Citations

Introduction Postcardiotomy veno-arterial extracorporeal membrane oxygenation (V-A-ECMO) is associated with significant mortality. Identification of patients at very high risk for death is elusive and the decision to initiate V-A-ECMO is based on clinical judgment. The prognostic impact of pre-V-A-ECMO arterial lactate level in these critically ill patients has been herein evaluated. Methods A systematic review was conducted to identify studies on postcardiotomy VA-ECMO for the present individual patient data meta-analysis. Results Overall, 1269 patients selected from 10 studies were included in this analysis. Arterial lactate level at V-A-ECMO initiation was increased in patients who died during the index hospitalization compared to those who survived (9.3 vs 6.6 mmol/L, p < 0.0001). Accordingly, in hospital mortality increased along quintiles of pre-V-A-ECMO arterial lactate level (quintiles: 1, 54.9%; 2, 54.9%; 3, 67.3%; 4, 74.2%; 5, 82.2%, p < 0.0001). The best cut-off for arterial lactate was 6.8 mmol/L (in-hospital mortality, 76.7% vs. 55.7%, p < 0.0001). Multivariable multilevel mixed-effect logistic regression model including arterial lactate level significantly increased the area under the receiver operating characteristics curve (0.731, 95% CI 0.702–0.760 vs 0.679, 95% CI 0.648–0.711, DeLong test p < 0.0001). Classification and regression tree analysis showed the in-hospital mortality was 85.2% in patients aged more than 70 years with pre-V-A-ECMO arterial lactate level ≥6.8 mmol/L. Conclusions Among patients requiring postcardiotomy V-A-ECMO, hyperlactatemia was associated with a marked increase of in-hospital mortality. Arterial lactate may be useful in guiding the decision-making process and the timing of initiation of postcardiotomy V-A-ECMO.

Abstract Background: The Tumor Immune microenvironment (TME) plays an important role in tumor development, progression, and treatment response. Recent studies show that spatial heterogeneity of Tumor-Infiltrating Lymphocytes (TILs), consisting of lymphocytic cell populations, is an important histopathologic feature and a powerful prognostic and predictive marker correlating with cancer progression and treatment response. Detecting and quantifying TIL density in Whole Slide Images (WSIs) is, however, labor-intensive, and it is difficult to assess differences in the composition of immune cells. Therefore, it remains a challenge to establish the analysis of TILs in the complex TME. We present an automated spatial image analysis of TILs on gastric cancer to address cancer immunotherapy. Method: 1,031WSIs of hematoxylin and eosin-stained (H&E) formalin-fixed paraffin-embedded (FFPE) sections from four patient cohorts: TCGA-STAD (329), Yonsei-1 (620 patients), Yonsei-2 (45), and St. Mary (37), were analyzed. Two treatment groups in response were classified as CR + PR, while another two treatment groups in non-response were classified as PD + SD. H&E stained WSIs were normalized using the Reinhard normalization method at 20X magnification for reducing the color variability of the stained tissue images. We used U-Net architecture to predict the normalized H&E stained WSIs. Three U-Net models were trained for predicting tumor, TILs, and stroma, using Adam optimizer, 1e-4 learning rate, a binary loss function, L2 regularization, and 50 epochs. The normalized H&E stained WSIs were predicted using the trained U-Net models. Spatial analysis of TILs was conducted on the predicted WSIs. Regional quantification of TILs was performed by two immune phenotype groups: immune-immersed (TILs enriched in tumor cells) and immune-excluded (TILs not enriched in tumor cells but in stromal cells). Kaplan-Meier with a log-rank test was used to evaluate the survival differences between the groups. Results: In TCGA-STAD, the proportion of immune-immersed composition is significantly different from the immune-excluded (p-value 0.05). In Yonsei-1, the immune-excluded composition is significantly different among the three risk groups (p-value 3e-05). In the Yonsei-2 and St. Mary cohorts, including anti-PD1 treated gastric cancer patients, the immune-immersed composition is significantly different between two response groups (p-value 0.007) and represented the diagnostic accuracy (AUROC: 0.78) on CR + PR groups. Conclusion: These findings suggest that the proposed TIL quantification in the complex TME is strongly associated with patient prognosis and anti-PD1 treatment response in gastric cancer. Citation Format: Sanghoon Lee, Sunho Park, Jae-Ho Cheong, Sam C. Wang, Matthew R. Porembka, In-Ho Kim, Sung Hak Lee, Tae Hyun Hwang. Spatial image analysis of tumor-infiltrating lymphocytes on gastric cancer to predict anti-PD1 inhibitor response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1360.

