin protein family. It is a Class III histone deacetylase (HDACs) and predominantly localized to the cytosol. SIRT2 deacetylates histones and a number of non-histone proteins and plays a pivotal role in various physiologic processes. Previously, SIRT2 has been considered indispensable during carcinogenesis; however, there is now a significant controversy regarding whether SIRT2 is an oncogene or a tumor suppressor. The purpose of this review is to summarize the physiological functions of SIRT2 and its mechanisms in cancer. We will focus on five malignancies (breast cancer, non-small cell lung cancer, hepatocellular carcinoma, colorectal cancer, and glioma) to describe the current status of SIRT2 research and discuss the clinical evaluation of SIRT2 expression and the use of SIRT2 inhibitors.

CA IX Stabilizes Intracellular pH to Maintain Metabolic Reprogramming and Proliferation in Hypoxia

Tumor hypoxia represents a severe microenvironmental stress that is frequently associated with acidosis. Cancer cells respond to these stresses with changes in gene expression that promote survival at least in part through pH regulation and metabolic reprogramming. Hypoxia-induced carbonic anhydrase IX (CA IX) plays a critical adaptive role in response to hypoxic and acidic environments by catalytically hydrating extracellular CO₂ to produce bicarbonate for buffering intracellular pH (pHi). We used proteome-wide profiling to study the cellular response to transient CA IX knockdown in hypoxia and found a decrease in the levels of key glycolytic enzymes and lactate dehydrogenase A (LDHA). Interestingly, the activity of LDH was also decreased as demonstrated by native in-gel activity assay. These changes led to a significant reduction in glycolytic flux and extracellular lactate levels in cancer cells in vitro, contributing to a decrease in proliferation. Interestingly, addition of the alternative LDH substrate alpha-ketobutyrate restored LDHA activity, extracellular acidification, pHi, and cellular proliferation. These results indicate that in the absence of CA IX, reduction of pHi disrupts LDHA activity and hinders the cellular capacity to regenerate NAD⁺ and secrete protons to the extracellular space. Hypoxia-induced CA IX therefore mediates adaptation to microenvironmental hypoxia and acidosis directly, by enzymatically converting extracellular CO₂ to bicarbonate, and indirectly, by maintaining glycolysis-permissive intracellular milieu.

Distribution and prognostic significance of gluconeogenesis and glycolysis in lung cancer

Inhibition of glycolysis has been considered as a therapeutic approach in aggressive cancers including lung cancer. Abbreviated gluconeogenesis, mediated by phosphoenolpyruvate carboxykinase (PEPCK), was recently discovered to partially circumvent the need for glycolysis in lung cancer cells. However, the interplay of glycolysis and gluconeogenesis in lung cancer is still poorly understood. Here, we analyzed the expression of GLUT1, the prime glucose transporter, and of PCK1 and PCK2, the cytoplasmic and mitochondrial isoforms of PEPCK, in 450 samples of non‐small cell lung cancer (NSCLC) and in 54 NSCLC metastases using tissue microarrays and whole tumor sections. Spatial distribution was assessed by automated image analysis. Additionally, glycolytic and gluconeogenic gene expression was inferred from The Cancer Genome Atlas (TCGA) datasets. We found that PCK2 was preferentially expressed in the lung adenocarcinoma subtype, while GLUT1 expression was higher in squamous cell carcinoma. GLUT1 and PCK2 were inversely correlated, GLUT1 showing elevated expression in larger tumors while PCK2 was highest in smaller tumors. However, a mixed phenotype showing the presence of both, glycolytic and gluconeogenic cancer cells was frequent. In lung adenocarcinoma, PCK2 expression was associated with significantly improved overall survival, while the opposite was found for GLUT1. The metabolic tumor microenvironment and the 3‐dimensional context play an important role in modulating both pathways, since PCK2 expression preferentially occurred at the tumor margin and hypoxia regulated both, glycolysis and gluconeogenesis, in NSCLC cells in vitro, albeit in opposite directions. PCK1/2 expression was enhanced in metastases compared to primary tumors, possibly related to the different environment. The results of this study show that glycolysis and gluconeogenesis are activated in NSCLC in a tumor size and oxygenation modulated manner and differentially correlate with outcome. The frequent co‐activation of gluconeogenesis and glycolysis in NSCLC should be considered in potential future therapeutic strategies targeting cancer cell metabolism.

