Tertiary lymphoid structures combined with biomarkers of inflammation are associated with the efficacy of neoadjuvant immunochemotherapy in resectable non-small cell lung cancer: A retrospective study.

BACKGROUND: Neoadjuvant immunochemotherapy can effectively downstage tumors and reduce the risk of postoperative recurrence and distant metastasis in patients with non-small cell lung cancer (NSCLC). In this study, we investigated the correlation between inflammatory biomarkers and tertiary lymphoid structure (TLS) expression. We also compared the predictive values of these inflammatory parameters, TLSs, and a combination of inflammatory parameters and TLSs for neoadjuvant efficacy in patients with NSCLC. METHODS: We retrospectively analyzed the clinical information of 106 patients with NSCLC who underwent neoadjuvant immunochemotherapy and radical surgery at Shandong Cancer Hospital between June 2020 and June 2022. RESULTS: TLS was evaluated using hematoxylin-eosin staining and immunohistochemically-stained tissue sections. Logistic analysis was performed to determine the correlation between inflammatory parameters, TLSs, and the factors affecting major pathological response (MPR). Receiver operating characteristic curves and the C-index were used to evaluate the predictive value of the nomogram models for MPR. The systemic immune-inflammatory index (SII) was an independent predictor of high TLS abundance and maturity. Platelet-to-lymphocyte ratio (PLR) ≤201.8, TLS abundance, and TLS maturity were independent predictors of MPR. The PLR-TLS combined model performed better in assessing the MPR in patients with NSCLC than models using single indicators. CONCLUSION: Our study demonstrated that the SII is an independent predictor of both TLS abundance and maturity. Both TLSs and PLR can predict MPR rates in patients with NSCLC receiving neoadjuvant immunochemotherapy. However, assessing the MPR in patients with NSCLC using a combination of PLR and TLSs is more accurate than using either indicator alone.

Combined inflammatory parameters and tertiary lymphoid structure predict prognosis in patients with resectable non-small cell lung cancer treated with neoadjuvant chemoimmunotherapy.

Introduction: Neoadjuvant chemoimmunotherapy shows great potential for patients with non-small cell lung cancer (NSCLC), but no clear prognostic markers have been identified. This study investigates the correlation between inflammatory parameters and the expression of tertiary lymphoid structures (TLS) and the predictive ability of inflammatory parameters combined with TLS for disease-free survival (DFS) in patients with resectable NSCLC receiving neoadjuvant chemotherapy. Materials and methods: We retrospectively analyzed the clinical data and hematological parameters of 117 patients with NSCLC who underwent neoadjuvant chemoimmunotherapy and radical surgery. TLS were evaluated by observing H&E stained and immunohistochemically stained tissue sections. Univariate chi-square and multifactor logistic analyses were used to determine the correlation between hematological parameters and TLS. The Kaplan-Meier method, univariate and multivariate Cox regression analysis and constructed nomogram models were used to assess the prognostic value of the investigated parameters on DFS. Receiver operating characteristic (ROC) curves analyses were used to compare the performances of the three models. Results: After logistic analysis, it was found that platelet-to-lymphocyte ratio (PLR) ≤288.78 (odds ratio OR=0.122, P=0.009) was an independent predictor of high TLS expression. The Cox regression analyses showed that Histology (HR=0.205, P=0.002), systemic immune inflammation index (SII) (HR=2.758, P=0.042) and TLS (HR=0.057, P<0.05) were independent prognostic factors in patients with NSCLC. The combined SII-TLS model was better than the single-indicator model in assessing the 1-year and 18-months DFS rates in patients with NSCLC. Conclusion: Our study showed that PLR was an independent predictor of TLS and that both TLS and SII predicted prognosis in patients with neoadjuvant chemoimmunotherapy-resectable NSCLC; however, combining SII and TLS to assess DFS was more accurate than using either parameter alone.

Model integrating CT-based radiomics and genomics for survival prediction in esophageal cancer patients receiving definitive chemoradiotherapy.

