Development of a machine learning-based radiomics signature for estimating breast cancer TME phenotypes and predicting anti-PD-1/PD-L1 immunotherapy response

BACKGROUNDS

Since breast cancer patients respond diversely to immunotherapy, there is an urgent need to explore novel biomarkers to precisely predict clinical responses and enhance therapeutic efficacy. The purpose of our present research was to construct and independently validate a biomarker of tumor microenvironment (TME) phenotypes via a machine learning-based radiomics way. The interrelationship between the biomarker, TME phenotypes and recipients' clinical response was also revealed.

METHODS

In this retrospective multi-cohort investigation, five separate cohorts of breast cancer patients were recruited to measure breast cancer TME phenotypes via a radiomics signature, which was constructed and validated by integrating RNA-seq data with DCE-MRI images for predicting immunotherapy response. Initially, we constructed TME phenotypes using RNA-seq of 1089 breast cancer patients in the TCGA database. Then, parallel DCE-MRI images and RNA-seq of 94 breast cancer patients obtained from TCIA were applied to develop a radiomics-based TME phenotypes signature using random forest in machine learning. The repeatability of the radiomics signature was then validated in an internal validation set. Two additional independent external validation sets were analyzed to reassess this signature. The Immune phenotype cohort (n = 158) was divided based on CD8 cell infiltration into immune-inflamed and immune-desert phenotypes; these data were utilized to examine the relationship between the immune phenotypes and this signature. Finally, we utilized an Immunotherapy-treated cohort with 77 cases who received anti-PD-1/PD-L1 treatment to evaluate the predictive efficiency of this signature in terms of clinical outcomes.

RESULTS

The TME phenotypes of breast cancer were separated into two heterogeneous clusters: Cluster A, an "immune-inflamed" cluster, containing substantial innate and adaptive immune cell infiltration, and Cluster B, an "immune-desert" cluster, with modest TME cell infiltration. We constructed a radiomics signature for the TME phenotypes ([AUC] = 0.855; 95% CI 0.777-0.932; p < 0.05) and verified it in an internal validation set (0.844; 0.606-1; p < 0.05). In the known immune phenotypes cohort, the signature can identify either immune-inflamed or immune-desert tumor (0.814; 0.717-0.911; p < 0.05). In the Immunotherapy-treated cohort, patients with objective response had higher baseline radiomics scores than those with stable or progressing disease (p < 0.05); moreover, the radiomics signature achieved an AUC of 0.784 (0.643-0.926; p < 0.05) for predicting immunotherapy response.

CONCLUSIONS

Our imaging biomarker, a practicable radiomics signature, is beneficial for predicting the TME phenotypes and clinical response in anti-PD-1/PD-L1-treated breast cancer patients. It is particularly effective in identifying the "immune-desert" phenotype and may aid in its transformation into an "immune-inflamed" phenotype.

Comparison of surgical effect in active and inactive Dysthyroid Optic Neuropathy after Endoscopic Transnasal Medial Orbital Decompression

PURPOSE

To evaluate and compare the changes in orbital soft tissue volume and visual function after endoscopic transnasal medial orbital decompression in patients with active and inactive dysthyroid optic neuropathy (DON).

METHODS

This prospective, cohort study recruited 112 patients (112 eyes) with DON who were divided into an active and inactive DON group (56 eyes each) by clinical activity scores. All patients underwent endoscopic transnasal medial orbital decompression. The pre- and post-operative orbital soft tissue volumes were measured with high-resolution computed tomography (CT) using Mimics software. Visual function, including best-corrected visual acuity (BCVA), visual field (VF), and visual evoked potential (VEP), was recorded before and after surgery.

RESULTS

Preoperatively, compared with the inactive DON group, the active DON group had greater extraocular muscle volume (EMV) and EMV/orbital volume (OV) ratio, but worse BCVA, VF, and exophthalmos. Postoperatively, although the EMV slightly increased, with the enlarged medial rectus muscle contributing dramatically, the EMV/OV ratio decreased in patients with DON. Besides, visual function including BCVA, VF, VEP and exophthalmos was also improved in both groups after surgery. There were no significant differences in postoperative OV; EMV; EMV/OV ratio; and the BCVA, VF, and VEP parameters between both groups (all P > 0.05).

CONCLUSION

Patients with DON who did not respond well to steroids, regardless of disease activity, may benefit from orbital decompression via the decrease in the proportion of EMV in OV, especially patients with active DON, who showed more improved visual function than patients with inactive DON.