Abstract Background: While immune checkpoint inhibitors (ICI) extend survival for patients suffering from a variety of cancers, most gastric cancer (GC) patients do not respond to ICI. There is a critical need to identify novel biomarkers that guide the use of ICI or strategies to improve outcomes for GC patients. We aim to gain a deeper understanding of the GC tumor microenvironment (TME) to refine the use of ICI using spatial transcriptomes from ICI-treated gastric tumors. Method: We collected 12 pre-ICI treatment gastric tumor samples from five responders and seven nonresponders and performed spatial profiling to investigate spatial heterogeneity, functions, and phenotypes of tumor and neighboring stromal and immune cells to identify features associated with ICI response. We used pan-cytokeratin (pan-CK) to mark epithelial cells, CD45 for immune cells, and smooth muscle actin (SMA) for fibroblasts. We generated gene expression profiles of each cell type within regions of interest (ROI) with a NanoString GeoMx Cancer Transcriptome Atlas panel, comprised of 1,800 genes. A total of 58 ROIs were analyzed from responders and 62 ROIs from nonresponders. Results: We measured the spatial heterogeneity of each cell type in ROIs within and across tumors. We found the tumor, immune, and fibroblasts from nonresponders are transcriptionally more heterogeneous, compared to those from responders. This might indicate a higher degree of intratumor transcriptional heterogeneity is linked to ICI resistance. We found that nonresponse was associated with higher expression of VEGFA and VEGFB in tumor cells and higher ACTA2 in fibroblasts, not in other cell types. These findings are intriguing when considering our other finding that increased endothelial cell and fibroblast proportions in the TME are associated with ICI nonresponse. We also found that the TME of nonresponders had fewer M1 and more M2 macrophages, and there were more T cells that overexpressed gene programs consistent with dysfunction and exhaustion. These findings indicate that ICI-resistant TMEs are densely surrounded by immune-suppressive cellular components which might reduce ICI efficacy and result in ICI resistance. Finally, we performed cell-cell interaction and identified ligand-receptor interactions that are stronger in nonresponders, including CXCL12-CXCR4, CD74-MIF, and LGALS9-LRP1 ligand-receptor interactions. The predicted ligand-receptor interactions are present in cell-type-specific manners, indicating the functional role of each cell type in facilitating ICI response. Conclusion: We investigated how tumor and neighboring stromal and immune cells interact within GC TME to mediate ICI response, which demonstrate that spatial analysis could be used to identify novel biomarkers that predict response to ICI, and new therapies to enhance ICI efficacy in GC patients. Citation Format: Sunho Park, Changjing Hong, Jae-Ho Cheong, Sam C. Wang, Matthew R. Porembka, In-Ho Kim, Sung Hak Lee, Tae Hyun Hwang. Spatial architecture and cellular interactions of tumor immune microenvironment to discover biomarkers and predict immune checkpoint inhibitor response in gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2262.