Heterogeneity of Glucose Transport in Lung Cancer

Increased glucose uptake is a known hallmark of cancer. Cancer cells need glucose for energy production via glycolysis and the tricarboxylic acid cycle, and also to fuel the pentose phosphate pathway, the serine biosynthetic pathway, lipogenesis, and the hexosamine pathway. For this reason, glucose transport inhibition is an emerging new treatment for different malignancies, including lung cancer. However, studies both in animal models and in humans have shown high levels of heterogeneity in the utilization of glucose and other metabolites in cancer, unveiling a complexity that is difficult to target therapeutically. Here, we present an overview of different levels of heterogeneity in glucose uptake and utilization in lung cancer, with diagnostic and therapeutic implications.

2-[18F]FDG PET/CT radiomics in lung cancer: An overview of the technical aspect and its emerging role in management of the disease

Lung cancer is the most common cancer, worldwide, and a major health issue with a remarkable mortality rate. 2-[¹⁸F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[¹⁸F]FDG PET/CT) plays an indispensable role in the management of lung cancer patients. Long-established quantitative parameters such as size, density, and metabolic activity have been and are being employed in the current practice to enhance interpretation and improve diagnostic and prognostic value. The introduction of radiomics analysis revolutionized the quantitative evaluation of medical imaging, revealing data within images beyond visual interpretation. The "big data" are extracted from high-quality images and are converted into information that correlates to relevant genetic, pathologic, clinical, or prognostic features. Technically advanced, diverse methods have been implemented in different studies. The standardization of image acquisition, segmentation and features analysis is still a debated issue. Importantly, a body of features has been extracted and employed for diagnosis, staging, risk stratification, prognostication, and therapeutic response. 2-[¹⁸F]FDG PET/CT-derived features show promising value in non-invasively diagnosing the malignant nature of pulmonary nodules, differentiating lung cancer subtypes, and predicting response to different therapies as well as survival. In this review article, we aimed to provide an overview of the technical aspects used in radiomics analysis in non-small cell lung cancer (NSCLC) and elucidate the role of 2-[¹⁸F]FDG PET/CT-derived radiomics in the diagnosis, prognostication, and therapeutic response.

The relationship between FDG PET/CT-defined metabolic parameters and the histopathological subtype of oesophageal carcinomas

Purpose

18F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET) combined with computed tomography (CT) scan is accepted as a standard tool in the staging of oesophageal cancer (OC). Histological subtype of tumour is known to be a major determinant of prognosis and metabolic behaviour. In this study, we aimed to evaluate the effect of histological subtypes of OC on standard uptake value (SUV_max), metabolic tumour volume (MTV), and total lesion glycolysis (TLG) obtained by PET/CT, and also to compare this effect with prognosis.

Material and methods

Images and clinical course data of 57 patients who were diagnosed with EC and treated in our hospital between 2009 and 2016 were evaluated in a retrospective manner. PET/CT images were re-analysed in terms of metabolic parameters, and observations were compared with histological subtypes.

Results

No significant difference was observed between histological subtypes with SUV_max, overall survival (OS), or progression-free survival (PFS). Thus, MTV was observed to be related with histological subtype; MTV values of adenocancer patients were significantly higher than those of squamous cell cancer patients.

Conclusions

Metabolic tumour volume was related with histological subtype of OC, but clinical staging, TLG, and SUV_max values were not related with histological subtype, which may suggest the use of MTV as a routine parameter for OC and inclusion of MTV observations in prognostic scoring.

