Mesenchymal epithelial transition (MET) overexpression has been reported in approximately 50–60

Background:Distinguishing synchronous double primary lung adenocarcinoma (SDPLA) from intrapulmonary metastasis (IPM) of lung cancer has significant therapeutic and prognostic values. This study aimed to develop and validate a CT-based radiomics model to differentiate SDPLA from IPM. Methods:A total of 153 patients (93 SDPLA and 60 IPM) with 306 pathologically confirmed lesions were retrospectively studied. CT morphological features were also recorded. Region of interest (ROI) segmentation was performed semiautomatically, and 1,037 radiomics features were extracted from every segmented lesion The differences of radiomics features were defined as the relative net difference in radiomics features between the two lesions on CT. Those low reliable (ICC <0.75) and redundant (r>0.9) features were excluded by intraclass correlation coefficients (ICC) and Pearson's correlation. Multivariate logistic regression (LR) algorithm was used to establish the classification model according to the selected features. The radiomics model was based on the four most contributing differences of radiomics features. Clinical-CT model and MixModel were based on selected clinical and CT features only and the combination of clinical-CT and Rad-score, respectively. Results:In both the training and testing cohorts, the area under the curves (AUCs) of the radiomics model were larger than those of the clinical-CT model (0.944 vs. 0.793 and 0.886 vs. 0.735 on training and testing cohorts, respectively), and statistically significant differences between the two models in the testing set were found (P<0.001). Meanwhile, three radiologists had sensitivities of 84.2%, 63.9%, and 68.4%, and specificities of 76.9%, 69.2%, and 76.9% in differentiating 19 SDPLA cases from 13 cases of IPM in the testing set. Compared with the performance of the three radiologists, the radiomics model showed better accuracy to the patients in both the training and testing cohorts. Among the three models, the radiomics model showed the best net benefits. Conclusions:The differences of radiomics features showed excellent diagnostic performance for preoperative differentiation between synchronous double primary lung adenocarcinoma from interpulmonary metastasis, superior to the clinical model and decisions made by radiologists.

Abstract Background The relationship between molecular characteristics and the prognosis of colorectal cancer (CRC) patients has not been fully understood. This study explored the impact of targeted therapy on the prognosis of CRC patients with different TP53 mutations, in the context of comprehensive treatment. Methods This study included patients with stage III/IV primary CRC from the electronic medical record system. TP53 mutations were detected via next‐generation sequencing (NGS) using formalin‐fixed paraffin‐embedded (FFPE) tissues. Applying two methods, we classified TP53 mutations as gain of function (GOF)/non‐GOF mutations or known/likely loss of function (LOF) mutations. Kaplan–Meier plot and parametric survival analysis were performed to evaluate the prognosis of CRC patients and identify potential predictors. Results There were 286 patients included, of which 166 (58.04%) patients received targeted therapy and 120 (41.96%) did not. There were 286 patients in the TP53 GOF classification set and 247 in the TP53 LOF classification set. Parametric survival analysis, adjusted for sex, onset, KRAS mutation, sidedness, stage, and surgery, showed that receiving targeted therapy predicted better overall survival (OS) among patients who harbored TP53 GOF mutations (HR 0.40, 95% confidence interval (CI) [0.21, 0.76], p = 0.005) or known LOF mutations (HR 0.21, 95% CI [0.07, 0.60], p = 0.002). However, there was no significant impact of receiving targeted therapy on OS among patients harboring TP53 non‐GOF mutations (HR 1.68, 95% CI [0.50, 5.63], p = 0.403) or likely LOF mutations (HR 0.90, 95% CI [0.34, 2.39], p = 0.837). Conclusions Receiving targeted therapy had a heterogeneous impact on the prognosis of CRC patients harboring different TP53 mutations. These results provide promising value for future personalized treatment and precision medicine.