Lack of incremental value of three-dimensional measurement in assessing invasiveness for lung cancer

OBJECTIVES

The aim of this study was to evaluate the performance of consolidation-to-tumour ratio (CTR) and the radiomic models in two- and three-dimensional modalities for assessing radiological invasiveness in early-stage lung adenocarcinoma.

METHODS

A retrospective analysis was conducted on patients with early-stage lung adenocarcinoma from Guangdong Provincial People's Hospital and Shenzhen People's Hospital. Manual delineation of pulmonary nodules along the boundary was performed on cross-sectional images to extract radiomic features. Clinicopathological characteristics and radiomic signatures were identified in both cohorts. CTR and radiomic score for every patient were calculated. The performance of CTR and radiomic models were tested and validated in the respective cohorts.

RESULTS

A total of 818 patients from Guangdong Provincial People's Hospital were included in the primary cohort, while 474 patients from Shenzhen People's Hospital constituted an independent validation cohort. Both CTR and radiomic score were identified as independent factors for predicting pathological invasiveness. CTR in two- and three-dimensional modalities exhibited comparable results with areas under the receiver operating characteristic curves and were demonstrated in the validation cohort (area under the curve: 0.807 vs 0.826, P = 0.059) Furthermore, both CTR in two- and three-dimensional modalities was able to stratify patients with significant relapse-free survival (P < 0.000 vs P < 0.000) and overall survival (P = 0.003 vs P = 0.001). The radiomic models in two- and three-dimensional modalities demonstrated favourable discrimination and calibration in independent cohorts (P = 0.189).

CONCLUSIONS

Three-dimensional measurement provides no additional clinical benefit compared to two-dimensional.

Expression Changes in Programmed Death Ligand 1 from Precancerous Lesions to Invasive Adenocarcinoma in Subcentimeter Pulmonary Nodules: A Large Study of 2022 Cases in China

PURPOSE

This large-scale, multicenter, retrospective observational study aimed to evaluate the clinicopathological and molecular profiles associated with programmed death-ligand 1 (PD-L1) expression in precancerous lesions and invasive adenocarcinoma in subcentimeter pulmonary nodules.

PATIENTS AND METHODS

Patients with histologically confirmed atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (ADC) were included. PD-L1 expression was evaluated at each center using a PD-L1 immunohistochemistry 22C3 pharmDx kit (Agilent, Santa Clara, CA, USA). The tumor proportion score (TPS) cutoff values were set at ≥ 1% and ≥ 50%.

RESULTS

A total of 2022 nodules from 1844 patients were analyzed. Of these, 9 (0.45%) nodules had PD-L1 TPS ≥ 50%, 187 (9.25%) had PD-L1 TPS 1-49%, and 1826 (90.30%) had PD-L1 TPS < 1%. A total of 378 (18.69%), 1016 (50.25%), and 628 (31.06%) nodules were diagnosed as AAH/AIS, MIA, and ADC, respectively, by pathology. A total of 1377 (68.10%), 591 (25.67%), and 54 (2.67%) nodules were diagnosed as pure ground-glass opacity (GGO), mixed GGO, and solid nodules, respectively, by computed tomography. There was a significant difference between PD-L1 expression and anaplastic lymphoma kinase (ALK) mutation status (P < 0.001). PD-L1 expression levels were significantly different from those determined using the International Association for the Study of Lung Cancer (IASLC) grading system (P < 0.001).

CONCLUSIONS

PD-L1 expression was significantly associated with radiological and pathological invasiveness and driver mutation status in subcentimeter pulmonary nodules. The significance of PD-L1 expression in the evolution of early-stage lung adenocarcinoma requires further investigation.

c-JUN is a barrier in hESC to cardiomyocyte transition

Loss of c-JUN leads to early mouse embryonic death, possibly because of a failure to develop a normal cardiac system. How c-JUN regulates human cardiomyocyte cell fate remains unknown. Here, we used the in vitro differentiation of human pluripotent stem cells into cardiomyocytes to study the role of c-JUN. Surprisingly, the knockout of c-JUN improved cardiomyocyte generation, as determined by the number of TNNT2+ cells. ATAC-seq data showed that the c-JUN defect led to increased chromatin accessibility on critical regulatory elements related to cardiomyocyte development. ChIP-seq data showed that the knockout c-JUN increased RBBP5 and SETD1B expression, leading to improved H3K4me3 deposition on key genes that regulate cardiogenesis. The c-JUN KO phenotype could be copied using the histone demethylase inhibitor CPI-455, which also up-regulated H3K4me3 levels and increased cardiomyocyte generation. Single-cell RNA-seq data defined three cell branches, and knockout c-JUN activated more regulons that are related to cardiogenesis. In summary, our data demonstrated that c-JUN could regulate cardiomyocyte cell fate by modulating H3K4me3 modification and chromatin accessibility and shed light on how c-JUN regulates heart development in humans.

