Correlation of metabolic information on FDG-PET with tissue expression of immune markers in patients with non-small cell lung cancer (NSCLC) who are candidates for upfront surgery

Repeated dynamic [18F]FDG PET/CT imaging using a high-sensitivity PET/CT scanner for assessing non-small cell lung cancer patients undergoing induction immuno-chemotherapy followed by hypo-fractionated chemoradiotherapy and consolidative immunotherapy: report from a prospective observational study (GASTO-1067)

OBJECTIVE

The study aims to investigate the role of dynamic [18F]FDG PET/CT imaging by high-sensitivity PET/CT scanner for assessing patients with locally advanced non-small cell lung cancer (LA-NSCLC) who undergo induction immuno-chemotherapy, followed by concurrent hypo-fractionated chemoradiotherapy (hypo-CCRT) and consolidative immunotherapy.

METHODS

Patients with unresectable LA-NSCLC are prospectively recruited. Dynamic [18F]FDG PET/CT scans are conducted at four timepoints: before treatment (Baseline), after induction immuno-chemotherapy (Post-IC), during hypo-CCRT (Mid-hypo-CCRT) and after hypo-CCRT (Post-hypo-CCRT). The primary lung tumors (PTs) are manually delineated, and the metabolic features, including the Patlak-Ki (Ki), maximum SUV (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have been evaluated. The expressions of CD3, CD8, CD68, CD163, CD34 and Ki67 in primary lung tumors at baseline are assayed by immunohistochemistry. The levels of blood lymphocytes at four timepoints are analyzed with flow cytometry.

RESULTS

Fifteen LA-NSCLC patients are enrolled between December 2020 and December 2022. Baseline Ki of primary tumor yields the highest AUC values of 0.722 and 0.796 for predicting disease progression and patient death, respectively. Patients are classified into the High FDG Ki group (n = 8, Ki > 2.779 ml/min/100 g) and the Low FDG Ki group (n = 7, Ki ≤ 2.779 ml/min/100 g). The High FDG Ki group presents better progression-free survival (P = 0.01) and overall survival (P = 0.025). The High FDG Ki group exhibits more significant reductions in Ki after hypo-CCRT compared to the Low FDG Ki group. Patients with a reduction in Ki > 73.1% exhibit better progression-free survival than those with a reduction ≤ 73.1% in Ki (median: not reached vs. 7.33 months, P = 0.12). The levels of CD3+ T cells (P = 0.003), CD8+ T cells (P = 0.002), CD68+ macrophages (P = 0.071) and CD163+ macrophages (P = 0.012) in primary tumor tissues are higher in the High FDG Ki group. The High FDG Ki group has higher CD3+CD8+ lymphocytes in blood at baseline (P = 0.108), post-IC (P = 0.023) and post-hypo-CCRT (P = 0.041) than the Low FDG Ki group.

CONCLUSIONS

The metabolic features in the High FDG Ki group significantly decrease during the treatment, particularly after induction immuno-chemotherapy. The Ki value of primary tumor shows significant relationship with the treatment response and survival in LA-NSCLC patients by the combined immuno-chemoradiotherapy regimen.

TRIAL REGISTRATION

ClinicalTrials.gov. NCT04654234. Registered 4 December 2020.

Conversion therapy with pembrolizumab for a peritoneal metastasis of rectal cancer causing hydronephrosis in a patient with Lynch syndrome

A 44-year-old woman with Lynch syndrome was referred to our hospital for treatment of recurrence of microsatellite instability-high rectal cancer. [18F]Fluorodeoxyglucose (18FDG)-positron emission tomography revealed a peritoneal metastasis with invasion to the small intestine and left ureter. The peritoneal metastasis was diagnosed initially as unresectable because of extensive invasion to the left ureter requiring nephrectomy. Hence, first-line treatment with pembrolizumab was started. After the first course of pembrolizumab, she developed hydronephrosis and a resulting urinary tract infection (UTI). A percutaneous nephrostomy was performed to control the UTI. After six courses of pembrolizumab, 18FDG-positron emission tomography showed that the peritoneal metastasis was smaller with significantly reduced 18FDG uptake, and it was then diagnosed as resectable without nephrectomy. She underwent R0 resection of the peritoneal metastasis with partial resection of the small intestine. Intraoperatively, the peritoneal metastasis showed no invasion of the left ureter, allowing its preservation. The percutaneous nephrostomy was removed postoperatively, and she has not developed any subsequent UTIs. Histopathologically, the tumor showed a pathological complete response to pembrolizumab. To the best of our knowledge, this is the first case of conversion therapy with pembrolizumab for peritoneal metastasis with hydronephrosis.

The role of radiotherapy in tumor immunity and the potential of PET/CT in detecting the expression of PD-1/PD-L1

Upregulation of PD-1/PD-L1 allows cancer cells to escape from host immune systems by functionally inactivating T-cell immune surveillance. Clinical blockade strategies have resulted in an increased prevalence of patients with late-stage cancers. However, many cancer patients had limited or no response to current immunotherapeutic strategies. Therefore, how to improve the sensitivity of immunotherapy has become the focus of attention of many scholars. Radiotherapy plays a role in the recruitment of T cells in the tumor microenvironment, increases CD4 + and CD8 + T cells, and increases PD-L1 expression, resulting in the synergistically enhanced antitumor effect of irradiation and PD-L1 blockade. Radiotherapy can cause changes in tumor metabolism, especially glucose metabolism. Tumor glycolysis and tumor immune evasion are interdependent, glycolytic activity enhances PD-L1 expression on tumor cells and thus promotes anti-PD-L1 immunotherapy response. Therefore, the mechanism of radiotherapy affecting tumor immunity may be partly through intervention of tumor glucose metabolism. Furthermore, some authors had found that the uptake of 2'-deoxy-2'-[18F]fluoro-D-glucose(18F-FDG) was correlated with PD-1/PD-L1 expression. Positron emission tomography/computed tomography (PET/CT) is a non-invasive detection method for PD-1/PD-L1 expression and has several potential advantages over immunohistochemical (IHC), PET/CT can dynamically reflect the expression of PD-1/PD-L1 inside the tumor and further guide clinical treatment.

Intraepithelial tumor-infiltrating lymphocytes shape loco-regional PET/CT spread of locally advanced cervical cancer

BACKGROUND

Data suggest an association between positron emission tomography/CT (PET/CT) metabolic metrics and tumor microenvironment in several malignancies, and a potential role of PET/CT to monitor response to immunotherapy.

OBJECTIVE

To evaluate the correlation between tumor loco-regional extension and tumor-infiltrating lymphocyte infiltration in locally advanced cervical cancer prior to concurrent chemo-radiotherapy.The secondary objective was to assess the association between tumor-infiltrating lymphocytes and PET/CT metabolic metrics.

METHODS

Patients with locally advanced cervical cancer and negative para-aortic extensions on PET/CT were included. Two senior nuclear medicine physicians specializing in gynecologic oncology reviewed all PET/CT exams, and extracted tumor maximum standardized uptake value, metabolic tumor volume, and total lesion glycolysis, as well as pelvic lymph node involvement. One senior gynecologic oncology pathologist assessed intraepithelial tumor-infiltrating lymphocytes and stromal tumor-infiltrating lymphocytes. Intraepithelial tumor-infiltrating lymphocytes were categorized following previous studies as <1% and >1%. The cut-off for stromal tumor-infiltrating lymphocytes was chosen empirically: intermediate <60% and high >60%.

RESULTS

86 patients were included. Intraepithelial tumor-infiltrating lymphocytes were not significantly associated with tumor metabolic metrics. Intraepithelial tumor-infiltrating lymphocytes were not significantly associated with maximum standard uptake value (p=0.16), or metabolic tumor volume (p=0.19). Tumors with <1% intraepithelial tumor-infiltrating lymphocytes score were associated with a higher MRI tumor size (≥ median) (63.3% vs 39.3%, p=0.04). Patients with pelvic lymph node uptake were significantly more frequent in patients with high stromal tumor-infiltrating lymphocytes score (≥60%) (61.5% vs 31.7%, p=0.009).

CONCLUSIONS

Poor or absent intraepithelial tumor-infiltrating lymphocytes were associated with more advanced disease at diagnosis and larger tumor size. Tumor-infiltrating lymphocytes were not associated with tumor metabolic activity. Intraepithelial and stroma tumor-infiltrating lymphocytes are not redundant and should be assessed separately. Further work is needed to evaluate the association between tumor metabolic profile and immune populations, including different T-cell subtypes for patient selection for immunotherapy strategies.

The predictive value of 18F-FDG PET/CT combined with inflammatory index for major pathological reactions in resectable NSCLC receiving neoadjuvant immunochemotherapy

OBJECTIVES

To investigate whether the combination of inflammatory biomarkers and metabolic parameters of 18F-FDG PET/CT could predict the major pathological reactions (MPR) in resectable NSCLC patients after neoadjuvant immunochemotherapy more accurately and screen out patients who may benefit from the neoadjuvant therapy.

MATERIALS AND METHODS

114 resectable NSCLC patients who underwent neoadjuvant immunochemotherapy and radical surgery were retrospectively enrolled. Detailed clinical characteristics, B-R and 18F-FDG PET/CT images were collected for analyzing their correlation with MPR. A metabolic-inflammation comprehensive prognostic index (MICPI) combined 18F-FDG PET/CT metabolic parameters and inflammatory index was proposed to predict MPR.

RESULTS

66.7 % patients achieved MPR. Smoking history, gender and ILO were influencing factors for MPR acquisition in NSCLC patients. High absolute neutrophils count (PreN ≥ 3.65), metabolic parameters (PreSUVmax ≥ 11.73) before treatment and ΔSUVmean (≥54.18) were significantly associated with MPR (P＜0.01, P＜0.05 and P＜0.001 respectively). MICPI-B based on PreN and PreSUVmax categorized NSCLC patients into three groups and among the groups of high, intermediate and low MICPI-B score, MPR accounted for 80.00 %, 51.72 % and 28.57 % respectively (P < 0.01). In high, intermediate and low MICPI-P groups which based on PreN and ΔSUVmean, MPR accounted for 92.31 %, 53.57 % and 11.11 %, respectively (P < 0.001).