CT radiomics analysis of lung cancers: Differentiation of squamous cell carcinoma from adenocarcinoma, a correlative study with FDG uptake

BACKGROUND AND PURPOSE

Pulmonary squamous cell carcinoma (SCC) was reported to have significantly higher histogram_kurtosis obtained by unenhanced computed tomography (CT) and a greater maximum standardized uptake value (SUVmax) determined by ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG-PET/CT) than pulmonary adenocarcinoma (AD). The first study aim was to investigate whether CT radiomics features could differentiate SCC from AD. The second aim was to investigate correlations between CT radiomics features and SUVmax.

MATERIALS AND METHODS

Forty solid lung tumors < 3 cm in diameter pathologically proven to be SCC (n = 18) or AD (n = 22) were included. The SUVmax was determined by ¹⁸F-FDG-PET/CT and 42 CT radiomics features were obtained from unenhanced CT. A Mann-Whitney U test was used to compare the SUVmax and each CT radiomics feature to differentiate SCC from AD. The area under the curve (AUC) was calculated from receiver operating characteristic (ROC) analysis. A binary logistic regression analysis was performed for a combination of SUVmax with each CT radiomics feature. A Spearman rank correlation analysis was performed to determine correlations between SUVmax and CT radiomics features.

RESULTS

Twenty-six of 42 CT radiomics features were significantly different between groups. The best AUC of the CT radiomics features was 0.81 for both the GLRLM_SRHGE and GLZLM_HGZE. The AUC value improved when the shape_sphericity feature was combined with SUVmax (AUC = 0.92). The CT radiomics features exhibiting strongest correlations with the SUVmax were different in both AD and SCC groups.

CONCLUSION

CT radiomics features correlated with tumor structural characteristics of SCC and AD, and were closely related to metabolic information from FDG-PET/CT.

Polymorphisms in Glycolysis-Related Genes Are Associated with Clinical Outcomes of Paclitaxel-Cisplatin Chemotherapy in Non-Small Cell Lung Cancer

OBJECTIVE

This study was conducted to investigate whether polymorphisms in glycolysis-related genes are associated with clinical outcomes of patients with advanced-stage non-small cell lung cancer (NSCLC) undergoing chemotherapy.

METHODS

A total of 377 patients with NSCLC were enrolled. Sixty-five single-nucleotide polymorphisms in 26 genes involved in the glycolytic pathway were evaluated. The associations of the variants with the chemotherapy response and overall survival (OS) were analyzed.

RESULTS

Among the 65 variants investigated, PFKL rs2073436C>G and GPI rs7248411C>G significantly correlated with clinical outcomes after chemotherapy in multivariate analyses. PFKL rs2073436C>G was significantly associated with both a worse response to chemotherapy (adjusted odds ratio [aOR] = 0.64, 95% CI = 0.45-0.90, p = 0.01) and a worse OS (adjusted hazard ratio [aHR] = 1.35, 95% CI = 1.14-1.61, p = 0.001). GPI rs7248411C>G was significantly associated with both a better chemotherapy response (aOR = 1.58, 95% CI = 1.07-2.23, p = 0.02) and a better OS (aHR = 0.80, 95% CI = 0.66-0.98, p = 0.03). When stratified by tumor histology, PFKL rs2073436C>G was significantly associated with OS only in squamous cell carcinoma, whereas GPI rs7248411C>G exhibited a significant association with the chemotherapy response and OS only in adenocarcinoma.

CONCLUSION

This result suggests that the PFKL rs2073436C>G and GPI rs7248411C>G are useful for predicting the clinical outcome of first-line paclitaxel-cisplatin chemotherapy in NSCLC.