CT morphological features for predicting the risk of lymph node metastasis in T1 colorectal cancer

OBJECTIVES

The aim of this study is to evaluate the feasibility of clinicopathological characteristics and computed tomography (CT) morphological features in predicting lymph node metastasis (LNM) for patients with T1 colorectal cancer (CRC).

METHODS

A total of 144 patients with T1 CRC who underwent CT scans and surgical resection were retrospectively included in our study. The clinicopathological characteristics and CT morphological features were assessed by two observers. Univariate and multiple logistic regression analyses were used to identify significant LNM predictive variables. Then a model was developed using the independent predictive factors. The predictive model was subjected to bootstrapping validation (1000 bootstrap resamples) to calculate the calibration curve and relative C-index.

RESULTS

LNM were found in 30/144 patients (20.83%). Four independent risk factors were determined in the multiple logistic regression analysis, including presence of necrosis (adjusted odds ratio [OR] = 10.32, 95% confidence interval [CI] 1.96-54.3, p = 0.004), irregular outer border (adjusted OR = 5.94, 95% CI 1.39-25.45, p = 0.035), and heterogeneity enhancement (adjusted OR = 7.35, 95% CI 3.11-17.38, p = 0.007), as well as tumor location (adjusted ORright-sided colon = 0.05 [0.01-0.60], p = 0.018; adjusted ORrectum = 0.22 [0.06-0.83], p = 0.026). In the internal validation cohort, the model showed good calibration and good discrimination with a C-index of 0.89.

CONCLUSIONS

There are significant associations between lymphatic metastasis status and tumor location as well as CT morphologic features in T1 CRC, which could help the doctor make decisions for additional surgery after endoscopic resection.

KEY POINTS

• LNM more frequently occurs in left-sided T1 colon cancer than in right-sided T1 colon and rectal cancer. • CT morphologic features are risk factors for LNM of T1 CRC, which may be related to fundamental biological behaviors. • The combination of tumor location and CT morphologic features can more effectively assist in predicting LNM in patients with T1 CRC, and decrease the rate of unnecessary extra surgeries after endoscopic resection.

MiRNA-338-3p Inhibits Neuroinflammation in the Corpus Callosum of LCV-LPS Rats Via STAT1 Signal Pathway

Neuroinflammation is a common characteristic of intracranial infection (ICI), which is associated with the activation of astrocytes and microglia. MiRNAs are involved in the process of neuroinflammation. This study aimed to investigate the potential mechanism by which miR-338-3p negatively modulate the occurrence of neuroinflammation. We here reported that the decreased levels of miR-338-3p were detected using qRT-PCR and the upregulated expression of TNF-α and IL-1β was measured by ELISA in the cerebrospinal fluid (CSF) in patients with ICI. A negative association between miR-338-3p and TNF-α or IL-1β was revealed by Pearson correlation analysis. Sprague-Dawley (SD) rats were injected with LPS (50 μg) into left cerebral ventricule (LCV), following which the increased expression of TNF-α and IL-1β and the reduction of miR-338-3p expression were observed in the corpus callosum (CC). Moreover, the expression of TNF-α and IL-1β in the astrocytes and microglia in the CC of LCV-LPS rats were saliently inhibited by the overexpression of miR-338-3p. In vitro, cultured astrocytes and BV2 cells transfected with mimic-miR-338-3p produced less TNF-α and IL-1β after LPS administration. Direct interaction between miR-338-3p and STAT1 mRNA was validated by biological information analysis and dual luciferase assay. Furthermore, STAT1 pathway was found to be implicated in inhibition of neuroinflammation induced by mimic miR-338-3p in the astrocytes and BV2 cells. Taken together, our results suggest that miR-338-3p suppress the generation of proinflammatory mediators in astrocyte and BV2 cells induced by LPS exposure through the STAT1 signal pathway. MiR-338-3p could act as a potential therapeutic strategy to reduce the neuroinflammatory response. Diagram describing the cellular and molecular mechanisms associated with LPS-induced neuroinflammation via the miR-338-3p/STAT1 pathway. LPS binds to TLRs on astrocytes or microglia to activate the STAT1 pathway and upregulate the production of pro-inflammatory cytokines. However, miR-338-3p inhibits the expression of STAT1 and reduces the production of inflammatory mediators.