Abstract Background: The prognostic value of stromal tumor-infiltrating lymphocytes (TILs) as a biomarker for triple-negative breast cancer (TNBC) has been extensively demonstrated in patients (pts) receiving (neo)adjuvant systemic therapy. In addition, several small studies suggest that a subset of pts with early-stage TNBC and high TILs have excellent long-term outcomes, even in the absence of systemic therapy [1-3]. However, data on the absolute risk of TNBC recurrence according to TIL levels in the absence of systemic therapy are limited and critical to inform the design of future systemic therapy de-escalation clinical trials. Methods: We conducted an individual patient data pooled analysis of 12 international cohorts of pts with TNBC treated with locoregional therapy but no systemic therapy. TNBC was defined as tumors with estrogen and progesterone receptor of &lt; 1% and HER2 negative (IHC 0, 1+ or IHC 2+ and FISH negative) per local evaluation. TILs were locally assessed in hematoxylin & eosin-stained slides according to the International Immuno-Oncology Biomarker Working Group guidelines (www.tilsinbreastcancer.org). We used the Kaplan-Meier method to assess survival outcomes according to prespecified TIL thresholds: 30% and 50%. Confidence intervals (CI) for survival probabilities were calculated using a percentile bootstrap method. The primary endpoint was invasive disease-free survival (iDFS, STEEP 2.0 definition). Key secondary outcomes included recurrence-free survival (RFS), distant disease-free survival (DDFS) and overall survival (OS). Results: 1,835 pts diagnosed with TNBC between 1982 and 2017 who did not receive systemic therapy were included. The median age at diagnosis was 56 (IQR 38-71). Menopausal status was known in 1,184 women, of whom 78% were post-menopausal. The median tumor size was 2.0 cm (IQR 1.2-2.6). Most pts (87%) had no axillary lymph node involvement (N0). Most tumors were invasive ductal carcinoma (74%) and grade 3 (70%). The median level of TILs was 15% (IQR 5-40). The median duration of follow-up was 30.4 years (95% CI 29.9, 31.1). A total of 950 (52%) iDFS, 828 (45%) RFS, 767 (42%) DDFS events, and 604 (33%) deaths were observed. In multivariable analyses, higher TILs were independently associated with improved iDFS, RFS, DDFS, and OS beyond clinicopathological factors (likelihood ratio p&lt; 10e-6). Each 10% increment in stromal TILs was associated with an 8% (95% CI: 6-11), 10% (95% CI: 7-13), and 13% (95% CI: 10-15) reduction in the risk of experiencing an iDFS, RFS or DDFS event, and with a 12% (95% CI: 9-15) reduction in the risk of death. iDFS, RFS, DDFS and OS rates according to different TIL thresholds and nodal status are shown in the Table. Of note, the RFS estimates (which exclude second non-breast primaries and contralateral breast cancers) were consistently higher than the iDFS counterparts (which include both), consistent with a high rate of contralateral breast cancers and second primary tumors in this cohort. Notably, patients with node-negative—and especially stage I—TNBC with high TILs had excellent survival rates at 10-year follow-up. Conclusion: TILs are highly prognostic in pts with systemically untreated early-stage TNBC. Pts with pN0 (and especially stage I) TNBC with high TILs exhibited very favorable long-term outcomes even in the absence of systemic therapy. These data define the natural history of TIL-rich TNBC pts and are crucial to identifying the optimal patient population for future chemotherapy and immunotherapy de-escalation clinical trials. References: [1] Leon-Ferre et al, 2017, PMID: 28913760 [2] Park et al, 2019, PMID: 31566659 [3] de Jong et al, 2022, PMID: 35353548 Table 5 and 10-year survival endpoints according TIL level, nodal status, and stage Citation Format: Roberto A. Leon-Ferre, Sarah Flora Jonas, Roberto Salgado, Sherene Loi, Vincent De Jong, Jodi M. Carter, Torsten Nielson, Samuel Leung, Nazia Riaz, Giuseppe Curigliano, Carmen Criscitiello, Vincent Cockenpot, Matteo Lambertini, Vera Suman, Barbro Linderholm, John WM Martens, Carolien HM van Deurzen, Mieke Timmermans, Tatsunori Shimoi, Shu Yazaki, Masayuki Yoshida, Sung-Bae Kim, Hee Jin Lee, Maria Vittoria Dieci, Guillaume Bataillon, Anne Salomon, Fabrice Andre, Marleen Kok, Sabine Linn, Matthew P. Goetz, Stefan Michiels. Stromal tumor-infiltrating lymphocytes identify early-stage triple-negative breast cancer patients with favorable outcomes at 10-year follow-up in the absence of systemic therapy: a pooled analysis of 1835 patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD9-05.

