Invasive Adenocarcinoma Research Articles

Prediction of solid and micropapillary components in lung invasive adenocarcinoma: radiomics analysis from high-spatial-resolution CT data with 1024 matrix

PurposeTo predict solid and micropapillary components in lung invasive adenocarcinoma using radiomic analyses based on high-spatial-resolution CT (HSR-CT).Materials and methodsFor this retrospective study, 64 patients with lung invasive adenocarcinoma were enrolled. All patients were scanned by HSR-CT with 1024 matrix. A pathologist evaluated subtypes (lepidic, acinar, solid, micropapillary, or others). Total 61 radiomic features in the CT images were calculated using our modified texture analysis software, then filtered and minimized by least absolute shrinkage and selection operator (LASSO) regression to select optimal radiomic features for predicting solid and micropapillary components in lung invasive adenocarcinoma. Final data were obtained by repeating tenfold cross-validation 10 times. Two independent radiologists visually predicted solid or micropapillary components on each image of the 64 nodules with and without using the radiomics results. The quantitative values were analyzed with logistic regression models. The receiver operating characteristic curves were generated to predict of solid and micropapillary components. P values < 0.05 were considered significant.ResultsTwo features (Coefficient Variation and Entropy) were independent indicators associated with solid and micropapillary components (odds ratio, 30.5 and 11.4; 95% confidence interval, 5.1–180.5 and 1.9–66.6; and P = 0.0002 and 0.0071, respectively). The area under the curve for predicting solid and micropapillary components was 0.902 (95% confidence interval, 0.802 to 0.962). The radiomics results significantly improved the accuracy and specificity of the prediction of the two radiologists.ConclusionTwo texture features (Coefficient Variation and Entropy) were significant indicators to predict solid and micropapillary components in lung invasive adenocarcinoma.

Machine learning-based exosome profiling of multi-receptor SERS sensors for differentiating adenocarcinoma in situ from early-stage invasive adenocarcinoma

Exosomes, extracellular vesicles released by cells, hold potential as diagnostic markers for the early detection of lung cancer. Despite their clinical promise, current technologies lack rapid and effective means to discriminate between exosomes derived from adenocarcinoma in situ (AIS) and early-stage invasive adenocarcinoma (IAC). This challenge arises from the intrinsic structural heterogeneity of exosomes, necessitating the development of advanced methodologies for precise differentiation. Here, we demonstrate a novel approach for plasma exosome detection utilizing multi-receptor surface-enhanced Raman spectroscopy (SERS) technology to differentiate between AIS and early-stage IAC. To accomplish this, we synthesized a stable and uniform two-dimensional SERS substrate (BC/Au NPs film) by fabricating gold nanoparticles onto bacterial cellulose. We then enhanced its capabilities by introducing multi-receptor SERS functionality via modifying the substrate with both low-specificity and physicochemical-selective molecules. Furthermore, by strategically combining all capturer-exosome SERS spectra, comprehensive “combined-SERS spectra” are reconstructed to enhance spectral variations of the exosome. Combining these features with partial least squares regression-discriminant analysis (PLS-DA) modeling significantly improved discriminatory accuracy, achieving 90% sensitivity and 95% specificity in distinguishing AIS from early-stage IAC. Our developed SERS sensor provides an effective method for early detection of lung cancer, thereby paving a new way for innovative advancements in diagnosing lung cancer.

Prognosis of spread through air spaces in invasive mucinous lung adenocarcinoma after curative surgery

IntroductionThe purpose of this study is to investigate the prognostic impact of spread through air spaces (STAS) in invasive mucinous adenocarcinoma (IMA). Materials and methodsFrom 2015 to 2019, patients who underwent complete resection of IMA were extracted from the prospective database. Multivariable Cox-regression analysis and inverse probability of treatment weight (IPTW) - adjusted log-rank test for 5-year recurrence-free survival (RFS) were performed. ResultsSTAS was observed in 39.1% (53 out of 133). The STAS (+) group shows larger tumor size (2.9 ± 2.4 cm vs 3.8 ± 2.4 cm, p = 0.031) and higher incidence of lympho-vascular invasion (6 [7.5%] vs 18 [34.0%], p < 00.001) compared to the STAS (−) group. The 5-year RFS was 66.1% in the STAS (+) group and 91.8% in the STAS (−) group (p < 00.001), and the incidence of locoregional recurrence was significantly higher in the STAS (+) group than the STAS (−) group (1 [1.2%] vs 12 [22.6%], p < 00.001). Multivariable analysis revealed that STAS was associated with poor prognosis for all-recurrence (hazard ratio 2.81, 95% confidence interval 1.01–7.81, p = 0.048). After IPTW adjustment, 5-year RFS was 66.3% in the STAS (+) group and 92.9% in the STAS (−) group (p = 0.007), and risk for locoregional recurrence was greater in the STAS (+) group than the STAS (−) group (1.1 [0.9%] vs 20.8 [16.6%], p < 00.001). ConclusionsSTAS showed negative prognostic impact on all-recurrence, especially due to locoregional recurrence, after curative resection of IMA.