An artificial intelligence-based ecological index for prognostic evaluation of colorectal cancer

BACKGROUND AND OBJECTIVE

In the tumor microenvironment (TME), the dynamic interaction between tumor cells and immune cells plays a critical role in predicting the prognosis of colorectal cancer. This study introduces a novel approach based on artificial intelligence (AI) and immunohistochemistry (IHC)-stained whole-slide images (WSIs) of colorectal cancer (CRC) patients to quantitatively assess the spatial associations between tumor cells and immune cells. To achieve this, we employ the Morisita-Horn ecological index (Mor-index), which allows for a comprehensive analysis of the spatial distribution patterns between tumor cells and immune cells within the TME.

MATERIALS AND METHODS

In this study, we employed a combination of deep learning technology and traditional computer segmentation methods to accurately segment the tumor nuclei, immune nuclei, and stroma nuclei within the tumor regions of IHC-stained WSIs. The Mor-index was used to assess the spatial association between tumor cells and immune cells in TME of CRC patients by obtaining the results of cell nuclei segmentation. A discovery cohort (N = 432) and validation cohort (N = 137) were used to evaluate the prognostic value of the Mor-index for overall survival (OS).

RESULTS

The efficacy of our method was demonstrated through experiments conducted on two datasets comprising a total of 569 patients. Compared to other studies, our method is not only superior to the QuPath tool but also produces better segmentation results with an accuracy of 0.85. Mor-index was quantified automatically by our method. Survival analysis indicated that the higher Mor-index correlated with better OS in the discovery cohorts (HR for high vs. low 0.49, 95% CI 0.27-0.77, P = 0.0014) and validation cohort (0.21, 0.10-0.46, < 0.0001).

CONCLUSION

This study provided a novel AI-based approach to segmenting various nuclei in the TME. The Mor-index can reflect the immune status of CRC patients and is associated with favorable survival. Thus, Mor-index can potentially make a significant role in aiding clinical prognosis and decision-making.

An optimized TRIzol-based method for isolating RNA from adipose tissue

High-quality RNA isolation from recalcitrant adipose tissue with high lipid content and low cell numbers is difficult. Many studies have made efforts to optimize methods for isolating RNA from adipose tissue through combinations of column-based kits and phenol-chloroform methods, or through in-house protocols. However, the considerable complexity of these protocols and the various kits/materials required hamper their wide use. Herein, we describe an optimized protocol based on TRIzol reagent, which is the most accessible ready-to-use reagent for nucleic acid and/or protein isolation in laboratories. This article provides a step-by-step protocol yielding sufficient and qualified RNA from lipid-rich specimens for downstream applications.

Necrosis score as a prognostic factor in stage I-III colorectal cancer: a retrospective multicenter study

BACKGROUND

Tumor necrosis results from failure to meet the requirement for rapid proliferation of tumor, related to unfavorable prognosis in colorectal cancer (CRC). However, previous studies used traditional microscopes to evaluate necrosis on slides, lacking a simultaneous phase and panoramic view for assessment. Therefore, we proposed a whole-slide images (WSIs)-based method to develop a necrosis score and validated its prognostic value in multicenter cohorts.

METHODS

Necrosis score was defined as the proportion of necrosis in the tumor area, semi-quantitatively classified into 3-level score groups by the cut-off of 10% and 30% on HE-stained WSIs. 768 patients from two centers were enrolled in this study, divided into a discovery (N = 445) and a validation (N = 323) cohort. The prognostic value of necrosis score was evaluated by Kaplan-Meier curves and the Cox model.

RESULT

Necrosis score was associated with overall survival, with hazard ratio for high vs. low in discovery and validation cohorts being 2.62 (95% confidence interval 1.59-4.32) and 2.51 (1.39-4.52), respectively. The 3-year disease free survival rates of necrosis-low, middle, and high were 83.6%, 80.2%, and 59.8% in discovery cohort, and 86.5%, 84.2%, and 66.5% in validation cohort. In necrosis middle plus high subgroup, there was a trend but no significant difference in overall survival between surgery alone and adjuvant chemotherapy group in stage II CRC (P = .075).

CONCLUSION

As a stable prognostic factor, high-level necrosis evaluated by the proposed method on WSIs was associated with unfavorable outcomes. Additionally, adjuvant chemotherapy provide survival benefits for patients with high necrosis in stage II CRC.