CONCLUSION

PreN and metabolic parameter of 18F-FDG PET/CT may be an accurate alternative biomarker for predicting MPR in NSCLC patients after neoadjuvant immunochemotherapy. Moreover, MICPI can stratify patients into different groups based on their likelihood of obtaining MPR, allowing clinicians to identify patients who may most likely benefit from neoadjuvant immunochemotherapy.

Potential biomarkers for predicting immune response and outcomes in lung cancer patients undergoing thermal ablation

Thermal ablation is a promising alternative treatment for lung cancer. It disintegrates cancer cells and releases antigens, followed by the remodeling of local tumor immune microenvironment and the activation of anti-tumor immune responses, enhancing the overall effectiveness of the treatment. Biomarkers can offer insights into the patient's immune response and outcomes, such as local tumor control, recurrence, overall survival, and progression-free survival. Identifying and validating such biomarkers can significantly impact clinical decision-making, leading to personalized treatment strategies and improved patient outcomes. This review provides a comprehensive overview of the current state of research on potential biomarkers for predicting immune response and outcomes in lung cancer patients undergoing thermal ablation, including their potential role in lung cancer management, and the challenges and future directions.

DARS2 overexpression is associated with PET/CT metabolic parameters and affects glycolytic activity in lung adenocarcinoma

BACKGROUND

This study investigated the correlation between the expression of DARS2 and metabolic parameters of 18F-FDG PET/CT, and explored the potential mechanisms of DARS2 affecting the proliferation and glycolysis of lung adenocarcinoma (LUAD) cells.

METHODS

This study used genomics and proteomics to analyze the difference in DARS2 expression between LUAD samples and control samples. An analysis of 62 patients with LUAD who underwent 18F-FDG PET/CT examinations before surgery was conducted retrospectively. The correlation between DARS2 expression and PET/CT metabolic parameters, including SUVmax, SUVmean, MTV, and TLG, was examined by Spearman correlation analysis. In addition, the molecular mechanism of interfering with DARS2 expression in inhibiting LUAD cell proliferation and glycolysis was analyzed through in vitro cell experiments.

RESULTS

DARS2 expression was significantly higher in LUAD samples than in control samples (p < 0.001). DARS2 has high specificity (98.4%) and sensitivity (95.2%) in the diagnosis of LUAD. DARS2 expression was positively correlated with SUVmax, SUVmean, and TLG (p < 0.001). At the same time, the sensitivity and specificity of SUVmax in predicting DARS2 overexpression in LUAD were 88.9% and 65.9%, respectively. In vitro cell experiments have shown that interfering with DARS2 expression can inhibit the proliferation and migration of LUAD cells, promote cell apoptosis, and inhibit the glycolytic activity of tumor cells by inhibiting the expression of glycolytic related genes SLC2A1, GPI, ALDOA, and PGAM1.

CONCLUSIONS

Overexpression of DARS2 is associated with metabolic parameters on 18F-FDG PET/CT, which can improve LUAD diagnosis accuracy. DARS2 may be a useful biomarker to diagnose, prognosis, and target treatment of LUAD patients.

Immunotherapy for early-stage non-small cell lung cancer: A system review

With the addition of immunotherapy, lung cancer, one of the most common cancers with high mortality rates, has broadened the treatment landscape. Immune checkpoint inhibitors have demonstrated significant efficacy in the treatment of non-small cell lung cancer (NSCLC) and are now used as the first-line therapy for metastatic disease, consolidation therapy after radiotherapy for unresectable locally advanced disease, and adjuvant therapy after surgical resection and chemotherapy for resectable disease. The use of adjuvant and neoadjuvant immunotherapy in patients with early-stage NSCLC, however, is still debatable. We will address several aspects, namely the initial efficacy of monotherapy, the efficacy of combination chemotherapy, immunotherapy-related biomarkers, adverse effects, ongoing randomized controlled trials, and current issues and future directions for immunotherapy in early-stage NSCLC will be discussed here.

Utility of 18F-FDG uptake in predicting major pathological response to neoadjuvant immunotherapy in patients with resectable non‑small cell lung cancer

PURPOSE

The aim of present study was to investigate the efficiency of ¹⁸F-FDG uptake in predicting major pathological response (MPR) in resectable non-small cell lung cancer (NSCLC) patients with neoadjuvant immunotherapy.

METHODS

A total of 104 patients with stage I-IIIB NSCLC were retrospectively derived from National Cancer Center of China, of which 36 cases received immune checkpoint inhibitors (ICIs) monotherapy (I-M) and 68 cases with ICI combination therapy (I-C). ¹⁸F-FDG PET-CT scans were performed at baseline and after neoadjuvant therapy (NAT). Receiver-operating characteristic (ROC) curve analyses were conducted and area under ROC curve (AUC) was calculated for biomarkers including maximum standardized uptake value (SUVmax), inflammatory biomarkers, tumor mutation burden (TMB), PD-L1 tumor proportion score (TPS) and iRECIST.

RESULTS

Fifty-four resected NSCLC tumors achieved MPR (51.9%, 54/104). In both neoadjuvant I-M and I-C cohorts, post-NAT SUVmax and the percentage changes of SUVmax (ΔSUVmax%) were significantly lower in the patients with MPR versus non-MPR (p < 0.01), and were also negatively correlated with the degree of pathological regression (p < 0.01). The AUC of ΔSUVmax% for predicting MPR was respectively 1.00 (95% CI: 1.00-1.00) in neoadjuvant I-M cohort and 0.94 (95% CI: 0.86-1.00) in I-C cohort. Baseline SUVmax had a statistical prediction value for MPR only in I-M cohort, with an AUC up to 0.76 at the threshold of 17.0. ΔSUVmax% showed an obvious advantage in MPR prediction over inflammatory biomarkers, TMB, PD-L1 TPS and iRECIST.

CONCLUSION

¹⁸F-FDG uptake can predict MPR in NSCLC patients with neoadjuvant immunotherapy.

Immune checkpoint inhibition: a future guided by radiology

The limitation of the function of antitumour immune cells is a common hallmark of cancers that enables their survival. As such, the potential of immune checkpoint inhibition (ICI) acts as a paradigm shift in the treatment of a range of cancers but has not yet been fully capitalised. Combining minimally and non-invasive locoregional therapies offered by radiologists with ICI is now an active field of research with the aim of furthering therapeutic capabilities in medical oncology. In parallel to this impending advancement, the "imaging toolbox" available to radiologists is also growing, enabling more refined tumour characterisation as well as greater accuracy in evaluating responses to therapy. Options range from metabolite labelling to cellular localisation to immune checkpoint screening. It is foreseeable that these novel imaging techniques will be integrated into personalised treatment algorithms. This growth in the field must include updating the current standardised imaging criteria to ensure they are fit for purpose. Such criteria is crucial to both appropriately guide clinical decision-making regarding next steps of treatment, but also provide reliable prognosis. Quantitative approaches to these novel imaging techniques are also already being investigated to further optimise personalised therapeutic decision-making. The therapeutic potential of specific ICIs and locoregional therapies could be determined before administration thus limiting unnecessary side-effects whilst maintaining efficacy. Several radiological aspects of oncological care are advancing simultaneously. Therefore, it is essential that each development is assessed for clinical use and optimised to ensure the best treatment decisions are being offered to the patient. In this review, we discuss state of the art advances in novel functional imaging techniques in the field of immuno-oncology both pre-clinically and clinically.

Tumor infiltrating lymphocytes and radiological picture of the tumor

Tumor microenvironment (TME) is a complex entity that includes besides the tumor cells also a whole range of immune cells. Among various populations of immune cells infiltrating the tumor, tumor infiltrating lymphocytes (TILs) are a population of lymphocytes characterized by high reactivity against the tumor component. As, TILs play a key role in mediating responses to several types of therapy and significantly improve patient outcomes in some cancer types including for instance breast cancer and lung cancer, their assessment has become a good predictive tool in the evaluation of potential treatment efficacy. Currently, the evaluation of the density of TILs infiltration is performed by histopathological. However, recent studies have shed light on potential utility of several imaging methods, including ultrasonography, magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), and radiomics, in the assessment of TILs levels. The greatest attention concerning the utility of radiology methods is directed to breast and lung cancers, nevertheless imaging methods of TILs are constantly being developed also for other malignancies. Here, we focus on reviewing the radiological methods used to assess the level of TILs in different cancer types and on the extraction of the most favorable radiological features assessed by each method.

The role of 18F-FDG PET in predicting the pathological response and prognosis to unresectable HCC patients treated with lenvatinib and PD-1 inhibitors as a conversion therapy

Purpose

To investigate the diagnostic value of ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET), as an imaging biomarker, for predicting pathological response and prognosis of unresectable hepatocellular carcinoma (HCC) patients treated with Lenvatinib and programmed cell death protein 1 (PD-1) inhibitors as a conversion therapy.

Methods

A total of 28 unresectable HCC patients with BCLC stage B or C were treated with Lenvatinib and PD-1 inhibitors before surgery. The ¹⁸F-FDG PET/CT scans were acquired before pre- (scan-1) and post-conversion therapy (scan-2). The maximum standardized uptake value (SUVmax), TLR (tumor-to-normal liver standardized uptake value ratio), and the percentages of post-treatment changes in metabolic parameters (ΔSUVmax [%] and ΔTLR [%]) were calculated. Major pathological response (MPR) was identified based on the residual viable tumor in the resected primary tumor specimen (≤10%). Differences in the progression-free survival (PFS) and overall survival (OS) stratified by ΔTLR were examined by the Kaplan-Meier method.

Results

11 (11/28, 39.3%) patients were considered as MPR responders and 17 (17/28, 60.7%) patients as non-MPR responders after conversion therapy. ΔSUVmax (-70.0 [-78.8, -48.8] vs. -21.7 [-38.8, 5.7], respectively; P<0.001) and ΔTLR (-67.6 [-78.1, -56.8] vs. -18.6 [-27.9, 4.0], respectively; P<0.001) were reduced in the responder group than those in the non-responder group. According to the results of the receiver operating characteristic curve analysis, ΔTLR showed an excellent predictive value for the MPR of primary HCC lesions (area under curve=0.989, with the optimal diagnostic threshold of -46.15). When using ΔTLR of -21.36% as a threshold, patients with ΔTLR-based metabolic response had superior PFS (log-rank test, P=0.001) and OS (log-rank test, P=0.016) compared with those without ΔTLR-based metabolic response.