PARP1-targeted fluorescence molecular endoscopy as novel tool for early detection of esophageal dysplasia and adenocarcinoma

BackgroundEsophageal cancer is one of the 10 most common cancers worldwide and its incidence is dramatically increasing. Despite some improvements, the current surveillance protocol with white light endoscopy and random untargeted biopsies collection (Seattle protocol) fails to diagnose dysplastic and cancerous lesions in up to 50% of patients. Therefore, new endoscopic imaging technologies in combination with tumor-specific molecular probes are needed to improve early detection. Herein, we investigated the use of the fluorescent Poly (ADP-ribose) Polymerase 1 (PARP1)-inhibitor PARPi-FL for early detection of dysplastic lesions in patient-derived organoids and transgenic mouse models, which closely mimic the transformation from non-malignant Barrett’s Esophagus (BE) to invasive esophageal adenocarcinoma (EAC).MethodsWe determined PARP1 expression via immunohistochemistry (IHC) in human biospecimens and mouse tissues. We also assessed PARPi-FL uptake in patient- and mouse-derived organoids. Following intravenous injection of 75 nmol PARPi-FL/mouse in L2-IL1B (n = 4) and L2-IL1B/IL8Tg mice (n = 12), we conducted fluorescence molecular endoscopy (FME) and/or imaged whole excised stomachs to assess PARPi-FL accumulation in dysplastic lesions. L2-IL1B/IL8Tg mice (n = 3) and wild-type (WT) mice (n = 2) without PARPi-FL injection served as controls. The imaging results were validated by confocal microscopy and IHC of excised tissues.ResultsIHC on patient and murine tissue revealed similar patterns of increasing PARP1 expression in presence of dysplasia and cancer. In human and murine organoids, PARPi-FL localized to PARP1-expressing epithelial cell nuclei after 10 min of incubation. Injection of PARPi-FL in transgenic mouse models of BE resulted in the successful detection of lesions via FME, with a mean target-to-background ratio > 2 independently from the disease stage. The localization of PARPi-FL in the lesions was confirmed by imaging of the excised stomachs and confocal microscopy. Without PARPi-FL injection, identification of lesions via FME in transgenic mice was not possible.ConclusionPARPi-FL imaging is a promising approach for clinically needed improved detection of dysplastic and malignant EAC lesions in patients with BE. Since PARPi-FL is currently evaluated in a phase 2 clinical trial for oral cancer detection after topical application, clinical translation for early detection of dysplasia and EAC in BE patients via FME screening appears feasible.

Value of CT Quantitative Parameters in Prediction of Pathological Types of Lung Ground Glass Nodules

The pathological types of lung ground glass nodules (GGNs) show great significance to the clinical treatment. This study was aimed to predict pathological types of GGNs based on computed tomography (CT) quantitative parameters. 389 GGNs confirmed by postoperative pathology were selected, including 138 cases of precursor glandular lesions [atypical adenomatous hyperplasia (AAH) and adenocarcinoma in situ (AIS)], 109 cases of microinvasive adenocarcinoma (MIA) and 142 cases of invasive adenocarcinoma (IAC). The morphological characteristics of nodules were evaluated subjectively by radiologist, as well as artificial intelligence (AI). In the subjective CT signs, the maximum diameter of nodule and the frequency of spiculation, lobulation and pleural traction increased from AAH+AIS, MIA to IAC. In the AI quantitative parameters, parameters related to size and CT value, proportion of solid component, energy and entropy increased from AAH+AIS, MIA to IAC. There was no significant difference between AI quantitative parameters and the subjective CT signs for distinguishing the pathological types of GGNs. AI quantitative parameters were valuable in distinguishing the pathological types of GGNs.

The organ sparing management of a patient with urachus cancer in conditions of comorbidity