Purpose: In recent years, a rising number of multiple primary lung cancers have been detected with the advancement of imaging technology. No detailed study has assessed the prognosis of multiple primary lung adenocarcinomas based on computed tomography characteristics. The present study aimed to analyze outcomes and determine valuable factors for predicting the prognosis of multiple primary lung adenocarcinoma. Methods: This single-center retrospective study was performed from January 2013 to October 2021. All patients were divided into 3 groups based on tumor density as follows: multi-pure ground-glass nodules, at least one part-solid nodule without solid nodules, and at least one solid nodule. Clinicopathologic features, computed tomography signs, and survival outcomes were compared between these groups. The Kaplan-Meier method was used for survival analysis. The multivariable Cox proportional hazards regression model was used to identify independent predictors for recurrence-free survival and overall survival. Results: The sample included 283 patients with 623 lesions who met the inclusion criteria for multiple primary lung adenocarcinoma. Of these patients, 71 (25.1%) presented with multi-pure ground-glass nodules, 100 (35.3%) with at least one part-solid nodule without solid nodule, and 112 (39.6%) with at least one solid nodule. The 3 groups had distinguished clinicopathologic and radiological features of age, adjuvant therapy, types of tumor resection, TNM stage, pathological subtypes, pleural indentation, spicule, and vacuole (all P < .001). Multivariate analysis found that lesion number was an independent predictor for both recurrence-free survival (hazard ratio 2.41; 95% confidence interval 1.12-5.19; P = .025) and overall survival (hazard ratio 4.78; 95% confidence interval 1.88-12.18; P = .001), and the at least one solid nodule was an independent predictor for overall survival (hazard ratio 5.307; 95% confidence interval 1.16-24.31; P = .032). Stage III (hazard ratio 5.71; 95% confidence interval 1.94-16.81; P = .002) and adjuvant therapy (hazard ratio 2.52; 95% confidence interval 1.24-5.13; P = .011) influenced the recurrence-free survival. Conclusions: Survival of multiple primary lung adenocarcinoma patients is strongly correlated with the lesion number and the at least one solid nodule tumors in radiological. This information may be useful for predicting survival and making clinical decisions in future studies.

ObjectivesTo investigate if delta-radiomics features have the potential to predict the major pathological response (MPR) to neoadjuvant chemoimmunotherapy in non-small cell lung cancer (NSCLC) patients.MethodsTwo hundred six stage IIA-IIIB NSCLC patients from three institutions (Database1 = 164; Database2 = 21; Database3 = 21) who received neoadjuvant chemoimmunotherapy and surgery were included. Patients in Database1 were randomly assigned to the training dataset and test dataset, with a ratio of 0.7:0.3. Patients in Database2 and Database3 were used as two independent external validation datasets. Contrast-enhanced CT scans were obtained at baseline and before surgery. The delta-radiomics features were defined as the relative net change of radiomics features between baseline and preoperative. The delta-radiomics model and pre-treatment radiomics model were established. The performance of Immune-Related Response Evaluation Criteria in Solid Tumors (iRECIST) for predicting MPR was also evaluated.ResultsHalf of the patients (106/206, 51.5%) showed MPR after neoadjuvant chemoimmunotherapy. For predicting MPR, the delta-radiomics model achieved a satisfying area under the curves (AUCs) values of 0.768, 0.732, 0.833, and 0.716 in the training, test, and two external validation databases, respectively, which showed a superior predictive performance than the pre-treatment radiomics model (0.644, 0.616, 0.475, and 0.608). Compared with iRECIST criteria (0.624, 0.572, 0.650, and 0.466), a mixed model that combines delta-radiomics features and iRECIST had higher AUC values for MPR prediction of 0.777, 0.761, 0.850, and 0.670 in four sets.ConclusionThe delta-radiomics model demonstrated superior diagnostic performance compared to pre-treatment radiomics model and iRECIST criteria in predicting MPR preoperatively in neoadjuvant chemoimmunotherapy for stage II-III NSCLC.Clinical relevance statementDelta-radiomics features based on the relative net change of radiomics features between baseline and preoperative CT scans serve a vital support tool in accurately identifying responses to neoadjuvant chemoimmunotherapy, which can help physicians make more appropriate treatment decisions.Key Points center dot The performances of pre-treatment radiomics model and iRECIST model in predicting major pathological response of neoadjuvant chemoimmunotherapy were unsatisfactory.center dot The delta-radiomics features based on relative net change of radiomics features between baseline and preoperative CT scans may be used as a noninvasive biomarker for predicting major pathological response of neoadjuvant chemoimmunotherapy.center dot Combining delta-radiomics features and iRECIST can further improve the predictive performance of responses to neoadjuvant chemoimmunotherapy.Key Points center dot The performances of pre-treatment radiomics model and iRECIST model in predicting major pathological response of neoadjuvant chemoimmunotherapy were unsatisfactory.center dot The delta-radiomics features based on relative net change of radiomics features between baseline and preoperative CT scans may be used as a noninvasive biomarker for predicting major pathological response of neoadjuvant chemoimmunotherapy.center dot Combining delta-radiomics features and iRECIST can further improve the predictive performance of responses to neoadjuvant chemoimmunotherapy.Key Points center dot The performances of pre-treatment radiomics model and iRECIST model in predicting major pathological response of neoadjuvant chemoimmunotherapy were unsatisfactory. center dot The delta-radiomics features based on relative net change of radiomics features between baseline and preoperative CT scans may be used as a noninvasive biomarker for predicting major pathological response of neoadjuvant chemoimmunotherapy.center dot Combining delta-radiomics features and iRECIST can further improve the predictive performance of responses to neoadjuvant chemoimmunotherapy.