Conclusion

¹⁸F-FDG PET is a valuable tool for predicting pathological response and prognosis of unresectable HCC patients treated by Lenvatinib combined with PD-1 as a conversion therapy.

Correlation of 18F-FDG PET/CT metabolic parameters with the expression of immune biomarkers in the tumour microenvironment in lung adenocarcinoma

AIM

To explore the association between metabolic parameters evaluated by integrated 2-[¹⁸F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET)/computed tomography (CT) and the expression of immune biomarkers in the tumour microenvironment in lung adenocarcinoma.

MATERIALS AND METHODS

This study included 134 patients. Metabolic parameters were obtained by PET/CT. Immunohistochemistry analysis was used for FOXP3-TILs (transcription factor forkhead box protein 3 tumour-infiltrating lymphocytes), CD8-TILs, CD4-TILs, CD68-TAMs (tumour-associated macrophages) and galectin-1 (Gal-1) tumour expression.

RESULTS

There were significant positive associations between FDG PET metabolic parameters and the median percentage of immune reactive areas (IRA%) covered by FOXP3-TILs and CD68-TAMs. Negative associations with the median IRA% covered by CD4-TILs and CD8-TILs were observed: maximal standardised uptake value (SUV_max), metabolic tumour volume (MTV), total lesion glycolysis (TLG), and IRA% for FOXP3-TILs (rho = 0.437, 0.400, 0.414; p<0.0001 for all parameters); SUV_max, MTV, TLG, and IRA% for CD68-TAMs (rho = 0.356, 0.355, 0.354; p<0.0001 for all parameters); SUV_max, MTV, TLG, and IRA% for CD4-TILs (rho = -0.164, -0.190, -0.191; p=0.059, 0.028, 0.027, respectively); SUV_max, MTV, TLG, and IRA% for CD8-TILs (rho = -0.305, -0.316, -0.322; p<0.0001 for all parameters). There were significant positive associations between tumour Gal-1 expression and the median IRA% covered by FOXP3-TILs and CD68-TAMs (rho = 0.379; p<0.0001; rho = 0.370; p<0.0001, respectively), and a significant negative association with the median IRA% covered by CD8-TILs (rho = -0.347; p<0.0001) was observed. Tumour stage (p=0.008), Gal-1 expression (p=0.008), and median IRA% covered by CD8-TILs (p=0.054) were independent risk factors for overall survival.

CONCLUSION

FDG PET may facilitate a comprehensive evaluation of the tumour microenvironment and predict response to immunotherapy.

Facts and Perspectives: Implications of tumor glycolysis on immunotherapy response in triple negative breast cancer

Triple negative breast cancer (TNBC) is an aggressive disease that is difficult to treat and portends a poor prognosis in many patients. Recent efforts to implement immune checkpoint inhibitors into the treatment landscape of TNBC have led to improved outcomes in a subset of patients both in the early stage and metastatic settings. However, a large portion of patients with TNBC remain resistant to immune checkpoint inhibitors and have limited treatment options beyond cytotoxic chemotherapy. The interplay between the anti-tumor immune response and tumor metabolism contributes to immunotherapy response in the preclinical setting, and likely in the clinical setting as well. Specifically, tumor glycolysis and lactate production influence the tumor immune microenvironment through creation of metabolic competition with infiltrating immune cells, which impacts response to immune checkpoint blockade. In this review, we will focus on how glucose metabolism within TNBC tumors influences the response to immune checkpoint blockade and potential ways of harnessing this information to improve clinical outcomes.

Relationship between FDG-PET and the immune microenvironment in breast cancer

OBJECTIVE

To investigate the relationship between fluorodeoxyglucose (FDG) uptake (maximum standardised uptake value [SUVmax]) and immune markers (tumour-infiltrating lymphocytes [TILs] and neutrophil-to-lymphocyte ratio [NLR]) and evaluate the potential prognostic value of any correlations.

METHODS

Data from 502 patients with breast cancer, including 346 oestrogen receptor (ER)-positive / human epidermal growth factor receptor 2 (HER2)-negative, 88 HER2-positive, and 68 triple-negative cases, who had undergone surgery were reviewed. Relationships between the clinicopathological factors, SUVmax, TILs, NLR, recurrence-free survival (RFS), and overall survival of all patients and each subtype were evaluated using a Cox proportional hazards model and log-rank test. A sub-analysis of patients divided into low and high TIL groups was also undertaken.

RESULTS

High SUVmax was significantly related to high TILs (p < 0.0001). In low TIL (TILs1) group, patients with high SUVmax (≥3.585) had a significantly shorter RFS than those with low SUVmax (<3.585; p < 0.0001). In high TIL (TILs2,3) group, patients with high SUVmax had a shorter RFS than those with low SUVmax without a significant difference (p = 0.35). Multivariate analysis of 502 patients showed high SUVmax, high T status, and nodal metastasis were independent negative predictors of RFS. In 317 TILs-low patients, high SUVmax, high T status, nodal metastasis, and ER-positivity were independent predictors of RFS. In 185 TILs-high patients, nodal metastasis was an independent predictor of RFS. In ER-positive/HER2-negative and HER2-positive subtypes, SUVmax was a significant predictive parameter in the TILs-low but not TILs-high groups.

CONCLUSION

FDG uptake may be predictive of immunological features and aggressive features in breast cancer patients.

Prognostic value of 18F-FDG PET/CT in patients with advanced or metastatic non-small-cell lung cancer treated with immune checkpoint inhibitors: A systematic review and meta-analysis

PURPOSE

This study aimed to investigate the value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting early immunotherapy response of immune checkpoint inhibitors (ICIs) in patients with advanced or metastatic non-small-cell lung cancer (NSCLC).

METHODS

A comprehensive search of PubMed, Web of science, Embase and the Cochrane library was performed to examine the prognostic value of 18F-FDG PET/CT in predicting early immunotherapy response of ICIs in patients with NSCLC. The main outcomes for evaluation were overall survival (OS) and progression-free survival (PFS). Detailed data from each study were extracted and analyzed using STATA 14.0 software.

RESULTS

13 eligible articles were included in this systematic review. Compared to baseline 18F-FDG PET/CT imaging, the pooled hazard ratios (HR) of maximum and mean standardized uptake values SUVmax, SUVmean, MTV and TLG for OS were 0.88 (95% CI: 0.69-1.12), 0.79 (95% CI: 0.50-1.27), 2.10 (95% CI: 1.57-2.82) and 1.58 (95% CI: 1.03-2.44), respectively. The pooled HR of SUVmax, SUVmean, MTV and TLG for PFS were 1.06 (95% CI: 0.68-1.65), 0.66 (95% CI: 0.48-0.90), 1.50 (95% CI: 1.26-1.79), 1.27 (95% CI: 0.92-1.77), respectively. Subgroup analysis showed that high MTV group had shorter OS than low MTV group in both first line group (HR: 1.97, 95% CI: 1.39-2.79) and undefined line group (HR: 2.11, 95% CI: 1.61-2.77). High MTV group also showed a shorter PFS in first line group (HR: 1.85, 95% CI: 1.28-2.68), and low TLG group had a longer OS in undefined group (HR: 1.37, 95% CI: 1.00-1.86). No significant differences were in other subgroup analysis.

CONCLUSION

Baseline MTV and TLG may have predictive value and should be prospectively studied in clinical trials. Baseline SUVmax and SUVmean may not be appropriate prognostic markers in advanced or metastatic NSCLC patients treated with ICIs.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=323906, identifier CRD42022323906.

PET/CT molecular imaging in the era of immune-checkpoint inhibitors therapy

Cancer immunotherapy, especially immune-checkpoint inhibitors (ICIs), has paved a new way for the treatment of many types of malignancies, particularly advanced-stage cancers. Accumulating evidence suggests that as a molecular imaging modality, positron emission tomography/computed tomography (PET/CT) can play a vital role in the management of ICIs therapy by using different molecular probes and metabolic parameters. In this review, we will provide a comprehensive overview of the clinical data to support the importance of 18F-fluorodeoxyglucose PET/CT (18F-FDG PET/CT) imaging in the treatment of ICIs, including the evaluation of the tumor microenvironment, discovery of immune-related adverse events, evaluation of therapeutic efficacy, and prediction of therapeutic prognosis. We also discuss perspectives on the development direction of 18F-FDG PET/CT imaging, with a particular emphasis on possible challenges in the future. In addition, we summarize the researches on novel PET molecular probes that are expected to potentially promote the precise application of ICIs.

The predictive value of total-body PET/CT in non-small cell lung cancer for the PD-L1 high expression

Purpose

Total-body positron emission tomography/computed tomography (PET/CT) provides faster scanning speed, higher image quality, and lower injected dose. To compensate for the shortcomings of the maximum standard uptake value (SUVmax), we aimed to normalize the values of PET parameters using liver and blood pool SUV (SUR-L and SUR-BP) to predict programmed cell death-ligand 1 (PD-L1) expression in non-small cell lung cancer (NSCLC) patients.

Materials and methods

A total of 138 (104 adenocarcinoma and 34 squamous cell carcinoma) primary diagnosed NSCLC patients who underwent ¹⁸F-FDG-PET/CT imaging were analyzed retrospectively. Immunohistochemistry (IHC) analysis was performed for PD-L1 expression on tumor cells and tumor-infiltrating immune cells with 22C3 antibody. Positive PD-L1 expression was defined as tumor cells no less than 50% or tumor-infiltrating immune cells no less than 10%. The relationships between PD-L1 expression and PET parameters (SUVmax, SUR-L, and SUR-BP) and clinical variables were analyzed. Statistical analysis included χ² test, receiver operating characteristic (ROC), and binary logistic regression.