Malignant tumors of the urachus are extremely rare. The frequency of urachal malignancy makes 1: 5 000 000 cases, which is 0.35–1.2 % of all the cases of bladder cancer. The small series of observations described in the literature do not allow us to formulate statistically reliable and unambiguously recommended statements about the optimal methods of diagnostics and treatment of this pathology. The diagnosis of urachus diseases is often challenging. This is associated with both the asymptomatic course and the variety of clinical flow of the disease. The treatment strategies are also largely ambiguous and ranging from the defining the indications for surgical treatment to the aggressiveness of surgical intervention. Meanwhile, 20 % of patients with urachal cancer have distant metastases at the time of detection. With everything listed above, (low frequency, little research done and aggressiveness of the flow) it makes every clinical observation of this disease valuable.This article is a clinical observation providing with the information upon the diagnosis, the choice of strategies and surgical treatment of urachal cancer in a patient suffering from multimorbidity. Volumetric formation of the bladder was detected in this patient during additional examination for macrohematuria. Cystoscopy with transurethral resection and subsequent morphological examination verified invasive mucinous adenocarcinoma of the bladder with the growth into the lamina propria and without the signs of vascular and perineural invasion. The patient underwent laparotomy, radical resection of the bladder with extended pelvic lymphadenectomy. The umbilicus, urachus and the bladder wall with the tumor, as well as the adjacent peritoneum, were excised as a single block during the surgical intervention. Morphological examination verified mucinous adenocarcinoma of urachus. The postoperative period was uneventful.There have been no signs of disease progression observed during 10-month follow-up period.

Construction and validation of a predictive model of invasive adenocarcinoma in pure ground-glass nodules less than 2 cm in diameter

ObjectivesIn this study, we aimed to develop a multiparameter prediction model to improve the diagnostic accuracy of invasive adenocarcinoma in pulmonary pure glass nodules.MethodWe included patients with pulmonary pure glass nodules who underwent lung resection and had a clear pathology between January 2020 and January 2022 at the Qilu Hospital of Shandong University. We collected data on the clinical characteristics of the patients as well as their preoperative biomarker results and computed tomography features. Thereafter, we performed univariate and multivariate logistic regression analyses to identify independent risk factors, which were then used to develop a prediction model and nomogram. We then evaluated the recognition ability of the model via receiver operating characteristic (ROC) curve analysis and assessed its calibration ability using the Hosmer-Lemeshow test and calibration curves. Further, to assess the clinical utility of the nomogram, we performed decision curve analysis.ResultWe included 563 patients, comprising 174 and 389 cases of invasive and non-invasive adenocarcinoma, respectively, and identified seven independent risk factors, namely, maximum tumor diameter, age, serum amyloid level, pleural effusion sign, bronchial sign, tumor location, and lobulation. The area under the ROC curve was 0.839 (95% CI: 0.798–0.879) for the training cohort and 0.782 (95% CI: 0.706–0.858) for the validation cohort, indicating a relatively high predictive accuracy for the nomogram. Calibration curves for the prediction model also showed good calibration for both cohorts, and decision curve analysis showed that the clinical prediction model has clinical utility.ConclusionThe novel nomogram thus constructed for identifying invasive adenocarcinoma in patients with isolated pulmonary pure glass nodules exhibited excellent discriminatory power, calibration capacity, and clinical utility.

Discovery of novel DNA methylation biomarker panels for the diagnosis and differentiation between common adenocarcinomas and their liver metastases

Differentiation between adenocarcinomas is sometimes challenging. The promising avenue for discovering new biomarkers lies in bioinformatics using DNA methylation analysis. Utilizing a 2853-sample identification dataset and a 782-sample independent verification dataset, we have identified diagnostic DNA methylation biomarkers that are hypermethylated in cancer and differentiate between breast invasive carcinoma, cholangiocarcinoma, colorectal cancer, hepatocellular carcinoma, lung adenocarcinoma, pancreatic adenocarcinoma and stomach adenocarcinoma. The best panels for cancer type exhibit sensitivity of 77.8–95.9%, a specificity of 92.7–97.5% for tumors, a specificity of 91.5–97.7% for tumors and normal tissues and a diagnostic accuracy of 85.3–96.4%. We have shown that the results can be extended from the primary cancers to their liver metastases, as the best panels diagnose and differentiate between pancreatic adenocarcinoma liver metastases and breast invasive carcinoma liver metastases with a sensitivity and specificity of 83.3–100% and a diagnostic accuracy of 86.8–91.9%. Moreover, the panels could detect hypermethylation of selected regions in the cell-free DNA of patients with liver metastases. At the same time, these were unmethylated in the cell-free DNA of healthy donors, confirming their applicability for liquid biopsies.

18 F-FDG PET/CT characteristics of IASLC grade 3 invasive adenocarcinoma and the value of 18 F-FDG PET/CT for preoperative prediction: a new prognostication model.