AbstractBackgroundRecent advancements in Deep Learning (DL) methodologies have led to state‐of‐the‐art performance in a wide range of applications especially in object recognition, classification, and segmentation of medical images. However, training modern DL models requires a large amount of computation and long training times due to the complex nature of network structures and the large number of training datasets involved. Moreover, it is an intensive, repetitive manual process to select the optimized configuration of hyperparameters for a given DL network.PurposeIn this study, we present a novel approach to accelerate the training time of DL models via the progressive feeding of training datasets based on similarity measures for medical image segmentation. We term this approach Progressive Deep Learning (PDL).MethodsThe two‐stage PDL approach was tested on the auto‐segmentation task for two imaging modalities: CT and MRI. The training datasets were ranked according to similarity measures between each sample based on Mean Square Error (MSE), Peak Signal‐to‐Noise Ratio (PSNR), Structural Similarity Index (SSIM), and the Universal Quality Image Index (UQI) values. At the start of the training process, a relatively coarse sampling of training datasets with higher ranks was used to optimize the hyperparameters of the DL network. Following this, the samples with higher ranks were used in step 1 to yield accelerated loss minimization in early training epochs and the total dataset was added in step 2 for the remainder of training.ResultsOur results demonstrate that the PDL approach can reduce the training time by nearly half (∼49%) and can predict segmentations (CT U‐net/DenseNet dice coefficient: 0.9506/0.9508, MR U‐net/DenseNet dice coefficient: 0.9508/0.9510) without major statistical difference (Wilcoxon signed‐rank test) compared to the conventional DL approach. The total training times with a fixed cutoff at 0.95 DSC for the CT dataset using DenseNet and U‐Net architectures, respectively, were 17 h, 20 min and 4 h, 45 min in the conventional case compared to 8 h, 45 min and 2 h, 20 min with PDL. For the MRI dataset, the total training times using the same architectures were 2 h, 54 min and 52 min in the conventional case and 1 h, 14 min and 25 min with PDL.ConclusionThe proposed PDL training approach offers the ability to substantially reduce the training time for medical image segmentation while maintaining the performance achieved in the conventional case.

Study Design: Case Series and Technical Note, Objective: UBS has been extensively used in open surgery. However, the use of UBS during UBESS has not been reported in the literature. The aim of this study was to describe a new spinal surgical technique using an ultrasonic bone scalpel (UBS) during unilateral biportal endoscopic spine surgery (UBESS) and to report the preliminary results of this technique. Methods: We enrolled patients diagnosed with lumbar spinal stenosis who underwent single-level UBESS. All patients were followed up for more than 12 months. A unilateral laminotomy was performed after bilateral decompression under endoscopy. We used the UBS system after direct visualization of the target for a bone cut. We evaluated the demographic characteristics, diagnosis, operative time, and estimated blood loss of the patients. Clinical outcomes included the visual analog scale (VAS), the Oswestry Disability Index (ODI), the modified MacNab criteria, and postoperative complications. Results: A total of twenty patients (five males and fifteen females) were enrolled in this study. The mean follow-up period was 13.2 months (range 12–17 months). The VAS score, ODI, and modified MacNab criteria classification improved after the surgery. A minimal mean blood loss of 22.1 mL was noted during the operation. Only one patient experienced neuropraxia, which resolved within 2 weeks. There was no durotomy, iatrogenic pars fracture, or infection. Conclusions: In conclusion, our study represents the first report of the use of UBS during UBESS. Our findings demonstrate that this technique is safe and efficient, with improved clinical outcomes and minimal complications. These preliminary results warrant further investigation through larger clinical studies with longer follow-up periods to confirm the effectiveness of this technique in the treatment of lumbar spinal stenosis.