Results

There were 36 patients (26%) expressing PD-L1 positively. Gender, smoking history, Ki-67, and histologic subtype were related factors. SUVmax, SUR-L, and SUR-BP were significantly higher in the positive subset than those in the negative subset. Among them, the area under the curve (AUC) of SUR-L on the ROC curve was the biggest one. In NSCLC patients, the best cutoff value of SUR-L for PD-L1-positive expression was 4.84 (AUC = 0.702, P = 0.000, sensitivity = 83.3%, specificity = 54.9%). Multivariate analysis confirmed that age and SUR-L were correlated factors in adenocarcinoma (ADC) patients.

Conclusion

SUVmax, SUR-L, and SUR-BP had utility in predicting PD-L1 high expression, and SUR-L was the most reliable parameter. PET/CT can offer reference to screen patients for first-line atezolizumab therapy.

Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis

Background

Immune checkpoint inhibitors (ICIs) have emerged as a promising treatment option for advanced non-small-cell lung cancer (NSCLC) patients, highlighting the need for biomarkers to identify responders and predict the outcome of ICIs. The purpose of this study was to evaluate the predictive value of baseline standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) derived from 18F-FDG-PET/CT in advanced NSCLC patients receiving ICIs.

Methods

PubMed and Web of Science databases were searched from January 1st, 2011 to July 18th, 2022, utilizing the search terms “non-small-cell lung cancer”, “PET/CT”, “standardized uptake value”, “metabolic tumor volume”, “ total lesion glycolysis”, and “immune checkpoint inhibitors”. Studies that analyzed the association between PET/CT parameters and objective response, immune-related adverse events (irAEs) and prognosis of NSCLC patients treated with ICIs were included. We extracted the hazard ratio (HR) with a 95% confidence interval (CI) for progression-free survival (PFS) and overall survival (OS). We performed a meta-analysis of HR using Review Manager v.5.4.1.

Results

Sixteen studies were included for review and thirteen for meta-analysis covering 770 patients. As for objective response and irAEs after ICIs, more studies with consistent assessment methods are needed to determine their relationship with MTV. In the meta-analysis, low SUVmax corresponded to poor PFS with a pooled HR of 0.74 (95% CI, 0.57-0.96, P=0.02). And a high level of baseline MTV level was related to shorter PFS (HR=1.45, 95% CI, 1.11-1.89, P<0.01) and OS (HR, 2.72; 95% CI, 1.97-3.73, P<0.01) especially when the cut-off value was set between 50-100 cm³. SUVmean and TLG were not associated with the prognosis of NSCLC patients receiving ICIs.

Conclusions

High level of baseline MTV corresponded to shorter PFS and OS, especially when the cut-off value was set between 50-100 cm³. MTV is a potential predictive value for the outcome of ICIs in NSCLC patients.

Dynamic 18 F-FDG PET/CT can predict the major pathological response to neoadjuvant immunotherapy in non-small cell lung cancer

Major pathological response (MPR) is a potential surrogate for overall survival. We determined whether the dynamic changes in ¹⁸ F-labeled fluoro-2-deoxyglucose positron emission tomography/computed tomography (¹⁸ F-FDG PET/CT) were associated with MPR in patients receiving neoadjuvant immunotherapy. Forty-four patients with stage II-III non-small cell lung cancer (NSCLC) who received neoadjuvant immunotherapy and radical surgery were enrolled. Moreover, ¹⁸ F-FDG PET/CT scans were performed at baseline and within 1 week before surgery to evaluate the disease. All histological sections were reviewed to assess MPR. The detailed clinical features of the patients were analyzed. The reliability of the clinical variables was assessed in differentiating between MPR and non-MPR using logistic regression. Receiver-operating characteristic (ROC) curve analysis identified the SUVmax changes threshold most associated with MPR. Most of the patients were pathologically diagnosed with squamous cell carcinoma and received anti-PD-1 antibodies plus chemotherapy. The immunotherapy regimens included nivolumab, pembrolizumab, and camrelizumab. MPR was observed in more than half of lesions. Tumors with MPR had a higher decrease in the longest dimension on dynamic PET/CT than those without MPR. Furthermore, the decline in SUVmax was significantly different between MPR and non-MPR diseases, and MPR lesions had a prominent mean reduction in SUVmax. SUVmax reduction was independently associated with MPR in the multivariate regression. On ROC analysis, the threshold of SUVmax decrease in 60% was associated with MPR. Dynamic changes in SUVmax were associated with MPR. The tumors with MPR showed a greater PET/CT response than those without MPR. A SUVmax decrease of more than 60% is more likely to result in an MPR after receiving neoadjuvant immunotherapy.

What does radiomics do in PD-L1 blockade therapy of NSCLC patients?

With the in‐depth understanding of programmed cell death 1 ligand 1 (PD‐L1) in non‐small cell lung cancer (NSCLC), PD‐L1 has become a vital immunotherapy target and a significant biomarker. The clinical utility of detecting PD‐L1 by immunohistochemistry or next‐generation sequencing has been written into guidelines. However, the application of these methods is limited in some circumstances where the biopsy size is small or not accessible, or a dynamic monitor is needed. Radiomics can noninvasively, in real‐time, and quantitatively analyze medical images to reflect deeper information about diseases. Since radiomics was proposed in 2012, it has been widely used in disease diagnosis and differential diagnosis, tumor staging and grading, gene and protein phenotype prediction, treatment plan decision‐making, efficacy evaluation, and prognosis prediction. To explore the feasibility of the clinical application of radiomics in predicting PD‐L1 expression, immunotherapy response, and long‐term prognosis, we comprehensively reviewed and summarized recently published works in NSCLC. In conclusion, radiomics is expected to be a companion to the whole immunotherapy process.

Molecular imaging to support cancer immunotherapy

The advent of immune checkpoint inhibitors has reinvigorated the field of immuno-oncology. These monoclonal antibody-based therapies allow the immune system to recognize and eliminate malignant cells. This has resulted in improved survival of patients across several tumor types. However, not all patients respond to immunotherapy therefore predictive biomarkers are important. There are only a few Food and Drug Administration-approved biomarkers to select patients for immunotherapy. These biomarkers do not consider the heterogeneity of tumor characteristics across lesions within a patient. New molecular imaging tracers allow for whole-body visualization with positron emission tomography (PET) of tumor and immune cell characteristics, and drug distribution, which might guide treatment decision making. Here, we summarize recent developments in molecular imaging of immune checkpoint molecules, such as PD-L1, PD-1, CTLA-4, and LAG-3. We discuss several molecular imaging approaches of immune cell subsets and briefly summarize the role of FDG-PET for evaluating cancer immunotherapy. The main focus is on developments in clinical molecular imaging studies, next to preclinical studies of interest given their potential translation to the clinic.

18F FDG PET/CT and Novel Molecular Imaging for Directing Immunotherapy in Cancer

Immunotherapy has transformed the treatment landscape of many cancers, with durable responses in disease previously associated with a poor prognosis. Patient selection remains a challenge, with predictive biomarkers an urgent unmet clinical need. Current predictive biomarkers, including programmed death-ligand 1 (PD-L1) (measured with immunohistochemistry), are imperfect. Promising biomarkers, including tumor mutation burden and tumor infiltrating lymphocyte density, fail to consistently predict response and have yet to translate to routine clinical practice. Heterogeneity of immune response within and between lesions presents a further challenge where fluorine 18 fluorodeoxyglucose PET/CT has a potential role in assessing response, stratifying treatment, and detecting and monitoring immune-related toxicities. Novel radiopharmaceuticals also present a unique opportunity to define the immune tumor microenvironment to better predict which patients may respond to therapy, for example by means of in vivo whole-body PD-L1 and CD8+ T cell expression imaging. In addition, longitudinal molecular imaging may help further define dynamic changes, particularly in cases of immunotherapy resistance, helping to direct a more personalized therapeutic approach. This review highlights current and emerging applications of molecular imaging to stratify, predict, and monitor molecular dynamics and treatment response in areas of clinical need.

Radiomic Signatures Associated with CD8+ Tumour-Infiltrating Lymphocytes: A Systematic Review and Quality Assessment Study

The tumour immune microenvironment influences the efficacy of immune checkpoint inhibitors. Within this microenvironment are CD8-expressing tumour-infiltrating lymphocytes (CD8+ TILs), which are an important mediator and marker of anti-tumour response. In practice, the assessment of CD8+ TILs via tissue sampling involves logistical challenges. Radiomics, the high-throughput extraction of features from medical images, may offer a novel and non-invasive alternative. We performed a systematic review of the available literature reporting radiomic signatures associated with CD8+ TILs. We also aimed to evaluate the methodological quality of the identified studies using the Radiomics Quality Score (RQS) tool, and the risk of bias and applicability with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Articles were searched from inception until 31 December 2021, in three electronic databases, and screened against eligibility criteria. Twenty-seven articles were included. A wide variety of cancers have been studied. The reported radiomic signatures were heterogeneous, with very limited reproducibility between studies of the same cancer group. The overall quality of studies was found to be less than desirable (mean RQS = 33.3%), indicating a need for technical maturation. Some potential avenues for further investigation are also discussed.

Prognostic impact of an integrative analysis of [18F]FDG PET parameters and infiltrating immune cell scores in lung adenocarcinoma

Background

High levels of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) tumor uptake are associated with worse prognosis in patients with non-small cell lung cancer (NSCLC). Meanwhile, high levels of immune cell infiltration in primary tumor have been linked to better prognosis in NSCLC. We conducted this study for precisely stratified prognosis of the lung adenocarcinoma patients using the integration of ¹⁸F-FDG positron emission tomography (PET) parameters and infiltrating immune cell scores as assessed by a genomic analysis.