This study is performed to investigate the imaging characteristics of the International Association for the Study of Lung Cancer grade 3 invasive adenocarcinoma (IAC) on PET/CT and the value of PET/CT for preoperative predicting this tumor. We retrospectively enrolled patients with IAC from August 2015 to September 2022. The clinical characteristics, serum tumor markers, and PET/CT features were analyzed. T test, Mann-Whitney U test, χ 2 test, Logistic regression analysis, and receiver operating characteristic analysis were used to predict grade 3 tumor and evaluate the prediction effectiveness. Grade 3 tumors had a significantly higher maximum standardized uptake value (SUV max ) and consolidation-tumor-ratio (CTR) ( P < 0.001), while Grade 1 - 2 tumors were prone to present with air bronchogram sign or vacuole sign ( P < 0.001). A stepwise logistic regression analysis revealed that smoking history, CEA, SUV max , air bronchogram sign or vacuole sign and CTR were useful predictors for Grade 3 tumors. The established prediction model based on the above 5 parameters generated a high AUC (0.869) and negative predictive value (0.919), respectively. Our study demonstrates that grade 3 IAC has a unique PET/CT imaging feature. The prognostication model established with smoking history, CEA, SUV max , air bronchogram sign or vacuole sign and CTR can effectively predict grade 3 tumors before the operation.

Prognostic factors for invasive mucinous adenocarcinoma of the lung: systematic review and meta-analysis

BackgroundInvasive mucinous adenocarcinoma of the lung (IMA) is a unique and rare subtype of lung adenocarcinoma with poorly defined prognostic factors and highly controversial studies. Hence, this study aimed to comprehensively identify and summarize the prognostic factors associated with IMA.MethodsA comprehensive search of relevant literature was conducted in the PubMed, Embase, Cochrane, and Web of Science databases from their inception until June 2023. The pooled hazard ratio (HR) and corresponding 95% confidence intervals (CI) of overall survival (OS) and/or disease-free survival (DFS) were obtained to evaluate potential prognostic factors.ResultsA total of 1062 patients from 11 studies were included. In univariate analysis, we found that gender, age, TNM stage, smoking history, lymph node metastasis, pleural metastasis, spread through air spaces (STAS), tumor size, pathological grade, computed tomography (CT) findings of consolidative-type morphology, pneumonia type, and well-defined heterogeneous ground-glass opacity (GGO) were risk factors for IMA, and spiculated margin sign was a protective factor. In multivariate analysis, smoking history, lymph node metastasis, pathological grade, STAS, tumor size, and pneumonia type sign were found to be risk factors. There was not enough evidence that epidermal growth factor receptor (EGFR) mutations, anaplastic lymphoma kinase (ALK) mutations, CT signs of lobulated margin, and air bronchogram were related to the prognosis for IMA.ConclusionIn this study, we comprehensively analyzed prognostic factors for invasive mucinous adenocarcinoma of the lung in univariate and multivariate analyses of OS and/or DFS. Finally, 12 risk factors and 1 protective factor were identified. These findings may help guide the clinical management of patients with invasive mucinous adenocarcinoma of the lung.

Discrepancies Between Morphological and Immunohistochemical Classifications Are Associated With Prognoses and Subtypes of Lung Cancer.

Immunohistochemical (IHC) staining has been routinely used to distinguish adenocarcinoma (ADC) and squamous cell carcinoma (SCC) of the lungs; however, it is challenging to obtain an accurate diagnosis, especially for cases with discrepancies between IHC and hematoxylin and eosin (H&E) staining results. This study aimed to clarify the clinicopathological characteristics of these discrepant cases. Tissue microarray specimens from 321 patients with ADC and SCC were used for H&E and IHC staining of thyroid transcription factor 1 (TTF-1), Napsin A, cytokeratin 5/6 (CK5/6), p40, and p63. The pathological diagnosis was made based on (1) H&E, (2) IHC, and (3) both H&E and IHC results. Discrepant cases were defined as those with different diagnoses based on the H&E and IHC results. A total of 32 (10%) discrepant cases were identified. ADC (3.9%) showed fewer discrepant cases than SCC (51%). Discrepant cases of ADC had a significantly higher proportion of poorly differentiated tumors and subtypes of solid and invasive mucinous ADC, and they also had shorter overall and disease-free survival than concordant cases. Solid and invasive mucinous ADC cases showed low positivity for TTF-1 (84% and 40%, respectively) and Napsin A (88% and 80%, respectively), and invasive mucinous ADC cases showed high positivity for CK5/6 (80%). The sensitivity and specificity of TTF-1+Napsin A for ADC were 91% and 83%, respectively, whereas those of CK5/6+p40 for SCC cases were 90% and 96%, respectively. Discrepant cases of ADC are associated with solid and invasive mucinous subtypes and shorter survival.

A combination of radiomic features, clinic characteristics, and serum tumor biomarkers to predict the possibility of the micropapillary/solid component of lung adenocarcinoma.