BACKGROUND: Definitive chemoradiotherapy (dCRT) is a standard treatment option for locally advanced stage inoperable esophageal squamous cell carcinoma (ESCC). Evaluating clinical outcome prior to dCRT remains challenging. This study aimed to investigate the predictive power of computed tomography (CT)-based radiomics combined with genomics for the treatment efficacy of dCRT in ESCC patients. METHODS: This retrospective study included 118 ESCC patients who received dCRT. These patients were randomly divided into training (n = 82) and validation (n = 36) groups. Radiomic features were derived from the region of the primary tumor on CT images. Least absolute shrinkage and selection operator (LASSO) regression was conducted to select optimal radiomic features, and Rad-score was calculated to predict progression-free survival (PFS) in training group. Genomic DNA was extracted from formalin-fixed and paraffin-embedded pre-treatment biopsy tissue. Univariate and multivariate Cox analyses were undertaken to identify predictors of survival for model development. The area under the receiver operating characteristic curve (AUC) and C-index were used to evaluate the predictive performance and discriminatory ability of the prediction models, respectively. RESULTS: The Rad-score was constructed from six radiomic features to predict PFS. Multivariate analysis demonstrated that the Rad-score and homologous recombination repair (HRR) pathway alterations were independent prognostic factors correlating with PFS. The C-index for the integrated model combining radiomics and genomics was better than that of the radiomics or genomics models in the training group (0.616 vs. 0.587 or 0.557) and the validation group (0.649 vs. 0.625 or 0.586). CONCLUSION: The Rad-score and HRR pathway alterations could predict PFS after dCRT for patients with ESCC, with the combined radiomics and genomics model demonstrating the best predictive efficacy.

Homeobox A1 Facilitates Immune Escape and Alleviates Oxidative Stress in Lung Adenocarcinoma.

Objective: Recent studies have demonstrated that homeobox A1 (HOXA1) is upregulated in lung cancer due to RNA modifications (N6-methyladenosine), but the specific function of HOXA1 in lung adenocarcinoma (LUAD) remains indistinct. Herein, we investigated the role of HOXA1 in LUAD biology. Methods: This study presented pancancer analysis of associations of HOXA1 with prognosis, TMB, and immune checkpoints. The expression of HOXA1 was detected in LUAD and normal tissues with immunohistochemistry and western blot. Through least absolute shrinkage and selection operator (LASSO) analysis, HOXA1-derived gene model was conducted in LUAD. Correlations of HOXA1 with immune cell infiltrations, immune checkpoints, HLAs, and chemotherapeutic sensitivity were evaluated. Colony formation, proliferation, and migration of LUAD cells with si-HOXA1 transfection were investigated, and the effects of HOXA1 on T cell exhaustion were assessed in vitro. Results: HOXA1 expression was a risk factor of overall survival, disease-specific survival, and progression-free interval of LUAD. HOXA1 exhibited prominent associations with immune cell infiltration, immune checkpoints, and HLAs. HOXA1-derived gene signature reliably and independently predicted LUAD outcomes. Also, high-risk cases presented increased sensitivity to cisplatin, paclitaxel, docetaxel, vinorelbine, and etoposide. HOXA1 knockdown exhibited an inhibitory effect on proliferation and migration abilities of LUAD cells. Silencing HOXA1 weakened the expression of antioxidative stress markers Nrf2/HO-1 and T cell exhaustion marker CD155 in LUAD cells. Moreover, LUAD cells with HOXA1 knockdown enhanced the CD8+ T cell response. Conclusion: Our data support the oncogenic function and prognostic significance of HOXA1 that facilitates immune escape and alleviates oxidative stress of LUAD.

Construction and validation of four-metabolism related-long non-coding RNAs as potential signature in prognosis of colon cancer.

Background: Emerging evidence suggests that metabolism plays important roles in the initiation and progression of colon cancer (CC) and the outcomes of CC patients. Long non-coding RNAs (lncRNA) are key regulators of regulatory molecules linking to a wide variety of cancer cellular functions. This study aims to develop a metabolic lncRNA signature to help better predict prognosis for CC patients. Methods: In the current study, the transcriptome data and clinical data of CC was downloaded from The Cancer Genome Atlas (TCGA). Metabolism-related gene sets were downloaded from the Molecular Signatures Database (MSigDB). Differential lncRNAs related to metabolism was obtained by performing the correlations between differential expression profile of metabolic genes and lncRNAs. To construct a prognostic model of CC based on metabolism-related lncRNAs, we divided patients, whose clinical data were available, into a training set and a validation set at a ratio of 7:3. The prognostic metabolism related-lncRNA signature was established using the training set by univariate and multivariate Cox regression analysis, and the validation set was used to test the capacity of the prognostic model. The correlation between risk score and clinicopathological features, immune function GO and KEGG analysis was investigated using the entire set. Finally, GSEA pathway enrichment analysis was carried out on the entire set samples for the high- and low- risk groups. Results: We identified 604 differential lncRNAs and 252 genes related to metabolism. After univariate and multivariate Cox regression analysis, four lncRNAs were finally identified to build a signature, which was verified the effectiveness by the TCGA validation set. The multivariate Cox regression analysis showed that the risk score, age of diagnosis and T stage were independent prognostic factor for CC patients. It is shown that some immunopathogenesis, GO items and KEGG pathways demonstrated difference between high- and low- risk group. Conclusions: We developed a four-metabolism related-lncRNA signature for prognostic prediction of CC, which may help select high-risk subpopulation patients who require more aggressive therapy or intervention.