Background Anaplastic lymphoma kinase (ALK) overexpression and gene alterations have been detected in several mesenchymal tumors, with significant implications for diagnosis, therapy and prognosis. However, few studies have investigated the correlation between ALK expression status and clinicopathological characteristics in patients with gastrointestinal stromal tumors (GISTs). Methods A total of 506 GIST patients were enrolled. Sanger sequencing was employed to detect c-KIT and PDGFRA gene mutations. The tissue microarray (TMA) technique and immunohistochemistry were employed to identify the ALK (clone: 1A4 and D5F3) expression status in the tumor tissues. The ALK gene variants of IHC-positive cases were analyzed by fluorescence in situ hybridization (FISH) and next-generation sequencing (NGS). The clinicopathological data were analyzed using SPSS Statistics 26.0. Results Among the 506 GIST patients, the c-KIT mutation accounted for 84.2% (426/506), followed by PDGFRA mutation (10.3%, 52/506), while the wild-type accounted for the least (5.5%, 28/506). ALK-positive expression was detected in PDGFRA -mutant GISTs (7.7%, 4/52) but negative for c-KIT -mutant or wild-type GISTs by IHC. Four ALK IHC-positive patients were all male. The tumors all occurred outside the stomach. The predominant patterns of growth were epithelioid (2/4), spindle (1/4), and mixed type (1/4). They were all identified as high-risk classification according to the National Institutes of Health (NIH) classification. Aberrant ALK mutations were not identified by DNA-based NGS except in one of the 4 cases with amplification by FISH. Conclusion Our study revealed 7.7% (4/52) of ALK expression in PDGFRA -mutant GISTs, indicating that molecular tests were required to rule out the possibility of PDGFRA -mutant GISTs when encountering ALK-positive mesenchymal tumors with CD117-negative or weakly positive in immunohistochemical staining.