Invasive lung adenocarcinoma with MPP/SOL components has a poor prognosis and often shows a tendency to recurrence and metastasis. This poor prognosis may require adjustment of treatment strategies. Preoperative identification is essential for decision-making for subsequent treatment. This study aimed to preoperatively predict the probability of MPP/SOL components in lung adenocarcinomas by a comprehensive model that includes radiomics features, clinical characteristics, and serum tumor biomarkers. A retrospective case control, diagnostic accuracy study. This study retrospectively recruited 273 patients (males: females, 130: 143; mean age ± standard deviation, 63.29 ± 10.03 years; range 21-83 years) who underwent resection of invasive lung adenocarcinoma. Sixty-one patients (22.3%) were diagnosed with lung adenocarcinoma with MPP/SOL components. Radiomic features were extracted from CT before surgery. Clinical, radiomic, and combined models were developed using the logistic regression algorithm. The clinical and radiomic signatures were integrated into a nomogram. The diagnostic performance of the models was evaluated using the area under the curve (AUC). Studies were scored according to the Radiomics Quality Score and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines. The radiomics model achieved the best AUC values of 0.858 and 0.822 in the training and test cohort, respectively. Tumor size (T_size), solid tumor size (ST_size), consolidation-to-tumor ratio (CTR), years of smoking, CYFRA 21-1, and squamous cell carcinoma antigen were used to construct the clinical model. The clinical model achieved AUC values of 0.741 and 0.705 in the training and test cohort, respectively. The nomogram showed higher AUCs of 0.894 and 0.843 in the training and test cohort, respectively. This study has developed and validated a combined nomogram, a visual tool that integrates CT radiomics features with clinical indicators and serum tumor biomarkers. This innovative model facilitates the differentiation of micropapillary or solid components within lung adenocarcinoma and achieves a higher AUC, indicating superior predictive accuracy.

Predictive value of metabolism and its heterogeneity parameters measured by preoperative 18 F-FDG PET/CT for mediastinal occult lymph node metastasis in cN0 lung invasive adenocarcinoma.

To explore the potential of intratumoral metabolism and its heterogeneous parameters, as measured by preoperative fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) imaging, to predict mediastinal occult lymph node metastasis in cN0 lung invasive adenocarcinoma. Seventy five patients were consecutively enrolled from January 2018 to December 2022. All patients underwent 18F-FDG PET/CT scans within two weeks before surgery, and had mediastinal lymph node metastasis confirmed by pathologic diagnosis after surgery. Metabolic parameters including the maximum standardized uptake value (SUVmax), mean SUV (SUVmean), maximum average SUV (SUVpeak), tumor metabolic volume (MTV), and metabolic heterogeneity (HF) were measured. The relationship between primary focal metabolism, its heterogeneity parameters, and occult mediastinal lymph node metastasis was analyzed using an independent-sample t-test, analysis of covariance, and Mann-Whitney U test. A multivariate logistic regression model was used to analyze independent risk factors for mediastinal lymph node metastasis, while the receiver operating characteristic (ROC) curve assessed the predictive value of metabolic heterogeneity parameters for mediastinal occult lymph node metastasis. A total of 20 out of 75 patients (26.7%) were pathologically confirmed to have mediastinal lymph node metastasis. Analysis of covariance showed that the SUVmax, SUVmean, SUVpeak and MTV were significantly higher in patients with metastasis than in those without (all P<0.05). The metabolic heterogeneity parameters HF2 and HF3 were significantly higher in patients with mediastinal lymph node metastasis than in those without (P=0.013, 0.001), but not HF1. Multivariate Logistic regression analysis identified that tumor size, SUVmax, SUVpeak, lymph node SUVmax, and HF2 of the primary tumor as independent risk factors for mediastinal lymph node metastasis. Metabolic heterogeneity 3 demonstrated high predictive value for mediastinal occult lymph node metastasis (AUC=0.720, P=0.004). Metabolism and heterogeneity, as measured by preoperative 18F-FDG PET/CT in lung invasive adenocarcinoma, potentially have clinical value for predicting mediastinal occult lymph node metastasis.

Intraductal papillary mucinous neoplasms of the pancreas: Cytologic-histologic correlation study and evaluation of the cytologic accuracy in identifying high-grade dysplasia/invasive adenocarcinoma.