Development and validation of novel radiomics-based nomograms for the prediction of EGFR mutations and Ki-67 proliferation index in non-small cell lung cancer.

Background: We developed and validated novel radiomics-based nomograms to identify epidermal growth factor receptor (EGFR) mutations and the Ki-67 proliferation index of non-small cell lung cancer. Methods: We enrolled 132 patients with histologically verified non-small cell lung cancer from four hospital institutions who underwent computed tomography (CT) scans. EGFR mutations and the Ki-67 proliferation index were measured from tumor tissues. A total of 1,287 radiomic features were extracted, and a three-stage feature selection method was implemented to acquire the most valuable radiomic features. Finally, the radiomic scores and nomograms of the two tasks were established and tested. Receiver operating characteristic curves, calibration curves, and decision curves were used to evaluate their prediction performance and clinical utility. Results: In task [1], smoking status and histological type were significantly associated with EGFR mutations. After feature selection, 10 features were used to establish radiomic score, which showed good performance [area under the curve (AUC) =0.800] in the validation cohort. The radiomic nomogram had an AUC of 0.798 (95% CI: 0.664 to 0.931) with a C-index of 0.798 in the validation cohort. In task [2], gender, smoking status, histological type, and stage showed a significant correlation with Ki-67 proliferation index expression. A total of 28 features were selected to develop a radiomic score, with an AUC of 0.820 in the validation cohort. The final nomogram showed an AUC of 0.828 (95% CI: 0.703 to 0.953) with a C-index of 0.828 in the validation cohort. Conclusions: EGFR mutations and Ki-67 proliferation index in non-small cell lung cancer can be predicted efficiently by the novel radiomic scores and nomograms.

CT-Based Hand-crafted Radiomic Signatures Can Predict PD-L1 Expression Levels in Non-small Cell Lung Cancer: a Two-Center Study.

Here, we used pre-treatment CT images to develop and evaluate a radiomic signature that can predict the expression of programmed death ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC). We then verified its predictive performance by cross-referencing its results with clinical characteristics. This two-center retrospective analysis included 125 patients with histologically confirmed NSCLC. A total of 1287 hand-crafted radiomic features were observed from manually determined tumor regions. Valuable features were then selected with a ridge regression-based recursive feature elimination approach. Machine learning-based prediction models were then built from this and compared each other. The final radiomic signature was built using logistic regression in the primary cohort, and then tested in a validation cohort. Finally, we compared the efficacy of the radiomic signature to the clinical model and the radiomic-clinical nomogram. Among the 125 patients, 89 were classified as having PD-L1 positive expression. However, there was no significant difference in PD-L1 expression levels determined by clinical characteristics (P = 0.109-0.955). Upon selecting 9 radiomic features, we found that the logistic regression-based prediction model performed the best (AUC = 0.96, P < 0.001). In the external cohort, our radiomic signature showed an AUC of 0.85, which outperformed both the clinical model (AUC = 0.38, P < 0.001) and the radiomics-nomogram model (AUC = 0.61, P < 0.001). Our CT-based hand-crafted radiomic signature model can effectively predict PD-L1 expression levels, providing a noninvasive means of better understanding PD-L1 expression in patients with NSCLC.

Surgery of primary tumor improves the survival of newly diagnosed metastatic melanoma: a population-based, propensity-matched study.

BACKGROUND: For the melanoma patients who are with the primary tumor and metastatic disease concurrently (the newly diagnosed metastatic patients), the effect of primary tumor surgery on survival has never been discussed. OBJECTIVE: We sought to estimate this effect based on data from the Surveillance, Epidemiology, and End Results database. PATIENTS AND METHODS: We identified patients with newly diagnosed metastatic melanoma from 2004 to 2015. The effect of primary tumor surgery was assessed by using Cox proportional hazard regression modeling and propensity score matching. RESULTS: Eight thousand three hundred and forty-one patients who had been diagnosed with primary melanoma and metastatic disease at the same time were included in this analysis, of whom 2,554 (30.6%) received primary tumor surgery. In multivariable analysis of the unmatched cohort, primary tumor surgery was an independent protective factor of overall survival (HR =0.617, 95% CI 0.565-0.674; P<0.001) and melanoma-specific survival (HR =0.599, 95% CI 0.537-0.668; P<0.001). In the matched cohort, primary tumor surgery was still associated with better overall survival (13 vs 6 months, P<0.001) and melanoma-specific survival (18 vs 6 months, P<0.001). CONCLUSION: Our results reveal the benefit of primary tumor surgery on the survival of patients with newly diagnosed metastatic melanoma and may fill in the gaps of guidelines for this population. IRB: IRB approval is not required because the SEER data are freely accessible.