Heterogeneity in the immune microenvironment of bone metastasis in driver-positive non-small cell lung cancer

Mutations in epidermal growth factor receptor and anaplastic lymphoma kinase are common driver events in non-small cell lung cancer (NSCLC), which are associated with a high frequency of bone metastases (BMs). While the bone marrow represents a specialized immune microenvironment, the immune repertoire of BMs remains unknown. Considering the higher incidence of BMs in driver gene-positive NSCLCs, and the unique biology of the bone, herein, we assessed the infiltrating immune cells and T cell receptor (TCR) profile of BMs in driver-positive NSCLCs. Immune profile of BMs in driver gene-positive NSCLC were assessed in 10 patients, where 6 had driver gene-positive mutation. TCR and bulk RNA sequencing were performed on malignant bone samples. The diversity and clonality of the TCR repertoire were analyzed. The cellular components were inferred from bulk gene expression profiles computationally by CIBERSORT. Although BMs were generally regarded as immune-cold tumors, immune cell composition analyses showed co-existence of cytotoxic and suppressor immune cells in driver-positive BM samples, as compared to primary lung. Analysis of the TCR repertoire indicated a trend of higher diversity and similar clonality in the driver-positive compared with the driver-negative subsets. In addition, we identified two cases that showed the opposite response to immune checkpoint blockade. A comparison of these two patients' BM samples showed more highly amplified clones, fewer M2 macrophages and more activated natural killer cells in the responder. In summary, BMs in NSCLC are heterogeneous in their immune microenvironment, which might be related to differential clinical outcomes to immune checkpoint blockade.

Ultrasound-assisted carbon nanoparticle suspension mapping versus dual tracer-guided sentinel lymph node biopsy in patients with early breast cancer (ultraCars): phase III randomized clinical trial

BACKGROUND

Appropriate tracing methods for sentinel lymph node biopsy (SLNB) play a key role in accurate axillary staging. This prospective, non-inferiority, phase III RCT compared the feasibility and diagnostic performance of ultrasound-assisted carbon nanoparticle suspension (CNS) mapping with dual tracer-guided SLNB in patients with early breast cancer.

METHODS

Eligible patients had primary breast cancer without nodal involvement (cN0), or had clinically positive lymph nodes (cN1) that were downstaged to cN0 after neoadjuvant chemotherapy. Patients were randomly assigned (1 : 1) to undergo either ultrasound-assisted CNS sentinel lymph node (SLN) mapping (UC group) or dual tracer-guided mapping with CNS plus indocyanine green (ICG) (GC group). The primary endpoint was the SLN identification rate.

RESULTS

Between 1 December 2019 and 30 April 2021, 330 patients were assigned randomly to the UC (163 patients) or GC (167 patients) group. The SLN identification rate was 94.5 (95 per cent c.i. 90.9 to 98.0) per cent in the UC group and 95.8 (92.7 to 98.9) per cent in the GC group. The observed difference of -1.3 (-5.9 to 3.3) per cent was lower than the prespecified non-inferiority margin of 6 per cent (Pnon-inferiority = 0.024). No significant difference was observed in metastatic node rate (30.5 versus 24.4 per cent; P = 0.222), median number of SLNs harvested (3 (range 1-7) versus 3 (1-8); P = 0.181), or duration of surgery (mean(s.d.) 7.53(2.77) versus 7.63(3.27) min; P = 0.316) between the groups. Among the subgroup of patients who had undergone neoadjuvant treatment, the SLN identification rate was 91.7 (82.2 to 100) per cent in the UC group and 90.7 (81.7 to 99.7) per cent in the GC group.

CONCLUSION

The diagnostic performance of ultrasound-assisted CNS mapping was non-inferior to that of dual tracer-guided SLN mapping with CNS plus ICG in patients with early breast cancer.

REGISTRATION NUMBER

NCT04951245 (http://www.clinicaltrials.gov).

Multiple-parameter MRI after neoadjuvant systemic therapy combining clinicopathologic features in evaluating axillary pathologic complete response in patients with clinically node-positive breast cancer

OBJECTIVE

This study aimed to evaluate axillary pathologic complete response (pCR) after neoadjuvant systemic therapy (NST) in clinically node-positive breast cancer (BC) patients based on post-NST multiple-parameter MRI and clinicopathological characteristics.

METHODS

In this retrospective study, females with clinically node-positive BC who received NST and followed by surgery between January 2017 and September 2021 were included. All axillary lymph nodes (ALNs) on MRI were matched with pathology by ALN markers or sizes. MRI morphological parameters, signal intensity curve (TIC) patterns and apparent diffusion coefficient (ADC) values of post-NST ALNs were measured. The clinicopathological characteristics was also collected and analyzed. Univariable and multivariable logistic regression analyses were performed to evaluate the independent predictors of axillary pCR.