Results

Using an RNA sequencing dataset, the patients were divided into three subtype groups. Additionally, 24 different immune cell scores and cytolytic scores (CYT) were obtained. In ¹⁸F-FDG PET scans, PET parameters of the primary tumors were obtained. An ANOVA test, a Chi-square test and a correlation analysis were also conducted. A Kaplan–Meier survival analysis with the log-rank test and multivariable Cox regression test was performed to evaluate prognostic values of the parameters. The terminal respiratory unit (TRU) group demonstrated lower ¹⁸F-FDG PET parameters, more females, and lower stages than the other groups. Meanwhile, the proximal inflammatory (PI) group showed a significantly higher CYT score compared to the other groups (P = .001). Also, CYT showed a positive correlation with tumor-to-liver maximum standardized uptake value ratio (TLR) in the PI group (P = .027). A high TLR (P = .01) score of ¹⁸F-FDG PET parameters and a high T follicular helper cell (TFH) score (P = .005) of immune cell scores were associated with prognosis with opposite tendencies. Furthermore, TLR and TFH were predictive of overall survival even after adjusting for clinicopathologic features and others (P = .024 and .047).

Conclusions

A high TLR score was found to be associated with worse prognosis, while high CD8 T cell and TFH scores predicted better prognosis in lung adenocarcinoma. Furthermore, TLR and TFH can be used to predict prognosis independently in patients with lung adenocarcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13550-022-00908-9.

Pretreatment Metabolic Parameters Measured by 18F-FDG PET to Predict the Pathological Treatment Response of HCC Patients Treated With PD-1 Inhibitors and Lenvatinib as a Conversion Therapy in BCLC Stage C

Objectives

This study aimed to assess the pretreatment ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) as a predictor of the pathological treatment response (PTR) of hepatocellular carcinoma (HCC) patients treated with PD-1 inhibitors and lenvatinib as a conversion therapy in BCLC stage C.

Methods

All patients (n=20) underwent pretreatment ¹⁸F-FDG PET/CT and were treated with conversion therapy and surgery. Patients were categorized into responders (n=9) and non-responders (n=11) according to PTR. The parameters of PET/CT, including lesion size, SUVmean (mean standard uptake value), MTV (metabolic tumor volume), TLG (total lesion glycolysis), SUVpeak (peak standard uptake value), and TLR (tumor-to-normal liver standardized uptake value ratio), were calculated. The diagnostic efficacy was evaluated by receiver operating characteristic analysis (ROC). PTR was compared with pretreatment PET/CT parameters by using Spearman correlation analysis. The patients were followed up.

Results

There was significant difference in TLR (5.59 ± 1.90 vs. 2.84 ± 1.70, respectively; P=0.003) between responders and non-responders, with the largest area under the curve (sensitivity=100%, specificity=72.7%, AUC=0.899, 95%CI: 0.759-1.000, optimal diagnostic threshold of 3.09). The relationship between ¹⁸F-FDG PET/CT parameters and PTR indicated TLR was moderately and positively correlated with pathological treatment response, with correlation coefficients (rs) of 0.69 (P<0.01). During the follow-up, no patients died, and tumor recurrence was found in one of the responders (11.1%). In all 11 non-responders, tumor recurrence was found in six patients (54.5%) and four patients (36.4%) died.

Conclusions

TLR may be a powerful marker to predict PTR of HCC patients with BCLC stage C who were treated with conversion therapy.

A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts Tumor Immune Profiles in Non-Small Cell Lung Cancer: A Retrospective Multicohort Study

Background

The tumor immune microenvironment (TIME) phenotypes have been reported to mainly impact the efficacy of immunotherapy. Given the increasing use of immunotherapy in cancers, knowing an individual's TIME phenotypes could be helpful in screening patients who are more likely to respond to immunotherapy. Our study intended to establish, validate, and apply a machine learning model to predict TIME profiles in non-small cell lung cancer (NSCLC) by using 18F-FDG PET/CT radiomics and clinical characteristics.

Methods

The RNA-seq data of 1145 NSCLC patients from The Cancer Genome Atlas (TCGA) cohort were analyzed. Then, 221 NSCLC patients from Daping Hospital (DPH) cohort received18F-FDG PET/CT scans before treatment and CD8 expression of the tumor samples were tested. The Artificial Intelligence Kit software was used to extract radiomic features of PET/CT images and develop a radiomics signature. The models were established by radiomics, clinical features, and radiomics-clinical combination, respectively, the performance of which was calculated by receiver operating curves (ROCs) and compared by DeLong test. Moreover, based on radiomics score (Rad-score) and clinical features, a nomogram was established. Finally, we applied the combined model to evaluate TIME phenotypes of NSCLC patients in The Cancer Imaging Archive (TCIA) cohort (n = 39).

Results

TCGA data showed CD8 expression could represent the TIME profiles in NSCLC. In DPH cohort, PET/CT radiomics model outperformed CT model (AUC: 0.907 vs. 0.861, P = 0.0314) to predict CD8 expression. Further, PET/CT radiomics-clinical combined model (AUC = 0.932) outperformed PET/CT radiomics model (AUC = 0.907, P = 0.0326) or clinical model (AUC = 0.868, P = 0.0036) to predict CD8 expression. In the TCIA cohort, the predicted CD8-high group had significantly higher immune scores and more activated immune pathways than the predicted CD8-low group (P = 0.0421).

Conclusion

Our study indicates that 18F-FDG PET/CT radiomics-clinical combined model could be a clinically practical method to non-invasively detect the tumor immune status in NSCLCs.

Thoracic Imaging Manifestations of Treated Lymphomas: Response Evaluation, Posttherapeutic Sequelae, and Complications

Lymphoma is the most common hematologic malignancy comprising a diverse group of neoplasms arising from multiple blood cell lineages. Any structure of the thorax may be involved at any stage of disease. Imaging has a central role in the initial staging, response assessment, and surveillance of lymphoma, and updated standardized assessment criteria are available to assist with imaging interpretation and reporting. Radiologists should be aware of the modern approaches to lymphoma treatment, the role of imaging in posttherapeutic surveillance, and manifestations of therapy-related complications.

Correlation of epidermal growth factor receptor mutation status and PD-L1 expression with [18F]FDG PET using volume-based parameters in non-small cell lung cancer

OBJECTIVE

We investigated the relationship between 2-deoxy-2-[18F]fluoro-D-glucose (FDG) PET using volume-based parameters and epidermal growth factor receptor (EGFR) mutation status, programmed death-ligand-1 (PD-L1) expression level, and their combination, in pretreated non-small cell lung cancer (NSCLC).

METHODS

FDG PET findings and EGFR mutation status and PD-L1 expression level were investigated retrospectively in 93 patients with newly diagnosed NSCLC (77 adenocarcinomas, 16 squamous cell carcinomas). Tumors were divided into six groups: EGFR mutant/negative PD-L1, EGFR mutant/low PD-L1, EGFR mutant/high PD-L1, EGFR wild/negative PD-L1, EGFR wild/low PD-L1, and EGFR wild/high PD-L1. The maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) for primary tumor were measured from PET images. The EGFR mutation status and PD-L1 expression level were estimated in tumor tissue specimens and compared with the PET parameters.

RESULTS

None of the PET parameters differed significantly between EGFR-mutated and wild-type EGFR. According to the PD-L1 level, significant differences were detected in SUVmax (P = 0.001) and TLG (P = 0.016), but not MTV. Comparing all six groups, significant difference was detected in only SUVmax (P = 0.011).

CONCLUSION

Based on the preliminary results of this study, FDG PET may help in the prediction of PD-L1 expression level, but not EGFR mutation status, in patients with newly diagnosed NSCLC. The SUVmax rather than MTV or TLG, may be of value in predicting the six groups according to the combination of EGFR mutation status and PD-L1 expression level.

Potentials of Non-Invasive 18F-FDG PET/CT in Immunotherapy Prediction for Non–Small Cell Lung Cancer

The immune checkpoint inhibitors (ICIs), by targeting cytotoxic-T-lymphocyte-associated protein 4, programmed cell death 1 (PD-1), or PD-ligand 1, have dramatically changed the natural history of several cancers, including non–small cell lung cancer (NSCLC). There are unusual response manifestations (such as pseudo-progression, hyper-progression, and immune-related adverse events) observed in patients with ICIs because of the unique mechanisms of these agents. These specific situations challenge response and prognostic assessment to ICIs challenging. This review demonstrates how ¹⁸F-FDG PET/CT can help identify these unusual response patterns in a non-invasive and effective way. Then, a series of semi-quantitative parameters derived from ¹⁸F-FDG PET/CT are introduced. These indexes have been recognized as the non-invasive biomarkers to predicting the efficacy of ICIs and survival of NSCLC patients according to the latest clinical studies. Moreover, the current situation regarding the functional criteria based on ¹⁸F-FDG PET/CT for immunotherapeutic response assessment is presented and analyzed. Although the criteria based on ¹⁸F-FDG PET/CT proposed some resolutions to overcome limitations of morphologic criteria in the assessment of tumor response to ICIs, further researches should be performed to validate and improve these assessing systems. Then, the last part in this review displays the present status and a perspective of novel specific PET probes targeting key molecules relevant to immunotherapy in prediction and response assessment.

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.

Artificial intelligence in cancer diagnostics and therapy: current perspectives

Artificial intelligence (AI) has found its way into every sphere of human life including the field of medicine. Detection of cancer might be AI's most altruistic and convoluted challenge to date in the field of medicine. Embedding AI into various aspects of cancer diagnostics would be of immense use in dealing with the tedious, repetitive, time-consuming job of lesion detection, remove opportunities for human error, and cut costs and time. This would be of great value in cancer screening programs. By using AI algorithms, data from digital images from radiology and pathology that are imperceptible to the human eye can be identified (radiomics and pathomics). Correlating radiomics and pathomics with clinico-demographic-therapy-morbidity-mortality profiles will lead to a greater understanding of cancers. Specific imaging phenotypes have been found to be associated with specific gene-determined molecular pathways involved in cancer pathogenesis (radiogenomics). All these developments would not only help to personalize oncologic practice but also lead to the development of new imaging biomarkers. AI algorithms in oncoimaging and oncopathology will broadly have the following uses: cancer screening (detection of lesions), characterization and grading of tumors, and clinical decision-making and prognostication. However, AI cannot be a foolproof panacea nor can it supplant the role of humans. It can however be a powerful and useful complement to human insights and deeper understanding. Multiple issues like standardization, validity, ethics, privacy, finances, legal liability, training, accreditation, etc., need to be overcome before the vast potential of AI in diagnostic oncology can be fully harnessed.