Intraductal papillary mucinous neoplasms (IPMNs) may be associated with invasive adenocarcinoma, low-grade dysplasia (LGD), or high-grade dysplasia (HGD). We aimed to review the cytologic-histologic correlation of cases with a histologic diagnosis of IPMN. A database search (January 2010-January 2021) was performed for resected IPMNs with preceding endoscopic ultrasound-guided fine-needle aspiration (FNA). Cytology slides were reviewed for the presence of benign, atypical, or malignant cells, and necrosis. Histologically, IPMNs were classified as benign (LGD) or malignant (HGD or adenocarcinoma). There were 41 patients with IPMN; 24 malignant and 17 benign. Sixteen of the 24 malignant IPMNs were accurately classified as malignant on cytology. There were eight false negatives and one false positive. Cytology yielded a sensitivity of 67% and a specificity of 94%. Among the 16 true positives with FNA diagnosis of adenocarcinoma, seven were IPMNs with HGD, and nine had invasive adenocarcinomas on histology. Cellular morphology and absence or presence of necrosis did not help distinguish HGD from adenocarcinoma on cytology (P > 0.5). Sampling errors and interpretative errors resulted in false-negative cases. Cytology yielded diagnoses related to IPMN in 73% of cases (30/41) and lack of identification of mucinous cells/mucinous background resulted in interpretative errors (9). This study shows that there is a good correlation between cytopathology and surgical pathology diagnoses of IPMNs and that cytology is mostly able to recognize IPMN with HGD/adenocarcinoma. However, heterogeneity in areas of IPMN with HGD/adenocarcinoma may result in sampling errors yielding false-negative cases. Mucinous cells/background should raise the suspicion of IPMN on cytology, even when no neoplastic epithelium is present for the evaluation of dysplasia.

Nomogram for predicting prognosis and identifying chemotherapy beneficiaries for completely resected stage I invasive mucinous lung adenocarcinoma.

At present, there is a lack of studies in invasive mucinous adenocarcinoma (IMA) that combine clinicopathological and imaging features to stratify risk and select optimal treatment regimen. We aimed to develop and validate a nomogram for predicting recurrence-free survival (RFS) and identifying adjuvant chemotherapy (ACT) beneficiaries for completely resected stage I primary IMA. This retrospective study included 750 patients from three hospitals. Patients from two hospitals were divided into training (n=424) and validating cohort (n=185), and patients from the remaining other one hospital constituted external test cohort (n=141) and preoperative computed tomography (CT) image features of each patient were consecutively evaluated. The nomogram was developed by integrating significant prognostic factors of RFS identified in the multivariate analysis. The risk score (RS) based on nomogram was calculated in the entire cohort and the optimal cut-off point for risk stratification was obtained by X-tile software. The Kaplan-Meier method, log-rank test and interaction were used to evaluate the difference in RFS and overall survival (OS) between different risk and treatment groups. Visceral pleural invasion (VPI, P<0.001), lymph-vascular invasion (LVI, P<0.001), tumor size (P<0.001), smoking history (P<0.001), lobulation (P<0.001) were identified as independent prognostic factors for RFS. The concordance index (C-index) of the nomogram was higher than that of tumor-node-metastasis (TNM) staging system (validation cohort: 0.73±0.09 vs. 0.62±0.08, P<0.001; external test cohort: 0.74±0.10 vs. 0.70±0.09, P=0.035). The patients with higher RS were associated with worse RFS [hazard ratios (HRs) ≥4.76] and OS (HRs ≥2.55) in all included cohorts. Chemotherapy benefits in terms of RFS and OS were observed for patients in higher RS group in both stage IB (interaction P=0.012 for RFS and P=0.037 for OS) and stage I IMA (interaction P<0.001 for both RFS and OS). The nomogram based on CT image and clinicopathologic features showed superior performance in predicting RFS for stage I IMA and might identify ACT candidates for personalized patient treatment.

The role of adenocarcinoma subtypes and immunohistochemistry in predicting lymph node metastasis in early invasive lung adenocarcinoma

BackgroundIdentifying lymph node metastasis areas during surgery for early invasive lung adenocarcinoma remains challenging. The aim of this study was to develop a nomogram mathematical model before the end of surgery for predicting lymph node metastasis in patients with early invasive lung adenocarcinoma.MethodsIn this study, we included patients with invasive lung adenocarcinoma measuring ≤ 2 cm who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University from January 2020 to January 2022. Preoperative biomarker results, clinical features, and computed tomography characteristics were collected. The enrolled patients were randomized into a training cohort and a validation cohort in a 7:3 ratio. The training cohort was used to construct the predictive model, while the validation cohort was used to test the model independently. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. The prediction model and nomogram were established based on the independent risk factors. Recipient operating characteristic (ROC) curves were used to assess the discrimination ability of the model. Calibration capability was assessed using the Hosmer–Lemeshow test and calibration curves. The clinical utility of the nomogram was assessed using decision curve analysis (DCA).ResultsThe overall incidence of lymph node metastasis was 13.23% (61/461). Six indicators were finally determined to be independently associated with lymph node metastasis. These six indicators were: age (P < 0.001), serum amyloid (SA) (P = 0.008); carcinoma antigen 125 (CA125) (P = 0. 042); mucus composition (P = 0.003); novel aspartic proteinase of the pepsin family A (Napsin A) (P = 0.007); and cytokeratin 5/6 (CK5/6) (P = 0.042). The area under the ROC curve (AUC) was 0.843 (95% CI: 0.779–0.908) in the training cohort and 0.838 (95% CI: 0.748–0.927) in the validation cohort. the P-value of the Hosmer–Lemeshow test was 0.0613 in the training cohort and 0.8628 in the validation cohort. the bias of the training cohort corrected C-index was 0.8444 and the bias-corrected C-index for the validation cohort was 0.8375. demonstrating that the prediction model has good discriminative power and good calibration.ConclusionsThe column line graphs created showed excellent discrimination and calibration to predict lymph node status in patients with ≤ 2 cm invasive lung adenocarcinoma. In addition, the predictive model has predictive potential before the end of surgery and can inform clinical decision making.