Relationship Between Clinicopathological Characteristics and PET/CT Uptake in Esophageal Squamous Cell Carcinoma: [18F]Alfatide versus [18F]FDG.

PURPOSE: To assess a novel radiotracer aluminum [18F]fluoride-1,4,7-triazacyclononane-triacetic acid-pegylated dimeric RGD ([18F]ALF-NOTA-PRGD2, denoted as [18F]Alfatide) for positron emission tomography (PET)/X-ray computed tomography (CT) and explore the relationships between clinicopathological characteristics and maximum standard uptake values in primary (SUVP) and metastatic lymph nodes (SUVLN) of patients with esophageal squamous cell carcinoma (ESCC), as verified by pathologic examination and compared with those obtained with 2-deoxy-2-[18F]fluoro-D-glucose ([18F]DG) PET. PROCEDURES: We prospectively enrolled patients with newly diagnosed ESCC who agreed to undergo [18F]Alfatide PET/CT or [18F]FDG PET/CT scans before surgery at Shandong Cancer Hospital from May 2011 to July 2017. SUVs and the pathological tumor-node-metastasis (pTNM) stages of primary tumors and metastatic lymph nodes (LNs) were measured and confirmed pathologically. Immunohistochemical (IHC) staining for integrin αvß3 was performed on tumor samples (both primary tumors and metastatic LNs) collected from nine patients. RESULTS: Of 61 patients who underwent PET/CT scans, 46 then underwent curative surgery and were included in our analysis (n = 21 for [18F]Alfatide PET/CT and n = 25 for [18F]FDG PET/CT). No significant differences in the SUVP on [18F]Alfatide PET/CT or [18F]FDG PET/CT were observed among the cohorts according to gender, pathological stage, T stage, status of LNs, and differentiation (all P > 0.05). The SUVLN differed significantly between the pathological stages and status of LNs both on [18F]Alfatide PET/CT (P = 0.03, 0.003) and [18F]FDG PET/CT (P = 0.001. < 0.001), but not according to gender (P = 0.128, 0.129), T stage (P = 0.791, 0.727), or tumor differentiation (P = 0.049, 0.053). Significant positive correlations were observed between the SUVLN on [18F]Alfatide PET/CT and [18F]FDG PET/CT, and pathological stage (r = 0.52, P = 0.016; r = 0.503, P = 0.01), LN status (r = 0.73, P < 0.001; r = 0.649, P < 0.001), and differentiation (r = 0.509, P < 0.019; r = 0.459, P = 0.021) were observed. No significant differences were found between the relationships of SUVP with SUVLN, length, age, gender, pathological stage, T stage, status of LN, or differentiation, or of SUVLN with length, age, gender, or T stage both on [18F]Alfatide PET/CT and [18F]FDG PET/CT (all P > 0.05). The quantitated expression levels of αvß3 in primary tumors and metastatic LNs were 1.67 ± 1.12 and 3.42 ± 2.93, respectively (P = 0.031). CONCLUSIONS: Our results suggest that SUVLN is influenced by pathological stage, LN status, and differentiation. SUVLN may therefore serve as a new parameter for risk stratification of with ESCC patients. Moreover, [18F]Alfatide PET can provide complementary molecular information about ESCC metastasis.

A Pilot Study of 18F-Alfatide PET/CT Imaging for Detecting Lymph Node Metastases in Patients with Non-Small Cell Lung Cancer.

Angiogenesis plays a key role in tumor development and αvß3 integrin are overexpressed on the endothelial cell surface of newly forming vessels. 18F-Alfatide has favorable properties for αvß3 integrin targeting and showed potential for imaging angiogenesis with Positron Emission Tomography (PET)/computed tomography (CT). In this study, 13 patients with non-small cell lung cancer (NSCLC) who underwent 18F-Alfatide PET/CT before surgery were enrolled. The uptake of all dissected lymph nodes (LNs) of 18F-Alfatide were assessed visually and analyzed with a maximum and mean standard uptake value (SUVmax, SUVmean) and SUV ratios. LN metastases were pathologically confirmed and 20 of 196 LNs were malignant. All malignant LNs were successfully visualized on 18F-Alfatide PET/CT in patients and the sensitivity, specificity and accuracy was 100.0%, 94.9% and 95.4%, respectively. SUVmax, SUVmean and SUV ratios in malignant LNs were significantly higher than in benign LNs for NSCLC patients (P < 0.001). The same result was observed in patients with adenocarcinoma and squamous cell carcinoma (P < 0.001). The 18F-Alfatide parameter shows high sensitivity (83.9-100%), specificity (78.6-96.7%) and accuracy (81.7-96.9%) according to thresholds calculated from receiver operating characteristic curve. Our results suggest that 18F-Alfatide PET/CT is valuable in the diagnosis of metastatic LNs for NSCLC patients.