Dynamic alteration in SULmax predicts early pathological tumor response and short-term prognosis in non-small cell lung cancer treated with neoadjuvant immunochemotherapy

Introduction: Biomarkers predicting tumor response to neoadjuvant immunochemotherapy in non-small cell lung cancer (NSCLC) are still lacking despite great efforts. We aimed to assess the effectiveness of the immune PET Response Criteria in Solid Tumors via SULmax (iPERCIST-max) in predicting tumor response to neoadjuvant immunochemotherapy and short-term survival in locally advanced NSCLC. Methods: In this prospective cohort study, we calculated SULmax, SULpeak, metabolic tumor volume (MTV), total lesion glycolysis (TLG) and their dynamic percentage changes in a training cohort. We then investigated the correlation between alterations in these parameters and pathological tumor responses. Subsequently, iPERCIST-max defined by the proportional changes in the SULmax response (△SULmax%) was constructed and internally validated using a time-dependent receiver operating characteristic (ROC) curve and the area under the curve (AUC) value. A prospective cohort from the Sun Yat-Sen University Cancer Center (SYSUCC) was also included for external validation. The relationship between the iPERCIST-max responsiveness and event-free survival in the training cohort was also investigated. Results: Fifty-five patients with NSCLC were included in this study from May 2019 to December 2021. Significant alterations in post-treatment SULmax (p < 0.001), SULpeak (p < 0.001), SULmean (p < 0.001), MTV (p < 0.001), TLG (p < 0.001), and tumor size (p < 0.001) were observed compared to baseline values. Significant differences in SULpeak, SULmax, and SULmean between major pathological response (mPR) and non-mPR statuses were observed. The optimal cutoff values of the SULmax response rate were -70.0% and -88.0% using the X-tile software. The univariate and multivariate binary logistic regression showed that iPERCIST-max is the only significant key predictor for mPR status [OR = 84.0, 95% confidence interval (CI): 7.84-900.12, p < 0.001]. The AUC value for iPERCIST-max was 0.896 (95% CI: 0.776-1.000, p < 0.001). Further, external validation showed that the AUC value for iPERCIST-max in the SYSUCC cohort was 0.889 (95% CI: 0.698-1.000, p = 0.05). Significantly better event-free survival (EFS) in iPERCIST-max responsive disease (31.5 months, 95% CI 27.9-35.1) than that in iPERCIST-max unresponsive disease (22.2 months, 95% CI: 17.3-27.1 months, p = 0.024) was observed. Conclusion: iPERCIST-max could better predict both early pathological tumor response and short-term prognosis of NSCLC treated with neoadjuvant immunochemotherapy than commonly used criteria. Furthermore, large-scale prospective studies are required to confirm the generalizability of our findings.

Pseudoprogression in lung cancer patients treated with immunotherapy

Lung cancer has attracted much attention because of its high morbidity and mortality worldwide. The advent of immunotherapy approaches, especially the application of immune checkpoint inhibitors (ICIs) has dramatically changed the treatment of lung cancer, but a novel and unexpected pattern of treatment response-- pseudoprogression, has been observed simultaneously which complicates the routine clinical evaluation and management. However, manifestations of pseudoprogression vary and there are many disputes on immune-related response assessment and corresponding treatments for lung cancer. Therefore, we summarized the possible mechanisms, clinical manifestations and corresponding treatment measures of pseudoprogression in lung cancer, as well as potential methods to differentiate pseudoprogression from true tumor progression.

A Novel Approach Using FDG-PET/CT-Based Radiomics to Assess Tumor Immune Phenotypes in Patients With Non-Small Cell Lung Cancer

PURPOSE

Tumor microenvironment immune types (TMITs) are closely related to the efficacy of immunotherapy. We aimed to assess the predictive ability of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT)-based radiomics of TMITs in treatment-naive patients with non-small cell lung cancer (NSCLC).

METHODS

A retrospective analysis was performed in 103 patients with NSCLC who underwent 18F-FDG PET/CT scans. The patients were randomly assigned into a training set (n = 71) and a validation set (n = 32). Tumor specimens were analyzed by immunohistochemistry for the expression of programmed death-ligand 1 (PD-L1), programmed death-1 (PD-1), and CD8+ tumor-infiltrating lymphocytes (TILs) and categorized into four TMITs according to their expression of PD-L1 and CD8+ TILs. LIFEx package was used to extract radiomic features. The optimal features were selected using the least absolute shrinkage and selection operator (LASSO) algorithm, and a radiomics signature score (rad-score) was developed. We constructed a combined model based on the clinical variables and radiomics signature and compared the predictive performance of models using receiver operating characteristic (ROC) curves.

RESULTS

Four radiomic features (GLRLM_LRHGE, GLZLM_SZE, SUVmax, NGLDM_Contrast) were selected to build the rad-score. The rad-score showed a significant ability to discriminate between TMITs in both sets (p < 0.001, p < 0.019), with an area under the ROC curve (AUC) of 0.800 [95% CI (0.688-0.885)] in the training set and that of 0.794 [95% CI (0.615-0.916)] in the validation set, while the AUC values of clinical variables were 0.738 and 0.699, respectively. When clinical variables and radiomics signature were combined, the complex model showed better performance in predicting TMIT-I tumors, with the AUC values increased to 0.838 [95% CI (0.731-0.914)] in the training set and 0.811 [95% CI (0.634-0.927)] in the validation set.

CONCLUSION

The FDG-PET/CT-based radiomic features showed good performance in predicting TMIT-I tumors in NSCLC, providing a promising approach for the choice of immunotherapy in a clinical setting.

Immunotherapy Monitoring with Immune Checkpoint Inhibitors Based on [18F]FDG PET/CT in Metastatic Melanomas and Lung Cancer

Immunotherapy with checkpoint inhibitors has prompted a major change not only in cancer treatment but also in medical imaging. In parallel with the implementation of new drugs modulating the immune system, new response criteria have been developed, aiming to overcome clinical drawbacks related to the new, unusual, patterns of response characterizing both solid tumors and lymphoma during the course of immunotherapy. The acknowledgement of pseudo-progression, hyper-progression, immune-dissociated response and so forth, has become mandatory for all imagers dealing with this clinical scenario. A long list of acronyms, i.e., irRC, iRECIST, irRECIST, imRECIST, PECRIT, PERCIMT, imPERCIST, iPERCIST, depicts the enormous effort made by radiology and nuclear medicine physicians in the last decade to optimize imaging parameters for better prediction of clinical benefit in immunotherapy regimens. Quite frequently, a combination of clinical-laboratory data with imaging findings has been tested, proving the ability to stratify patients into various risk groups. The next steps necessarily require a large scale validation of the most robust criteria, as well as the clinical implementation of immune-targeting tracers for immuno-PET or the exploitation of radiomics and artificial intelligence as complementary tools during the course of immunotherapy administration. For the present review article, a summary of PET/CT role for immunotherapy monitoring will be provided. By scrolling into various cancer types and applied response criteria, the reader will obtain necessary information for better understanding the potentials and limitations of the modality in the clinical setting.

NSCLC Biomarkers to Predict Response to Immunotherapy with Checkpoint Inhibitors (ICI): From the Cells to In Vivo Images

Lung cancer remains the leading cause of cancer-related death, and it is usually diagnosed in advanced stages (stage III or IV). Recently, the availability of targeted strategies and of immunotherapy with checkpoint inhibitors (ICI) has favorably changed patient prognosis. Treatment outcome is closely related to tumor biology and interaction with the tumor immune microenvironment (TME). While the response in molecular targeted therapies relies on the presence of specific genetic alterations in tumor cells, accurate ICI biomarkers of response are lacking, and clinical outcome likely depends on multiple factors that are both host and tumor-related. This paper is an overview of the ongoing research on predictive factors both from in vitro/ex vivo analysis (ranging from conventional pathology to molecular biology) and in vivo analysis, where molecular imaging is showing an exponential growth and use due to technological advancements and to the new bioinformatics approaches applied to image analyses that allow the recovery of specific features in specific tumor subclones.

A narrative review of primary research endpoints of neoadjuvant therapy for lung cancer: past, present and future

Objective

This review summarizes the current status of neoadjuvant therapy and discusses the choice of new clinical research endpoints for non-small cell lung cancer.

Background

Neoadjuvant chemotherapy is a recognized practice in patients with resectable and locally advanced lung cancer. With the introduction of molecular targeted drugs and immune checkpoint inhibitors (ICIs), the overall survival (OS) of patients with lung cancer has been significantly improved, and the original traditional clinical research endpoints are no longer suitable for existing clinical research. In order to accelerate the process of clinical trials and the development and approval of drugs, it is necessary to find suitable alternative indicators as the main indicators of clinical research.

Methods

Therefore, this article focuses on clinical trials using disease-free survival (DFS), progression free survival, and pathological evaluation indicators, pathologic complete response and major pathologic response, as surrogate endpoints. We search related literature through PubMed database and clinical trials through clinicaltrials.gov.

Conclusions

Pathologic complete response and major pathologic response are recommended as surrogate endpoints in the era of neoadjuvant immunotherapy, and secondary endpoints are listed for the prediction of pathological results. In addition, the definitions of major pathological response (MPR) and PCR should be standardized, and a new pathological evaluation standard should be developed, which is applicable to all current treatment methods.

Keywords

Neoadjuvant therapy; resectable lung cancer; clinical research endpoint; pathological response.

First Comparison between [18f]-FMISO and [18f]-Faza for Preoperative Pet Imaging of Hypoxia in Lung Cancer

Simple Summary

The definition of the tumor hypoxia is important in oncology because this characteristic is linked to a poor prognosis. In this context, we compared two hypoxia tracers, FMISO and FAZA, before surgery for lung cancer. Hypoxia tracers correlate well with each other and FMISO is superior to FAZA in defining the hypoxia volume of lung cancers. However, there is no correlation with immunohistochemical findings (GLUT-1, CAIX, LDH-5, and HIF1-Alpha).