Background Gastrointestinal stromal tumours (GISTs) rarely arise in the esophagus. The clinical course and treatment options for esophageal GISTs are poorly understood because of their rarity. In general, the mutation spectrum of esophageal GISTs resembles that of gastric GISTs. Wild-type (WT) GISTs lacking KIT and PDGFRA gene mutations occasionally occur in adults; primary esophageal GISTs are commonly WT . Case presentation Herein, we report the case of a 41-year-old female patient who presented with a 1-week history of anterior upper chest pain. Chest computed tomography revealed a 3.7 cm × 2.8 cm × 6.7 cm soft tissue mass in the right posterior mediastinum adjacent to the esophagus. The patient underwent thoracoscopic mediastinal tumor resection and was subsequently diagnosed with an esophageal GIST. Neither KIT nor PDGFRA mutations were detected by Sanger sequencing; however, next-generation sequencing (NGS) identified an FGFR2-KIAA1217 gene fusion in the tumor tissue. No relapse was observed in this patient during the 8-month treatment-free follow-up period. Conclusion To the best of our knowledge, this report is the first to describe an FGFR2-KIAA1217 fusion in a patient with a quadruple WT esophageal GIST. When WT KIT/PDGFRA GISTS are suspected, intensive genetic analysis is recommended, and obtaining a better molecular characterization of these tumours might reveal novel therapeutic avenues.

OBJECTIVE:To investigate the efficacy of chemotherapy combined with antivirals in adult T-cell leukemia/lymphoma (ATLL) patients and the prognostic factors.METHODS:Forty nine patients with previously treated or treatment-nave ATLL from January 2018 to January 2021 were included in our study. The patients were divied into two groups according to whether they received antiviral treatment, twenty-seven patients were treated with chemotherapy combined with antivirals, including thirteen patients treated with recombinant interferon alpha-2b and CHOP therapy, eight patients treated with zidovudine combined with CHOP therapy, and 6 patients treated with CHOP regimen combined with interferon and zidovudine. Twenty-two patients were treated with CHOP therapy. The changes of symptom, hematological parameters, lactic dehydrogenase, β2-microglobulin, and the Ki-67 positive rate were compared between the two groups before and after treatments. The clinical efficacy of chemotherapy combined with antiviral therapy for ATLL was evaluated. The antiviral effect was assessed by detecting HTLV-1 virus copy number, and prognostic factors were analyzed.RESULTS:The median follow-up time was 14 months. Compared with the patients treated with chemotherapy alone, the patients treated with chemotherapy combined with antivirals had lower tumor and virus loads, lower white blood cell count, lower lactate dehydrogenase level, lower β2-microglobulin lever, and lower Ki-67 positive rate (all P<0.05). The total effective rate of patients treated with chemotherapy combined with antivirals was significantly higher than those of patients treated with chemotherapy alone (63.0% vs 31.8%, P=0.035). The one-year overall survival (OS) rates of chemotherapy combined with antivirals groups and chemotherapy alone group were (74.1±2.9)％ and (40.9±2.1)％ (P=0.021), respectively. The one-year progress free survival (PFS) rates were (51.9±3.3)％ and (13.6±2.8)％ (P=0.017), respectively. Multivariable Cox regression analysis showed that HTLV-1 virus load (HR=7.518, 95%CI: 2.517-36.192, P=0.013) and antiviral therapy ［HR=5.617 (95%CI 1.803-11.293), P=0.027］ were independent prognostic factors for the long-term efficacy.CONCLUSION:Addition of antivirals to chemotherapy can prolong PFS and OS in ATLL patients. HTLV-1 virus load and antiviral therapy are independent prognostic factors for ATLL patients.

BACKGROUND:Pulmonary sarcomatoid carcinoma (PSC) is a rare and unconventional non-small-cell lung cancer (NSCLC) that appears to be aggressive, with a poor prognosis and response to conventional treatment. Approximately 30% of PSCs have potentially targetable genomic alterations, but few studies have involved RET gene fusions, and corresponding targeted therapies are lacking.CASE PRESENTATION:In this report, we describe a patient with PSC harboring a KIF5B-RET gene fusion who was initially diagnosed with stage IVb lung cancer. Due to the poor performance status, the patient was unable to tolerate any radiotherapy or chemotherapy. Based on the next-generation sequencing (NGS) result of RET gene fusion, the patient was treated with pralsetinib. Two months after the treatment, the patient achieved a partial response.CONCLUSIONS:Our case indicates that RET is one of the main driver oncogenes of PSC and provides useful information for precise RET inhibitor administration in the future. Thus, the use of comprehensive genomic profiling may provide important treatment options for PSC.