RESULTS

Pathologically confirmed 137 non-pCR ALNs in 71 patients and 87 pCR ALNs in 87 patients were included in this study. Cortical thickness, fatty hilum, and TIC patterns of ALNs, hormone receptor, and human epidermal growth factor receptor 2 (HER2) status were significantly different between the two groups (all, p < 0.05). There was no significant difference for ADC values (p = 0.875). On multivariable analysis, TIC patterns (odds ratio [OR], 2.67, 95% confidence interval [CI]: 1.33, 5.34, p = 0.006), fatty hilum (OR, 2.88, 95% CI:1.39, 5.98, p = 0.004), hormone receptor (OR, 8.40, 95% CI: 2.48, 28.38, p = 0.001) and HER2 status (OR, 8.57, 95% CI: 3.85, 19.08, p < 0.001) were identified as independent predictors associated with axillary pCR. The area under the curve of the multivariate analysis using these predictors was 0.85 (95% CI: 0.79, 0.91).

CONCLUSION

Combining post-NST multiple-parameter MRI and clinicopathological characteristics allowed more accurate identification of BC patients who had received axillary pCR after NST.

ADVANCES IN KNOWLEDGE

A combined model incorporated multiple-parameter MRI and clinicopathologic features demonstrated good performance in evaluating axillary pCR preoperatively and non-invasively.

A Novel Radiopathological Grading System to Tailor Recurrence Risk for Pathologic Stage IA Lung Adenocarcinoma

To validate the efficiency of pathologic grading system in pathologic stage IA lung adenocarcinoma (LUAD), and explore whether integrating preoperative radiological features would enhance the performance of recurrence discrimination. We retrospectively collected 510 patients with resected stage IA LUAD between January 2012 and December 2019 from Guangdong Provincial People's Hospital (GDPH). Pathologic grade classification of each case was based on the International Association for the Study of Lung Cancer (IASLC) pathologic staging system. Kaplan-Meier curves was used to assess the power of recurrence stratification. Concordance index (C-Index) and receiver operating characteristic curves (ROC) were used for evaluating the clinical utility of different grading systems for recurrence discrimination. Patients of lower IASLC grade showed improved recurrence-free survival (RFS) (P < 0.0001) where numerically difference was found between grade II and grade III (P = 0.119). By integrating the IASLC grading system and radiological feature, we found the RFS rate decreased as the novel radiopathological (RP) grading system increased (P < 0.0001). The difference of RFS curves between any 2 groups as per the RP grading system was statisticallysignificant (RP grade I vs RP grade II, p = 0.007; RP grade I vs RP grade III, P < 0.0001; RP grade II vs RP grade III, P = 0.0003). Compared with the IASLC grading system, the RP grading system remarkably improved recurrence survival discrimination (C-index: 0.822; area under the curve, 0.845). Integrating imaging features into pathologic grading system enhanced the efficiency of recurrence discrimination for resected stage IA LUAD and might help conduct subsequent management.

Melatonin Reduces Neuroinflammation and Improves Axonal Hypomyelination by Modulating M1/M2 Microglia Polarization via JAK2-STAT3-Telomerase Pathway in Postnatal Rats Exposed to Lipopolysaccharide

Microglia activation and associated inflammation are implicated in the periventricular white matter damage (PWMD) in septic postnatal rats. This study investigated whether melatonin would mitigate inflammation and alleviate the axonal hypomyelination in the corpus callosum in septic postnatal rats. We further explored if this might be related to the modulation of microglial polarization from M1 phenotype to M2 through the JAK2/STAT3/telomerase pathway. We reported here that indeed melatonin not only can it reduce the neurobehavioral disturbances in LPS-injected rats, but it can also dampen microglia-mediated inflammation. Thus, in LPS + melatonin group, the expression of proinflammatory mediators in M1 phenotype microglia was downregulated. As opposed to this, M2 microglia were increased which was accompanied by upregulated expression of anti-inflammatory mediators along with telomerase reverse transcriptase or melatonin receptor 1(MT1). In parallel to this was decreased NG2 expression but increased expression of myelin and neurofilament proteins. Melatonin can improve hypomyelination which was confirmed by electron microscopy. In vitro in primary microglia stimulated by LPS, melatonin decreased the expression of proinflammatory mediators significantly; but it increased the expression of anti-inflammatory mediators. Additionally, the expression levels of p-JAK2 and p-STAT3 were significantly elevated in microglia after melatonin treatment. Remarkably, the effect of melatonin on LPS-treated microglia was blocked by melatonin receptor, JAK2, STAT3 and telomerase reverse transcriptase inhibitors, respectively. Taken together, it is concluded that melatonin can attenuate PWMD through shifting M1 microglia towards M2 via MT1/JAK2/STAT3/telomerase pathway. The results suggest a new therapeutic strategy whereby melatonin may be adopted to convert microglial polarization from M1 to M2 phenotype that would ultimately contribute to the attenuation of PWMD.