Abstract

Hypoxic areas are typically resistant to treatment. However, the fluorine-18-fluoroazomycin-arabinoside (FAZA) and fluorine 18 misonidazole (FMISO) tracers have never been compared in non small cell lung cancer (NSCLC). This study compares the capability of 18F-FAZA PET/CT with that of 18F-FMISO PET/CT for detecting hypoxic tumour regions in early and locally advanced NSCLC patients. We prospectively evaluated patients who underwent preoperative PET scans before surgery for localised NSCLC (i.e., fluorodeoxyglucose (FDG)-PET, FMISO-PET, and FAZA-PET). The PET data of the three tracers were compared with each other and then compared to immunohistochemical analysis (GLUT-1, CAIX, LDH-5, and HIF1-Alpha) after tumour resection. Overall, 19 patients with a mean age of 68.2 ± 8 years were included. There were 18 lesions with significant uptake (i.e., SUVmax >1.4) for the F-MISO and 17 for FAZA. The mean SUVmax was 3 (±1.4) with a mean volume of 25.8 cc (±25.8) for FMISO and 2.2 (±0.7) with a mean volume of 13.06 cc (±13.76) for FAZA. The SUVmax of F-MISO was greater than that of FAZA (p = 0.0003). The SUVmax of F-MISO shows a good correlation with that of FAZA at 0.86 (0.66–0.94). Immunohistochemical results are not correlated to hypoxia PET regardless of the staining. The two tracers show a good correlation with hypoxia, with FMISO being superior to FAZA. FMISO, therefore, remains the reference tracer for defining hypoxic volumes.

Primary metabolic tumor volume from 18F-FDG PET/CT associated with epidermal growth factor receptor mutation in lung adenocarcinoma patients

PURPOSE

To explore the potential parameters from F-FDG PET/CT that might be associated with the epidermal growth factor receptor (EGFR) gene mutation status in lung adenocarcinoma (ADC) patients.

METHODS

Data of the test cohort of 191 patients and the validation cohort of 55 patients with newly diagnosed ADC were retrospectively reviewed. All patients underwent F-FDG PET/CT scans and EGFR mutation tests prior to treatment. The metabolic parameters obtained from F-FDG PET/CT combining with clinical characteristics were analyzed by using univariate and multivariate logistic regression analyses. Then two cohorts were enrolled to validate the predictive model by area under the receiver-operating characteristic curve (AUC), respectively.

RESULTS

EGFR mutation-positive was seen of 33.0% (63/191) and 32.7% (18/55) in two cohorts, respectively. In univariate analysis, female, nonsmokers, metabolic parameters of primary tumor [mean standardized uptake value, metabolic tumor volume (pMTV), and total lesion glycolysis], non-necrosis of primary tumor, and serum tumor markers [carbohydrate antigen 19-9, squamous cell carcinoma antigen, and precursor of gastrin releasing peptide (proGRP)] were significantly relevant with EGFR mutation. In multivariate analysis with adjustment of age and TNM stage, pMTV (<8.13 cm), proGRP (≥38.44 pg/ml) and women were independent significant predictors for EGFR mutation. The AUC for the predictive value of these factors was 0.739 [95% confidence interval (CI) 0.665-0.813] in the cohort of 191 patients and 0.716 (95% CI 0.567-0.865) in the cohort of 55 patients, respectively.

CONCLUSION

Low pMTV (<8.13 cm) was an independent predictor and could be integrated with women and high proGRP (≥38.44 pg/ml) to enhance the discriminability on the EGFR mutation status in ADC patients.

Correlation Between 18F-FDG Uptake and Immune Cell Infiltration in Metastatic Brain Lesions

Background

The purpose of this study was to investigate the correlation between ¹⁸F-fluorodeoxyglucose (FDG) uptake and infiltrating immune cells in metastatic brain lesions.

Methods

This retrospective study included 34 patients with metastatic brain lesions who underwent brain ¹⁸F-FDG positron emission tomography (PET)/computed tomography (CT) followed by surgery. ¹⁸F-FDG uptake ratio was calculated by dividing the standardized uptake value (SUV) of the metastatic brain lesion by the contralateral normal white matter uptake value. We investigated the clinicopathological characteristics of the patients and analyzed the correlation between ¹⁸F-FDG uptake and infiltration of various immune cells. In addition, we evaluated immune-expression levels of glucose transporter 1 (GLUT1), hexokinase 2 (HK2), and Ki-67 in metastatic brain lesions.

Results

The degree of ¹⁸F-FDG uptake of metastatic brain lesions was not significantly correlated with clinical parameters. There was no significant relationship between the ¹⁸F-FDG uptake and degree of immune cell infiltration in brain metastasis. Furthermore, other markers, such as GLUT1, HK2, and Ki-67, were not correlated with degree of ¹⁸F-FDG uptake. In metastatic brain lesions that originated from breast cancer, a higher degree of ¹⁸F-FDG uptake was observed in those with high expression of CD68.

Conclusions

In metastatic brain lesions, the degree of ¹⁸F-FDG uptake was not significantly associated with infiltration of immune cells. The ¹⁸F-FDG uptake of metastatic brain lesions from breast cancer, however, might be associated with macrophage activity.

The Role of the Immune Metabolic Prognostic Index in Patients with Non-Small Cell Lung Cancer (NSCLC) in Radiological Progression during Treatment with Nivolumab

Simple Summary

Identifying reliable prognostic biomarkers of progression in the early phases of treatment is crucial in patients undergoing immune checkpoints inhibitors (ICI) administration for advanced non-small cell lung cancer (NSCLC). With this aim, in this study we combined the prognostic power of the degree of systemic inflammation (depicted by peripheral inflammation indexes), the quantification of the metabolically active tumor burden (estimated using 18F-fluorodeoxyglucose positron emission tomography/computed tomography) as well as their combination in NSCLC patients receiving immune checkpoints inhibitors. This combined approach could be used to improve the risk stratification and the subsequent clinical management in NSCLC patients treated with immune checkpoints inhibitors.

Abstract

An emerging clinical need is represented by identifying reliable biomarkers able to discriminate between responders and non-responders among patients showing imaging progression during the administration of immune checkpoints inhibitors for advanced non-small cell lung cancer (NSCLC). In the present study, we analyzed the prognostic power of peripheral-blood systemic inflammation indexes and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) in this clinical setting. In 45 patients showing radiological progression (defined as RECIST 1.1 progressive disease) during Nivolumab administration, the following lab and imaging parameters were collected: neutrophil-to-lymphocyte ratio (NLR), derived-NLR (dNLR), lymphocyte-to-monocyte ratio (LMR), platelets-to-lymphocyte ratio (PLR), systemic inflammation index (SII), maximum standardized uptake value, metabolic tumor volume (MTV), and total lesion glycolysis (TLG). MTV and SII independently predicted OS. Their combination in the immune metabolic prognostic index (IMPI) allowed the identification of patients who might benefit from immunotherapy continuation, despite radiological progression. The combination of FDG PET/CT volumetric data with SII also approximates the immune-metabolic response with respect to baseline, providing additional independent prognostic insights. In conclusion, the degree of systemic inflammation, the quantification of the metabolically active tumor burden, and their combination might disclose the radiological progression in NSCLC patients receiving Nivolumab.

Response Prediction and Evaluation Using PET in Patients with Solid Tumors Treated with Immunotherapy

Simple Summary

In cancer treatment, immunotherapy is increasingly becoming important as a component of first-line treatment and has improved the prognosis of patients since its introduction. A large group of patients, however, do not respond to immunotherapy, and predicting a treatment response remains challenging. Furthermore, evaluating a response using conventional computed tomography (CT) scans is not straightforward due to the different mechanism of action of immunotherapy compared to chemotherapy. This review provides an overview of positron emission tomography (PET) in predicting and evaluating treatment response to immunotherapy.

Abstract

In multiple malignancies, checkpoint inhibitor therapy has an established role in the first-line treatment setting. However, only a subset of patients benefit from checkpoint inhibition, and as a result, the field of biomarker research is active. Molecular imaging with the use of positron emission tomography (PET) is one of the biomarkers that is being studied. PET tracers such as conventional ¹⁸F-FDG but also PD-(L)1 directed tracers are being evaluated for their predictive power. Furthermore, the use of artificial intelligence is under evaluation for the purpose of response prediction. Response evaluation during checkpoint inhibitor therapy can be challenging due to the different response patterns that can be observed compared to traditional chemotherapy. The additional information provided by PET can potentially be of value to evaluate a response early after the start of treatment and provide the clinician with important information about the efficacy of immunotherapy. Furthermore, the use of PET to stratify between patients with a complete response and those with a residual disease can potentially guide clinicians to identify patients for which immunotherapy can be discontinued and patients for whom the treatment needs to be escalated. This review provides an overview of the use of positron emission tomography (PET) to predict and evaluate treatment response to immunotherapy.

Non-invasive measurement of PD-L1 status and prediction of immunotherapy response using deep learning of PET/CT images

BACKGROUND

Currently, only a fraction of patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) experience a durable clinical benefit (DCB). According to NCCN guidelines, Programmed death-ligand 1 (PD-L1) expression status determined by immunohistochemistry (IHC) of biopsies is the only clinically approved companion biomarker to trigger the use of ICI therapy. Based on prior work showing a relationship between quantitative imaging and gene expression, we hypothesize that quantitative imaging (radiomics) can provide an alternative surrogate for PD-L1 expression status in clinical decision support.

METHODS

¹⁸F-FDG-PET/CT images and clinical data were curated from 697 patients with NSCLC from three institutions and these were analyzed using a small-residual-convolutional-network (SResCNN) to develop a deeply learned score (DLS) to predict the PD-L1 expression status. This developed model was further used to predict DCB, progression-free survival (PFS), and overall survival (OS) in two retrospective and one prospective test cohorts of ICI-treated patients with advanced stage NSCLC.

RESULTS

The PD-L1 DLS significantly discriminated between PD-L1 positive and negative patients (area under receiver operating characteristics curve ≥0.82 in the training, validation, and two external test cohorts). Importantly, the DLS was indistinguishable from IHC-derived PD-L1 status in predicting PFS and OS, suggesting the utility of DLS as a surrogate for IHC. A score generated by combining the DLS with clinical characteristics was able to accurately (C-indexes of 0.70-0.87) predict DCB, PFS, and OS in retrospective training, prospective testing and external validation cohorts.