FDG-PET/CT imaging findings of hepatic tumors and tumor-like lesions based on molecular background

The usefulness of whole-body 18-fluoro-2-deoxyglucose (FDG)-fluorodeoxyglucose positron emission (PET)/computed tomography (CT) is established for assessment of disease staging, detection of early disease recurrence, therapeutic evaluation, and predicting prognosis in various malignancies; and for evaluating the spread of inflammation. However, the role of FDG-PET/CT for the liver is limited because CT and magnetic resonance imaging (MRI) can provide an accurate diagnosis of most tumors. In addition, in other potentially useful roles there are several pitfalls in the interpretation of FDG uptake in PET/CT imaging. Accurate evaluation demands knowledge of the FDG uptake of each lesion, including potential negative and positive uptakes, and requires an understanding of the underlying background of the molecular mechanisms. The degree of FDG uptake is dependent on cellular metabolic rate and the expression of glucose transporter, hexokinase, and glucose-6-phosphatase, which in turn are closely affected by biological characteristics such as pathological category (e.g., adenocarcinoma, squamous cell carcinoma, small cell cancer, transitional cell cancer, neuroendocrine tumor, sarcoma, lymphoma), tumor differentiation, histological behavior (e.g., solid, cystic, mucinous), and intratumoral alterations (e.g., necrosis, degeneration, hemorrhage). Correlation with the CT and MRI findings, which also precisely depict the pathological findings, is important to avoid misdiagnosis.

A Machine-Learning Approach Using PET-Based Radiomics to Predict the Histological Subtypes of Lung Cancer

PURPOSE

We sought to distinguish lung adenocarcinoma (ADC) from squamous cell carcinoma using a machine-learning algorithm with PET-based radiomic features.

METHODS

A total of 396 patients with 210 ADCs and 186 squamous cell carcinomas who underwent FDG PET/CT prior to treatment were retrospectively analyzed. Four clinical features (age, sex, tumor size, and smoking status) and 40 radiomic features were investigated in terms of lung ADC subtype prediction. Radiomic features were extracted from the PET images of segmented tumors using the LIFEx package. The clinical and radiomic features were ranked, and a subset of useful features was selected based on Gini coefficient scores in terms of associations with histological class. The areas under the receiver operating characteristic curves (AUCs) of classifications afforded by several machine-learning algorithms (random forest, neural network, naive Bayes, logistic regression, and a support vector machine) were compared and validated via random sampling.

RESULTS

We developed and validated a PET-based radiomic model predicting the histological subtypes of lung cancer. Sex, SUVmax, gray-level zone length nonuniformity, gray-level nonuniformity for zone, and total lesion glycolysis were the 5 best predictors of lung ADC. The logistic regression model outperformed all other classifiers (AUC = 0.859, accuracy = 0.769, F1 score = 0.774, precision = 0.804, recall = 0.746) followed by the neural network model (AUC = 0.854, accuracy = 0.772, F1 score = 0.777, precision = 0.807, recall = 0.750).

CONCLUSIONS

A machine-learning approach successfully identified the histological subtypes of lung cancer. A PET-based radiomic features may help clinicians improve the histopathologic diagnosis in a noninvasive manner.

Prognostic significance of semi-quantitative FDG-PET parameters in stage I non-small cell lung cancer treated with carbon-ion radiotherapy

Purpose

Prognostic significance of volumetric ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography/computer tomography (PET/CT) parameters in carbon-ion radiotherapy (C-ion RT) treated stage I non-small cell lung cancer, and need of histology-wise separate cut-off values for risk stratification were assessed.

Methods

Thirty-nine patients (29 men and 10 women, 71.9 ± 8.3 years) who underwent FDG PET/CT examinations before C-ion RT were retrospectively evaluated. FDG-PET parameters: standardized uptake values (SUVmax, SUVpeak, and SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG), and clinicopathological variables were assessed for prognosis using Cox proportional hazards regression analysis. Mann-Whitney test compared medians of significant parameters between adenocarcinoma (AC) and squamous cell carcinoma (SCC), and Kaplan-Meier curves were plotted for median-based low- and high-risk groups.