Proposed novel grading system for stage I invasive lung adenocarcinoma and a comparison with the 2020 IASLC grading system.

Several studies have proposed grading systems for risk stratification of early-stage lung adenocarcinoma based on histological patterns. However, the reproducibility of these systems is poor in clinical practice, indicating the need to develop a new grading system which is easy to apply and has high accuracy in prognostic stratification of patients. Patients with stage I invasive nonmucinous lung adenocarcinoma were retrospectively collected from pathology archives between 2009 and 2016. The patients were divided into a training and validation set at a 6:4 ratio. Histological features associated with patient outcomes (overall survival [OS] and progression-free survival [PFS]) identified in the training set were used to construct a new grading system. The newly proposed system was validated using the validation set. Survival differences between subgroups were assessed using the log-rank test. The prognostic performance of the novel grading system was compared with two previously proposed systems using the concordance index. A total of 539 patients were included in this study. Using a multioutcome decision tree model, four pathological factors, including the presence of tumor spread through air space (STAS) and the percentage of lepidic, micropapillary and solid subtype components, were selected for the proposed grading system. Patients were accordingly classified into three groups: low, medium, and high risk. The high-risk group showed a 5-year OS of 52.4% compared to 89.9% and 97.5% in the medium and low-risk groups, respectively. The 5-year PFS of patients in the high-risk group was 38.1% compared to 61.7% and 90.9% in the medium and low-risk groups, respectively. Similar results were observed in the subgroup analysis. Additionally, our proposed grading system provided superior prognostic stratification compared to the other two systems with a higher concordance index. The newly proposed grading system based on four pathological factors (presence of STAS, and percentage of lepidic, micropapillary, and solid subtypes) exhibits high accuracy and good reproducibility in the prognostic stratification of stage I lung adenocarcinoma patients.

Expression heterogeneity, tumor immune characteristics and the prognosis effects of OPRL1 in patients with tumors: a pan-cancer study combined with bioinformation analyses and in vitro validation

PurposeOpioids are currently the most frequently prescribed analgesics in clinical practice. However, their effect on cancer progression remains a topic of debate. Opioid receptors (ORs) are present in various types of tumor cells and their expression levels vary depending on the type of tumor. This study aims to explore and preliminarily characterize the association between four different ORs (μ, δ, κ, and nociception/orphanin FQ peptide receptor) and the prognosis of different types of tumors for comparison, with a focus on nociception/ orphanin FQ peptide receptor.MethodsThe expression levels of four ORs in normal tissues and immune cells were obtained from Human Protein Atlas (HPA) RNA-seq dataset, Monaco dataset, and Consensus dataset. Pan-cancer analysis was performed using the The Cancer Genome Atlas (TCGA) dataset, which included the expression of four ORs in different cancer types, significant copy-number alterations (sCNA), gene mutations of the four ORs, survival analysis, co-expression genes analysis, functional enrichment analyses, and correlations between ORs and immune cell infiltration levels. Based on the results of bioinformatic analysis, we selected 10 cancer cell lines for validation in vitro using specific agonists for the four ORs.ResultsOPRL1 (opioid related nociceptin receptor 1 gene) exhibited the highest abundance across different types of cancers, while OPRM1 (opioid receptor mu 1 gene) and OPRD1 (opioid receptor delta 1 gene) were barely detectable in multiple cancer types. Pan-cancer survival analysis revealed the overall worse/better prognosis of the four ORs in certain cancer types. Elevated levels of OPRM1 appear to be associated with poorer outcomes in breast invasive carcinoma and kidney renal clear cell carcinoma. Elevated OPRD1 levels are connected to worsen outcomes in kidney renal clear cell carcinoma and liver hepatocellular carcinoma, but better prognosis in bladder urothelial carcinoma. Increased OPRK1 (opioid receptor kappa 1 gene) expression is linked to a poorer prognosis in kidney renal papillary cell carcinoma. Furthermore, high OPRL1 expression relates to worse outcomes in bladder urothelial carcinoma and liver hepatocellular carcinoma, but better outcomes in breast invasive carcinoma and pancreatic adenocarcinoma. Functional enrichment analyses found that immune-related pathways were enriched in OPRK1 and OPRL1, with OPRL1 exhibiting the highest correlation with immune cell infiltration. Different effects on cell growth, migration, and invasion were observed in different cancer types upon the administration of agonists for the four ORs.ConclusionOPRL1 may play a vital role in monocytes and regulating the immune response and tumor-infiltrating macrophages. Due to its high abundance in different types of tumors, it may hold greater clinical significance for oncology patients. OPRK1 also participates in immune-related pathways. OPRL1 could potentially serve as therapeutic targets for different types of cancers.Graphical