Abstract Summary We recently introduced the Gut Microbiome Wellness Index (GMWI), a stool metagenome-based indicator for assessing health by determining the likelihood of disease given the state of one’s gut microbiome. The calculation of our wellness index depends on the relative abundances of health-prevalent and health-scarce species. Encouragingly, GMWI has already been utilized in various studies focusing on differences in the gut microbiome between cases and controls. Herein, we introduce the GMWI-webtool, a user-friendly browser application that computes GMWI, health-prevalent/-scarce species’ relative abundances, and α-diversities from stool shotgun metagenome taxonomic profiles. Users of our interactive online tool can visualize their results and compare them side-by-side with those from our pooled reference dataset of metagenomes, as well as export data in.csv format and high-resolution figures. Availability and implementation GMWI-webtool is freely available here: https://gmwi-webtool.github.io/. Supplementary information Supplementary data are available at Bioinformatics online.

Heart failure (HF) is a chronic, debilitating condition associated with significant morbidity, mortality, and socioeconomic burden. Patients with end-stage HF (ESHF) who are not a candidate for advanced therapies will continue to progress despite standard medical therapy. Thus, the focus of care shifts from prolonging life to controlling symptoms and improving quality of life through palliative care ( PC). Because the condition and prognosis of HF patients evolve and can rapidly deteriorate, it is imperative to begin the discussion on end-of-life (EOL) issues early during HF management. These include the completion of an advance directive, do-not-resuscitate orders, and policies on device therapy and discontinuation as part of advance care planning (ACP). ESHF patients who do not have indications for advanced therapies or those who wish not to have a left ventricular assist device (LVAD) or heart transplant (HT) often experience high symptom burden despite adequate medical management. The proper identification and assessment of symptoms such as pain, dyspnea, nausea, depression, and anxiety are essential to the management of ESHF and may be underdiagnosed and undertreated. Psychological support and spiritual care are also crucial to improving the quality of life during EOL. Caregivers of ESHF patients must also be provided supportive care to prevent compassion fatigue and improve resilience in patient care. In this narrative review, we compare the international guidelines and provide an overview of end-of-life and palliative care for patients with ESHF.

Abstract Aims To investigate whether left arterial reservoir strain (LASr) could predict new-onset atrial fibrillation (NOAF) in patients with light-chain-type cardiac amyloidosis (ALCA). Methods and results This study enrolled 427 patients with CA from two tertiary centres between 2005 and 2019. LASr was measured using a vendor-independent analysis programme. The primary outcome was NOAF. A total of 287 patients with ALCA were included [median age 63.0 (56.0–70.0) years, 53.3% male]. The median LASr was 13.9% (10.5–20.8%). During the median follow-up of 0.85 years, AF occurred in 34 patients (11.8%). In the receiver operating characteristics curve analysis, the optimal cut-off of LASr for predicting NOAF was 14.4%. Patients with LASr ≤14.4% had a higher risk of NOAF than those with LASr &gt;14.4% (18.1% vs. 5.1%, P &lt; 0.010). In the multivariate analysis adjusting for confounding factors, including left arterial volume index and left ventricular global longitudinal strain (LV-GLS), higher LASr (%) was independently associated with lower risk for NOAF [adjusted hazard ratio (aHR): 0.936, 95% confidence interval (95% CI): 0.879–0.997, P = 0.039]. Furthermore, LASr ≤14.4% was an independent predictor for NOAF (aHR: 3.370, 95% CI: 1.337–8.492, P = 0.010). This remained true after accounting for all-cause death as a competing risk. Compared with Model 1 (LV-GLS) and Model 2 (LV-GLS plus LAVI), Model 3, including LASr showed a better reclassification ability for predicting NOAF (net reclassification index = 0.735, P &lt; 0.001 compared with Model 1; net reclassification index = 0.514, P = 0.003 compared with Model 2). Conclusion LASr was an independent predictor of NOAF in patients with ALCA.