CONCLUSION

Hence, we propose DLS as a surrogate or substitute for IHC-determined PD-L1 measurement to guide individual pretherapy decisions pending in larger prospective trials.

Prognostic value of PET parameters in patients with pleomorphic lung cancer: Results from a single institution

OBJECTIVES

Pleomorphic lung carcinoma (PLC) is a rare histotype of non-small cell lung cancer (NSCLC) characterized by aggressive clinical course, poor response to therapy and poor prognosis. Therefore, aim of our study is to analyze with 18F-FDG PET/CT a subset of patients affected by PLC to evaluate their metabolic characteristics in terms of SUVmax, MTV and TLG, in order to correlate them with overall survival (OS) and disease-free survival (DFS).

MATERIAL AND METHODS

We retrospectively analyzed 49 consecutive patients with histologically defined PLC occurred to our Institution between 2003 and 2014. All patients underwent F18-FDG PET-CT before surgery and primary tumor was automatically segmented using an isocontour threshold method. SUV threshold for tumor segmentation was defined as the 41 % of lesion SUVmax. Total volume of the segmented VOI (MTV, centimeters cubed) and average SUV (SUVavg, grams per milliliter) in the segmented VOI were measured.

RESULTS

In our population men were significantly more affected than women (42:7). According to Youden criteria, SUVmax, MTV41 and TLG41 best cut-off values to predict 2-year mortality were, 18.95, 27.89 and 290.45, respectively, with TLG41 showing best specificity (85 %) and positive predictive value (82.4 %). As concerning 2-year recurrence, SUVmax, MTV41 and TLG41 best cut-off values were 10.08, 27.89 and 134.85, with SUVmax showing best sensitivity (96.7 %) and negative predictive value (85.7 %). ROC curves confirmed that SUVmax, MTV41 and TLG41 were equally accurate to predict 2-year mortality and 2-year recurrence in our population.

CONCLUSION

Metabolic biomarkers such as SUVmax, MTV and TLG can be used as a prognostic index for disease progression, recurrence and death in patients with PLC, independently from other clinical/pathological prognostic elements.

Prognostic Significance of SUVmax Combined With Lactate Dehydrogenase in Advanced Lung Cancer Patients Treated With Immune Checkpoint Inhibitor Plus Chemotherapy: A Retrospective Study

Purpose

This research aims to investigate the predictive capacity of PET/CT quantitative parameters combined with haematological parameters in advanced lung cancer patients treated with immune checkpoint inhibitor (ICI) plus chemotherapy.

Methods

A total of 120 patients who underwent ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) were enrolled before therapy. The following parameters were calculated: the maximum, mean, and peak standardized uptake value (SUVmax, SUVmean, and SUVpeak, respectively); total tumour volume (MTV) and total lesion glycolysis (TLG); and whole-body metabolic values (MTVwb, TLGwb, SUVmeanwb, and SUVmaxwb). Lactate dehydrogenase (LDH) levels, absolute neutrophil count, absolute platelet count, albumin levels and derived neutrophil to lymphocyte ratio (dNLR) were also computed. The associations between the variables and therapy outcome (evaluated by iRECIST) were analyzed.

Results

Based on iRECIST, 32 of 120 patients showed iPD, 43 iSD, 36 iPR and 9 iCR. Multivariate analysis found that SUVmax, MTVwb, LDH and absolute platelet count were associated with treatment response (P =0.015, P =0.005, P <0.001 and P =0.015, respectively). Kaplan-Meier survival analyses showed that SUVmax ≥11.42 and LDH ≥245 U/L were associated with shorter OS (P = 0.001 and P = 0.004, respectively). Multivariate Cox regression revealed that SUVmax and LDH alone were not correlated with survival prognosis (p>0.05), but the combination of SUVmax and LDH was independently associated with OS (P=0.015, P=0.001, respectively). The median survival time (MST) for the low (LDH<245 and SUVmax<11.42), intermediate(LDH<245 or SUVmax<11.42), and high(SUVmax≥11.42 and LDH≥245) groups was 24.10 months (95% CI: 19.43 to 28.77), 17.41 months (95% CI: 15.83 to 18.99), and 13.76 months (95% CI: 12.51 to 15.02), respectively.

Conclusion

This study identified that SUVmax plus LDH correlated with the survival outcome in patients with advanced lung cancer receiving PD-1/PD-L1 blockade plus chemotherapy.

Noninvasive evaluation of tumor immune microenvironment in patients with clear cell renal cell carcinoma using metabolic parameter from preoperative 2-[18F]FDG PET/CT

PURPOSE

Nowadays, it is necessary to explore effective biomarkers associated with tumor immune microenvironment (TIME) noninvasively. Here, we investigated whether the metabolic parameter from preoperative 2-[¹⁸F]FDG PET/CT could provide information related to TIME in patients with clear cell renal cell carcinoma (ccRCC).

METHODS

Ninety patients with newly diagnosed ccRCC who underwent 2-[¹⁸F]FDG PET/CT prior to surgery were retrospectively reviewed. The immunological features included tumor-infiltrating lymphocytes (TILs) density, programmed death-ligand 1 (PD-L1) expression, and tumor immune microenvironment types (TIMTs). TIMTs were classified as TIMT I (positive PD-L1 and high TILs), TIMT II (negative PD-L1 and low TILs), TIMT III (positive PD-L1 and low TILs), and TIMT IV (negative PD-L1 and high TILs). The relationship between maximum standardized uptake value (SUVmax) in the primary lesion from 2-[¹⁸F]FDG PET/CT and immunological features was analyzed. Cox proportional hazards analyses were performed to identify the prognostic factors for disease-free survival (DFS) after nephrectomy.

RESULTS

Tumors with high TILs infiltration showed remarkable correlation with elevated SUVmax and aggressive clinicopathological characteristics, such as high World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade. PD-L1 expression on tumor cells was positively associated with WHO/ISUP grade and negatively correlated with body mass index (BMI). However, no correlation was observed between SUVmax and PD-L1 expression, regardless of its spatial tissue distribution. SUVmax of TIMT I and IV was higher than that of TIMT II, but there was remarkable difference merely between TIMT II and IV. In multivariate analysis, SUVmax (P = 0.022, HR 3.120, 95% CI 1.175-8.284) and WHO/ISUP grade (P = 0.046, HR 2.613, 95% CI 1.017-6.710) were the significant prognostic factors for DFS. Six cases (16.2%) with normal SUVmax showed disease progression, while 25 cases (71.4%) with elevated SUVmax experienced disease progression. Conversely, the immunological features held no prognostic value.

CONCLUSIONS

Our findings demonstrated that 2-[¹⁸F]FDG PET/CT could provide metabolic information of TIME for ccRCC patients and develop image-guided therapeutic strategies accordingly. Patients with elevated preoperative SUVmax should be seriously considered, and perioperative immunotherapy might be beneficial for them.

Radiomic biomarkers of tumor immune biology and immunotherapy response

Immunotherapies are leading to improved outcomes for many cancers, including those with devastating prognoses. As therapies like immune checkpoint inhibitors (ICI) become a mainstay in treatment regimens, many concurrent challenges have arisen - for instance, delineating clinical responders from non-responders. Predicting response has proven to be difficult given a lack of consistent and accurate biomarkers, heterogeneity of the tumor microenvironment (TME), and a poor understanding of resistance mechanisms. For the most part, imaging data have remained an untapped, yet abundant, resource to address these challenges. In recent years, quantitative image analyses have highlighted the utility of medical imaging in predicting tumor phenotypes, prognosis, and therapeutic response. These studies have been fueled by an explosion of resources in high-throughput mining of image features (i.e. radiomics) and artificial intelligence. In this review, we highlight current progress in radiomics to understand tumor immune biology and predict clinical responses to immunotherapies. We also discuss limitations in these studies and future directions for the field, particularly if high-dimensional imaging data are to play a larger role in precision medicine.

The Value of 18F-FDG PET/CT in Predicting the Response to PD-1 Blocking Immunotherapy in Advanced NSCLC Patients with High-Level PD-L1 Expression

BACKGROUND

The objective of this study was to evaluate if ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT)-derived parameters are useful in predicting response and survival after programmed cell death protein 1 (PD-1) blocking immunotherapy in patients with advanced NSCLC characterized by a high programmed death-ligand 1 (PD-L1) expression (≥50%) on immunohistochemistry.

PATIENTS AND METHODS

In 30 patients with advanced stage IV non-small-cell lung cancer (NSCLC) and high PD-L1 expression, ¹⁸F-FDG PET/CT parameters before start of treatment with PD-1 blocking immunotherapy were evaluated retrospectively. In 24 out of the 30 patients, ¹⁸F-FDG PET/CT was available 8 to 9 weeks after start of the treatment. Response Evaluation Criteria in Solid Tumors (RECIST 1.1) and metabolic responses assessed on ¹⁸F-FDG PET/CT were compared.

RESULTS

Median follow-up was 20 months (range, 4.2-37.6). Median PD-L1 expression was 80%. The objective response rate with RECIST 1.1 was 53.3%. Median progression-free survival (PFS) was 12.4 months (95% confidence interval [CI], 1.0-37.8), and median overall survival (OS) was 14.9 months (95% CI, 2.4-38.2). Baseline ¹⁸F-FDG PET/CT parameters did not differ between responders and non-responders (all P > .05). The maximum standardized uptake value (SUVmax) was the only ¹⁸F-FDG PET/CT parameter associated with PFS (P = .04), with a trend for OS (P = .06). At first evaluation, response according to total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) were associated with PFS and OS (both P < .0001). This was not the case for RECIST 1.1 (P = .29 for PFS and P = .38 for OS).

CONCLUSION

Clinical response and survival were independent from metabolic tumor volume at baseline. Reduction of metabolic tumor volume after 8 to 9 weeks of treatment was a better predictor for prolonged survival than RECIST 1.1.