Construction of a Prognostic Prediction Model of Patients with Pathologic N0 in Resected Invasive Mucinous Adenocarcinoma of the Lung

Invasive mucinous adenocarcinoma (IMA) was a rare and specific type of lung adenocarcinoma, which was often characterized by fewer lymphatic metastases. Therefore, it was difficult to evaluate the prognosis of these tumors based on the existing tumor-node-metastasis (TNM) staging. So, this study aimed to develop Nomograms to predict outcomes of patients with pathologic N0 in resected IMA. According to the inclusion criteria and exclusion criteria, IMA patients with pathologic N0 in The Affiliated Lihuili Hospital of Ningbo University (training cohort, n=78) and Ningbo No.2 Hospital (validation cohort, n=66) were reviewed between July 2012 and May 2017. The prognostic value of the clinicopathological features in the training cohort was analyzed and prognostic prediction models were established, and the performances of models were evaluated. Finally, the validation cohort data was put in for external validation. Univariate analysis showed that pneumonic type, larger tumor size, mixed mucinous/non-mucinous component, and higher overall stage were significant influence factors of 5-year progression-free survival (PFS) and overall survival (OS). Multivariate analysis further indicated that type of imaging, tumor size, mucinous component were the independent prognostic factors for poor 5-year PFS and OS. Moreover, the 5-year PFS and OS rates were 62.82% and 75.64%, respectively. In subgroups, the survival analysis also showed that the pneumonic type and mixed mucinous/non-mucinous patients had significantly poorer 5-year PFS and OS compared with solitary type and pure mucinous patients, respectively. The C-index of Nomograms with 5-year PFS and OS were 0.815 (95%CI: 0.741-0.889) and 0.767 (95%CI: 0.669-0.865). The calibration curve and decision curve analysis (DCA) of both models showed good predictive performances in both cohorts. The Nomograms based on clinicopathological characteristics in a certain extent, can be used as an effective prognostic tool for patients with pathologic N0 after IMA resection.

Prognostic value of the CRM status in pancreatic ductal adenocarcinoma: Data from a regional cancer registry.

632 Background: Ductal pancreatic adenocarcinoma (PDAC) still has a dismal prognosis even when deemed resectable. A cancer free resection margin (R0) is associated with a more favourable prognosis than the presence of tumour cells at resection margin (R1). However, the precise definition of the R0 status is still a matter of debate in PDAC. For a more accurate determination of R0 in PDAC the concept of circumferential resection margins (CRM) has been introduced. However, an international standardized nomenclature of CRM is still missing, and the clinical value of the CRM concept is not yet fully established. Here we evaluate whether the CRM status as defined in the national German S3 guideline is an independent prognostic factor in PDAC using data from the regional cancer registry of the State of Baden Württemberg in Germany. Methods: Data from the cancer registry of the State of Baden-Württemberg, Germany were collected, using documented patients diagnosed with invasive ductal adenocarcinoma of the pancreas between 2015 and 2020. The R-status was assessed according to the national German S3 guideline with R0 wide/CRM- when CRM is &gt; 1mm, R0 narrow/CRM+ when CRM is £ 1 mm from the tumour and R1 when tumour cells are found at the resection margin. Progression free survival (PFS) as well as 3-year overall survival (OS) were assessed using Kaplan-Meier statistics and multivariable Cox regression models (adjusted for age, pN stage, primary tumor location and systemic treatment). Results: In total we identified 1098 cases surgically treated for pancreatic cancer and fulfilling the inclusion criteria. 340 patients had an R0 wide/CRM- resection, 410 patients an R0 narrow/CRM+ resection, and 348 patients an R1 resection. The R0 wide/CRM- status was associated with a significantly increased median 3-year OS rate compared to the other two groups (51,5%, 37,4% and 26,7% for R0 wide/CRM-, R0 narrow/CRM+ and R1, respectively). mPFS was also longer in the R0 wide/CRM- group. These findings were robust with regards to grading. 5-FU based adjuvant treatment was mainly mFOLFIRINOX and show better outcome as compared to gemcitabine-based treatments. Conclusions: The present study was performed using real world data reflecting actual clinical settings. The results obtained are in good agreement with data from clinical trials, including the prognostic role of the R- and N- Status as well as the efficacy of adjuvant chemotherapy protocols used.