Results

Median follow-up period was 44.8 months. 1/2/3-year overall survival (OS), progression-free survival (PFS) and local control (LC) rates were 94.9/84.3/70.8, 82.1/69.2/58.4 and 97.3/85.7/82.3%. Multivariate analysis revealed age (hazard ratio, HR: 1.09; 95% confidence interval, CI: 1.0–1.19, p < 0.05) and MTV (HR 4.83, 95% CI 1.21–19.27, p < 0.03) predicted OS, and only MTV predicted PFS (HR 5.3, CI 1.32–21.35, p < 0.02) independently. Compared with AC, SCC had higher MTV (median, 6.625cm³ vs 0.2 cm³, p < 0.01). Single MTV cut-off based on overall cohort was insignificant in SCC for PFS (p > 0.02); separate cut-offs of MTV, 0.2 cm³ for AC (p < 0.03) and 6.625 cm³ for SCC (p < 0.05) were relevant.

Conclusion

Among all FDG PET/CT parameters, only MTV beared prognostic ability for stage I NSCLC treated with C-ion RT, and its histological variation may need consideration for risk-adapted therapeutic management.

Radioimmunoimaging of 125I-labeled anti-CD93 monoclonal antibodies in a xenograft model of non-small cell lung cancer

Lung cancer, especially non-small cell lung cancer (NSCLC), is the most common malignant tumor associated with poor prognosis. Angiogenesis plays a vital role in NSCLC, and could be used in tumor staging and therapy evaluation. CD93 (C1q receptor) is reportedly a key regulator of tumor angiogenesis. In the present study, the efficacy and specificity of a ¹²⁵I-labeled CD93-specific monoclonal antibody (¹²⁵I-anti-CD93 mAb) in detecting NSCLC xenografts were analyzed, and the association between CD93 expression and ¹²⁵I-anti-CD93 mAb uptake by tumors was evaluated. The targeting ability of ¹²⁵I-anti-CD93 mAb enabled its rapid, continuous and highly specific accumulation in CD93-expressing tumors in vivo. These results revealed the potential applicability of ¹²⁵I-anti-CD93 mAb for non-invasive imaging diagnosis of CD93-positive NSCLC.

Glucose and glutamine metabolism in relation to mutational status in NSCLC histological subtypes

BACKGROUND

Both hypoxia and oncogenic mutations rewire tumor metabolism. In this study, glucose and glutamine metabolism-related markers were examined in stage I - resectable stage IIIA non-small cell lung cancer (NSCLC). Furthermore, expression of metabolism-related markers was correlated with mutational status to examine mutations associated with rewired tumor metabolism.

METHODS

Mutation analysis was performed for 97 tumors. Glucose and glutamine metabolism-related marker expression was measured by immunofluorescent staining (protein) and qPCR (mRNA) (n = 81).

RESULTS

Glutamine metabolism-related markers were significantly higher in adeno- than squamous cell NSCLCs. Glucose transporter 1 (GLUT1) protein expression was higher in solid compared to lepidic adenocarcinomas (P < 0.01). In adenocarcinomas, mRNA expression of glutamine transporter SLC1A5 correlated with tumor size (r(p) = 0.41, P = 0.005). Furthermore, SLC1A5 protein expression was significantly higher in adenocarcinomas with worse pTNM stage (r(s) = 0.39, P = 0.009). EGFR-mutated tumors showed lower GLUT1 protein (P = 0.017), higher glutaminase 2 (GLS2) protein (P = 0.025) and higher GLS2 mRNA expression (P = 0.004), compared to EGFR wild-type tumors. GLS mRNA expression was higher in KRAS-mutated tumors (P = 0.019). TP53-mutated tumors showed higher GLUT1 expression (P = 0.009).

CONCLUSIONS

NSCLC is a heterogeneous disease, with differences in mutational status and metabolism-related marker expression between adeno- and squamous cell NSCLCs, and also within adenocarcinoma subtypes. GLUT1 and SLC1A5 expression correlate with aggressive tumor behavior in adenocarcinomas but not in squamous cell NSCLCs. Therefore, these markers could steer treatment modification for subgroups of adenocarcinoma patients. TP53, EGFR and KRAS mutations are associated with expression of glucose and glutamine metabolism-related markers in NSCLC.