Predicting Neoadjuvant Chemoradiotherapy Response in Locally Advanced Rectal Cancer Using Tumor-Infiltrating Lymphocytes Density

PURPOSE

Accumulating evidence revealed the predictive value of tumor-infiltrating lymphocytes (TILs) for neoadjuvant chemoradiotherapy (nCRT) response in solid tumors. This study quantified TILs density using hematoxylin and eosin (H&E) stained whole-slide images (WSIs) and investigated the predictive value of TILs density on nCRT response in locally advanced rectal cancer (LARC) patients.

PATIENTS AND METHODS

Two hundred and ten patients diagnosed with LARC were enrolled in this study. The density of TILs in the stroma region was quantified by a semi-automatic method in WSIs. Patients were stratified into low-TILs and high-TILs groups using the median value as the threshold. The tumor regression grade (TRG) was used to assess the response to nCRT in tumor resected specimens. Based on TRG, patients were classified into major-responder (TRG 0-1) and non-responder (TRG 2-3) groups.

RESULTS

The TILs density was significantly correlated with the nCRT response. Specifically, patients with high-TILs tend to have a higher major-responder rate than the low-TILs group (63.8% vs 47.6%, P = 0.026). Univariate analysis showed the TILs density was a predictor for the nCRT response (high vs low, odds ratio [OR] =1.94, 95% confidence interval 1.12-3.37, P = 0.019), and multivariate analysis further confirmed the correlation (adjusted odds ratio [AOR] = 2.41, 1.28-4.56, P = 0.007).

CONCLUSION

Patients with a high-TIL density have a higher major-responder rate than the low-TILs group, indicating patients with a strong immune response benefit more from nCRT. This semi-automatic method can facilitate the individualized preoperative prediction of the TRG for LARC patients before nCRT.

Validation of a portable marker-based motion analysis system

BACKGROUND

The Opti_Knee system, a marker-based motion capture system, tracks and analyzes the 6 degrees of freedom (6DOF) motion of the knee joint. However, the validation of the accuracy of this gait system had not been previously reported. The objective of this study was to validate and the system. Two healthy subjects were recruited for the study.

METHODS

The 6DOF kinematics of the knee during flexion-extension and level walking cycles of the knee were recorded by Opti_Knee and compared to those from a biplanar fluoroscopy system. The root mean square error (RMSE) of knee kinematics in flexion-extension cycles were compared between the two systems to validate the accuracy at which they detect basic knee motions. The RMSE of kinematics at key events of gait cycles (level walking) were compared to validate the accuracy at which the systems detect functional knee motion. Pearson correlation tests were conducted to assess similarities in knee kinematic trends between the two systems.

RESULTS

In flexion-extension cycles, the average translational accuracy (RMSE) was between 2.7 and 3.7 mm and the average rotational accuracy was between 1.7 and 3.8°. The Pearson correlation of coefficients for flexion-extension cycles was between 0.858 and 0.994 for translation and 0.995-0.999 for angles. In gait cycles, the RMSEs of angular knee kinematics were 2.3° for adduction/abduction, 3.2° for internal/external rotation, and 1.4° for flexion/extension. The RMSEs of translational kinematics were 4.2 mm for anterior/posterior translation, 3.3 mm for distal/proximal translation, and 3.2 mm for medial/lateral translation. The Pearson correlation of coefficients values was between 0.964 and 0.999 for angular kinematics and 0.883 and 0.938 for translational kinematics.

CONCLUSION

The Opti_Knee gait system exhibited acceptable accuracy and strong correlation strength compared to biplanar fluoroscopy. The Opti _Knee may serve as a promising portable clinical system for dynamic functional assessments of the knee.

A three-dimensional printing navigational template combined with mixed reality technique for localizing pulmonary nodules

OBJECTIVES

Localizing non-palpable pulmonary nodules is challenging for thoracic surgeons. Here, we investigated the accuracy of three-dimensional (3D) printing technology combined with mixed reality (MR) for localizing ground glass opacity-dominant pulmonary nodules.

METHODS

In this single-arm study, we prospectively enrolled patients with small pulmonary nodules (<2 cm) that required accurate localization. A 3D-printing physical navigational template was designed based on the reconstruction of computed tomography images, and a 3D model was generated through the MR glasses. We set the deviation distance as the primary end point for efficacy evaluation. Clinicopathological and surgical data were obtained for further analysis.

RESULTS

Sixteen patients with 17 non-palpable pulmonary nodules were enrolled in this study. Sixteen nodules were localized successfully (16/17; 94.1%) using this novel approach with a median deviation of 9 mm. The mean time required for localization was 25 ± 5.2 min. For the nodules in the upper/middle and lower lobes, the median deviation was 6 mm (range, 0-12.0) and 16 mm (range, 15.0-20.0), respectively. The deviation difference between the groups was significant (Z = -2.957, P = 0.003). The pathological evaluation of resection margins was negative.

CONCLUSIONS

The 3D printing navigational template combined with MR can be a feasible approach for localizing pulmonary nodules.

Deep learning quantified mucus-tumor ratio predicting survival of patients with colorectal cancer using whole-slide images

BACKGROUND

In colorectal cancer (CRC), mucinous adenocarcinoma differs from other adenocarcinomas in gene-phenotype, morphology, and prognosis. However, mucinous components are present in a large number of adenocarcinomas, and the prognostic value of mucus proportion has not been investigated. Artificial intelligence provides a way to quantify mucus proportion on whole-slide images (WSIs) accurately. We aimed to quantify mucus proportion by deep learning and further investigate its prognostic value in two CRC patient cohorts.

METHODS

Deep learning was used to segment WSIs stained with hematoxylin and eosin. Mucus-tumor ratio (MTR) was defined as the proportion of mucinous component in the tumor area. A training cohort (N = 419) and a validation cohort (N = 315) were used to evaluate the prognostic value of MTR. Survival analysis was performed using the Cox proportional hazard model.

RESULT

Patients were stratified to mucus-low and mucus-high groups, with 24.1% as the threshold. In the training cohort, patients with mucus-high had unfavorable outcomes (hazard ratio for high vs. low 1.88, 95% confidence interval 1.18-2.99, P = 0.008), with 5-year overall survival rates of 54.8% and 73.7% in mucus-high and mucus-low groups, respectively. The results were confirmed in the validation cohort (2.09, 1.21-3.60, 0.008; 62.8% vs. 79.8%). The prognostic value of MTR was maintained in multivariate analysis for both cohorts.

CONCLUSION

The deep learning quantified MTR was an independent prognostic factor in CRC. With the advantages of advanced efficiency and high consistency, our method is suitable for clinical application and promotes precision medicine development.

Complement C3a induces axonal hypomyelination in the periventricular white matter through activation of WNT/β-catenin signal pathway in septic neonatal rats experimentally induced by lipopolysaccharide

Neuroinflammation is thought to play a pivotal role in the pathogenesis of periventricular white matter (PWM) damage (PWMD) induced by neonatal sepsis. Because the complement cascade is implicated in inflammatory response, this study was carried out to determine whether C3a is involved in PWMD, and, if so, whether it would induce axonal hypomyelination. Furthermore, we explored if C3a would act through its C3a receptor (C3aR) and thence inhibit maturation of oligodendrocyte precursor cells (OPCs) via the WNT/β-catenin signal pathway. Sprague Dawley (SD) rats aged 1 day were intraperitoneally injected with lipopolysaccharide (LPS) (1 mg/kg). C3a was upregulated in activated microglia and astrocytes in the PWM up to 7 days after LPS injection. Concomitantly, enhanced C3aR expression was observed in NG2⁺ oligodendrocytes (OLs). Myelin proteins including CNPase, PLP, MBP and MAG were significantly reduced in the PWM of 28-day septic rats. The number of PLP⁺ and MBP⁺ cells was markedly decreased. By electron microscopy, myelin sheath thickness was thinner and the average g-ratios were higher. This was coupled with an increase in number of NG2⁺ cells and decreased number of CC1⁺ cells. Olig1, Olig2 and SOX10 protein expression was significantly reduced in the PWM after LPS injection. Very strikingly, C3aRa administration for the first 7 days could reverse the above-mentioned pathological alterations in the PWM of septic rats. When incubated with C3a, expression of MBP, CNPase, PLP, MAG, Olig1, Olig2, SOX10 and CC1 in primary cultured OPCs was significantly downregulated as opposed to increased NG2. Moreover, WNT/β-catenin signaling pathway was found to be implicated in inhibition of OPCs maturation and differentiation induced by C3a in vitro. As a corollary, it is speculated that C3a in the PWM of septic rats is closely associated with the disorder of OPCs differentiation and maturation through WNT/β-catenin signaling pathway, which would contribute ultimately to axonal hypomyelination.